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Undergraduate Research Project: The Wettability of Templates for Protein Crystallisation

A Crystallisation Study of Savinase® 16.0L

and Termamyl® 120L The Effect of Nanoporous Templates on the Induction Time

and Quality of the Crystals

Jimmy P Olet and Hyewon Hong

Department of Chemical Engineering, ACEX Building, London, SW7 2AZ

Supervisors: Dr. Jerry YY Heng

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Abstract

The crystallisation of proteins is an acute problem from which a solution would be beneficial. There is not only interest from a structural determination perspective, but from a commercial perspective to determine all morphological forms of a protein crystal. Due to the narrow conditions that induce nucleation, the scope to inadvertently miss those suitable, requires addressing. Past research regarding heterogeneous nucleants, has been derived on the idea that amongst a library of pores shapes and sizes, there exists a few which will accommodate the proteins and induce nucleation. This report investigates an alternate methodology where we investigate the problem from the perspective of an optimum pore size, specific to each protein, which induces nucleation. This is investigated with the use of nano-engineered templates; a nucleant with a narrow pore size distribution manufactured with sol-gel methods. The two enzymes studied are the alkaline protease Savinase® 16.0L from Bacillus sp., and Termamyl® 120L (α-amylase from Bacillus Licheniformis). Four pore sizes are tuned to multiples of the Stokes radii of the protein molecules. For Termamyl® 120L, PCS shows the Stokes radius to be 7.6 ± 0.2 nm. We initially test the effectiveness of different screens to induce nucleation, and reduce induction times for the enzymes. We then further assess the reductions in induction time, and improvements in crystal quality with the incorporation of nano-templates, and find increases in the yield, crystal quality, and a reduction in induction time for both target enzymes. Termamyl 120L ® was found to be easier to crystallise and we observe more significant reductions in the induction time to 90 ± 90 minutes, and diffraction quality crystals after 24 hours as upper limits upon the use of a Na/K Phosphate Buffer (pH 6.2), noted from high throughput techniques. We also find consistently, interesting crystal habits that arise from the use of this buffer system from as soon as 24 hours. Acknowledgements

We would like to acknowledge the contributions several individuals made to this project. We wish to thank deeply Niklas H. Jahn for his continual support and guidance for the duration of the project. His critical comments and suggestions were most helpful and influenced our learning process. For his help in Photon Correlation Spectroscopy and High Throughput Screening, we are thankful. We are most grateful of his taking time out of his busy schedule to assist us. We wish to thank Dr. Jerry YY Heng for inspirational discussions we had with him, the continual support through the project, suggestions and guidance given, and strong advice provided. We wish to thank Umang Shah for sharing his intellectual property with us, his assistance regarding the nano-templates, and educational discussions to further our understanding. Finally, we wish to thank the SPEL Group, Imperial College London, for their support, provision of help when asked, and helpful suggestions.

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Contents 1. Introduction .................................................................................................................... 1

2. Theoretical Development ............................................................................................... 2

2.1. Classical Nucleation Theory .................................................................................... 2

2.1.1. Limitations and Assumptions ........................................................................... 4

2.2. Crystal Growth ........................................................................................................ 5

2.3. Phase Diagram in Protein Crystallization ................................................................ 6

3. Savinase® 16.0L and Termamyl® 120L (α-amylase) of Novozymes .............................. 7

3.1. Background............................................................................................................. 7

3.2.1. Termamyl® 120L (alpha-amylase form Bacillus Licheniformis) ............................... 8

3.2.2. Savinase® 16.0L (alkaline protease from Bacillus sp.) ............................................ 9

4. The Nano-Templates ..................................................................................................... 9

5. Literature Review ......................................................................................................... 11

5.1. Benefits of Protein Crystallisation .......................................................................... 11

5.2. The Two-Step Theory of Nucleation ...................................................................... 11

5.3. Crystallisation Methods ......................................................................................... 13

5.3.1. Batch Crystallisation ...................................................................................... 13

5.3.2. Micro Scale Batch Experiments ..................................................................... 13

5.3.3. Free Interface Diffusion (FID) ......................................................................... 14

5.3.4. Dialysis .......................................................................................................... 14

5.3.5. Microfluidics ................................................................................................... 14

5.3.6. Vapour Diffusion ............................................................................................ 15

5.3.7. High-Throughput Screening ........................................................................... 18

5.4. Influencing the Kinetics of Crystallisation .............................................................. 22

5.5. Screening Matrices and Solutions ......................................................................... 22

5.5.1. The Relevance of Screening .......................................................................... 22

5.5.2. Crystallisation Parameters ............................................................................. 23

5.6. Induction of Nucleation ......................................................................................... 25

5.7. Heterogeneous Nucleation Investigations ............................................................. 25

5.7.1. Rationale for Incorporation of Heterogeneous Nucleants ............................... 25

5.7.2. Porous Silicon ................................................................................................ 26

5.7.3. Mineral Surfaces ............................................................................................ 27

5.7.4. Heterogeneous Nucleation via Membranes and Membrane Crystallisation .... 28

5.7.5. Heterogeneous Nucleants Derived from Nature ............................................. 28

5.7.6. Computational Modelling of Heterogeneous Nucleation in Pores ................... 28

5.7.7. Surface Structure and the Role of Surface Chemistry .................................... 29

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5.7.8. Outlook for Heterogeneous Nucleation .......................................................... 30

5.7.9. Limitations of Literature Concerning Heterogeneous Nucleation .................... 31

5.8. Nucleation In and Out of Pores – Theoretical and Practical Perspectives ............. 32

5.9. Pore Diameter ....................................................................................................... 34

6. Aims and Objectives .................................................................................................... 35

7. Methodology and Apparatus ........................................................................................ 35

7.1. The Stokes Radius................................................................................................ 35

7.2. Characterisation: Dynamic Light Scattering (DLS) ................................................ 36

7.3. Characterisation: Polydispersity ............................................................................ 37

7.4. Materials ............................................................................................................... 37

7.5. Sample Preparation .............................................................................................. 38

7.6. Hanging Drop Vapour Diffusion Set-up ................................................................. 38

7.7. Nano-Templates Preparation ................................................................................ 39

7.8. Microscopy – Droplet Imaging ............................................................................... 39

7.9. Mosquito Nano-litre Robot .................................................................................... 39

8. Results ......................................................................................................................... 40

8.1. Results of PCS Measurement ............................................................................... 40

8.2. Screens Employed ................................................................................................ 41

8.2.1. Screen 1 ........................................................................................................ 41

8.2.2. Screen 2 ........................................................................................................ 44

8.2.3. Screen 3 ........................................................................................................ 44

8.2.4. Screen 4 ........................................................................................................ 46

8.2.5. Screen 5 ........................................................................................................ 48

8.2.6. Screen 6 ........................................................................................................ 49

8.2.7. Screen 7 ........................................................................................................ 50

8.2.8. Screen 8 ........................................................................................................ 51

8.2.9. Screen 9 ........................................................................................................ 54

8.2.10. Screen 10 ................................................................................................... 55

8.2.11. Screen 11 ................................................................................................... 57

8.2.12. Results of High Throughput Screening ....................................................... 60

8.2.13. Screen 12 ................................................................................................... 61

8.2.14. Screen 13 – Creating a phase diagram using Na/K Buffer (pH 6.2) ............ 64

8.2.15. Screen 14 – Sol Coated Coverslips ............................................................ 67

8.3. The Significance of Crystal Growth on the Inside of the Interface ......................... 68

8.4. Experimental Errors .............................................................................................. 70

9. Conclusion ................................................................................................................... 70

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10. Future work .............................................................................................................. 71

References ......................................................................................................................... 73

APPENDIX ...................................................................................................................... 79

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1. Introduction Due to the success of the Human Genome Project, exciting opportunities have arisen for the treatment of disease. In this instance however, it is the proteins coded by the genes, which are the focus. By crystallising the proteins, scientists can learn more of their structures and their roles and as such, protein crystallisation will be able to contribute to medicinal and industrial uses. NMR techniques are currently effective for structure determination of very small proteins [1]. The most popular method based on its effectiveness, is X-ray crystallography. X-ray crystallography however requires diffraction quality crystals, of which attainment has constantly been a challenge. One protein, which has found uses in medicine in the treatment of diabetes, is the protein insulin. There is evidence that its crystallisation has been contributing to our understanding of how crystals grow, and how the knowledge is helping scientists design new drugs [2]. The proteins this report will focus on are Savinase® 16.0L (alkaline protease from Bacillus sp.), and Termamyl® 120L (alpha-amylase form Bacillus Licheniformis) of Novozymes. Savinase® 16.0L, being a protease, hydrolyses the peptide bonds in proteins dividing them into peptides, and Termamyl® 120L, and α-amylase, facilitates in the hydrolysis and breaking down of starch. As such, a common use for these enzymes is in biological detergent formulations breaking down protein-based stains on fabric, or on hard surfaces such as dishes where they have become state of the art. α-amylase is further used in industrial applications to synthesise or form part of the purification process for products in Bioprocessing. Crystallisation can help us understand the structures of the enzymes and how best to engineer them for medicinal and industrial applications. The enzymes amylase and lipase joined protease as an essential detergent ingredient at a later stage. Shenoy et al. (2001) notes that protein crystallisation carries the potential to revolutionize the production, formulation and delivery of biopharmaceuticals [3], which highlights the perceived benefits from the investigations this report will describe and discuss. Placing proteins in the suitable conditions will prompt them to undergo crystallisation. However, there are multitudes of factors that affect crystallisation. These include factors such as the choice of buffer system and its ionic strength, the pH, and the choice and concentration of precipitant. Further, these factors are dependent on each other, and thus there are no ideal conditions. As such, it is clear to see there is a challenge in crystallising proteins. The mission to find suitable conditions is thus, highly empirical, and given the wide range of techniques that all have their merits, it is clear that no one technique is the best. McPherson (1990) also recommends that once crystals are obtained, the quest to find conditions that provide higher diffraction quality crystals should not be abandoned [4].

Figure 1: Computation representations of protein macromolecules as posted by Martin-Protean

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Due to the perceived value of protein engineering and the design of enzyme substrates and inhibitors in both industry and pharmaceuticals, there is strong motivation and commercial interest to determine the relevant molecular structures and polymorphs of crystals. There is further an increased need to develop a means to quickly and efficiently produce protein crystals that are additionally of diffraction quality if for structural studies [1]. However, as this is not an easy task, research has been made into the use of substrates that cannot only induce nucleation, but can do so with any protein, i.e. universal nucleants. These substrates have included materials such as natural minerals, zeolites, porous glass, and mica, where emphasis has been made on using substrates with a catalogue of pores, of which, a few will accommodate the protein molecule and induce nucleation. In literature, the power of heterogeneous nucleants has been widely documented where they have aided in crystallising “difficult-to-crystallise” proteins. Other works additionally note an increase in the diffraction quality of the crystals obtained, and others highlight the reduction in induction times because of their use. An alternate approach however, is to nano-engineer a substrate with pores sizes tuned to the Stokes radius of the protein – its apparent size – and with a narrow pore size distribution. This substrate is a nanoporous template. The rationale being that there is an optimum pore size in which nucleation of a protein can be induced. This report will focus on this approach. In regards to future prospects in protein crystallisation, there is a dilemma facing researchers is how to develop nucleants, centred on whether to design a nucleant that induces nucleation in all proteins and is hence ‘universal’, or design a protein specific substrate. There is also the manner of delivery of the substrate in which miniaturisation and automation of its addition to the droplet is challenged by the use of a functionalised surface on which the drops will be dispensed [5]. Saridakis (2009) further states that a better understanding of the nucleation process is prerequisite, and subsequent knowledge of how the target protein attaches to the nucleant. Protein crystallisation still presents itself as a powerful tool for protein separation and given its empirical nature, time will tell which route will be taken to develop the universal nucleant. 2. Theoretical Development 2.1. Classical Nucleation Theory One theory used to describe nucleation, is the Classical Nucleation Theory (CNT) which estimates the Gibbs free energy barrier for nucleation to occur, where the system which originally was a homogeneous state, and becomes a heterogeneous state. It is a theory which is widely used to describe the formation of crystals from a supersaturated solution despite its original purpose being to describe condensation of vapour into liquid [6]. Nucleation is a term with a broad meaning used to categorise the reactions leading to polymerisation, or reactions that lead to assemblage. The first steps are energetically less favourable until continual growth occurs, where the free energy barriers have been overcome. Nucleation has two modes: primary nucleation, which is in the absence of crystals, and secondary nucleation, which involves the presence of ‘seeds’. The latter is popular in light of the difficulty of crystallisation where crystals will habitually not form in solution, even when it is highly concentrated with the macromolecule [7]. From a thermodynamic context, nucleation, the formation of crystals, is a first-order phase transition given the barriers associated with forming the crystalline phase from the liquid phase, and has an associated ∆ , the crystallisation enthalpy, a non-zero latent heat, as noted by

Vekilov (2004) [8]. In a protein crystallisation context, nucleation is derived from the condensation of macromolecules to form nuclei, where a change in the Gibbs free energy occurs during the formation of the nucleus and during nucleus growth, until a critical size called the ‘critical

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radius’ is attained. Nucleation is thus prerequisite in protein crystallisation. For this phase transition, the degree of supersaturation or supercooling is the driving force. Supersaturation is defined as the amount of solute in excess of that which can be dissolved within a given solution at thermodynamic equilibrium [9]. The equation, shown in Equation 1, is the CNT equation where, G, is the Gibbs free energy, r, is the size of the cluster, Gv is the volume free energy, and , is the interfacial energy. The equation is characterised by two terms, which highlight their competition in order for nucleation to be favourable. The first is the energy gained per unit volume to create the new bulk phase (growth), which is favourable. The second, is the energy sacrificed to overcome the interfacial surface energy, , of each phase by the system to create a new surface, and favours the dissolution of the solid phase [10]. The resultant (free) energy required for nucleation is the summation of both these terms. The nucleation process becomes favourable when the change in Gibbs free energy is negative [6]. However, a limitation in which there has been much study, is that even at conditions of thermodynamic stability, an energy barrier of entropic origin exists that must be overcome to allow the initial nucleus to continually grow into a crystal. Due to the low entropic state of the crystalline phase, there must be a (negative) gain in enthalpy to ascertain a negative Gibbs free energy [5].

Equation 1

Equation 2 In Equation 2, G is the Gibbs free energy, T, is the temperature, H, is the enthalpy, and S, is the entropy. When conditions exist where crystal growth is thermodynamically favourable, the (negative) enthalpy gain attributed to the incorporation of a molecule into the bulk crystal, exceeds the loss in entropy (ΔH outweighs ΔS). However, the formation of the crystal surface leads to a lower than required enthalpic gain, and as long as the enthalpic gain does not outweigh the loss in entropy, the system overall will be subjected to a barrier to nucleation [5]; i.e. ΔH must be more negative than ΔS. This, in essence, highlights the fact that the favourable creation of bulk volume is in competition with the unfavourable creation of a new surface. In Equation 1, the first term scales as the radius cubes, and the second term, sales as the radius squares. This gives the shape of the curve shown in Figure 2. Mathematical analysis shows that beyond a critical radius of the nucleus, R*, the contribution of the bulk volume to the free energy favourably exceeds that of the surface interfacial energy contribution, and so crystal growth is no longer limited energetically. The collection of macromolecules can then be termed a critical nucleus, free to grow spontaneously. Another way to describe the phenomenon is that for any nucleus size greater than the critical radius, the nucleus experiences a lowering of free energy and becomes more stable as it grows [11]. Due to the energetic challenges attributed to the nucleation process, this phenomenon has been termed as “one of nature’s greatest triumphs” in the past. The values of R* and can be found by mathematical analysis of the CNT equation

(∆ =

Equation 1) at R* (the

critical radius), the critical size at which the value of the change of Gibbs free energy peaks.

thus:

[

]

Leading to:

Equation 3

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Substituting this result back into the CNT equation (Equation 2), the following result can be obtained:

Equation 4

Figure 2: The graph above represents the energy barrier for nucleation as a solid line - the

Gibbs free energy ( ) as a function of R, the aggregate size. The dashed lines represent the free energy contributions of surface formation (which costs energy) and volume creation

that releases energy. R* represents the critical radius. *, represents the energy barrier for nucleation. When R is less than R*, intermediate aggregates form and subsequently redissolve. When the reverse is true, a nucleus can spontaneously grow and form a crystal. This figure was adapted from figures within Boistelle (1989) [12] and Manuel Garcia-Ruiz (2003) [11]. 2.1.1. Limitations and Assumptions

Dr R.P.L. Sear also notes that nucleation only takes place at constant pressure and temperature [13] and is additionally an assumption of this theory. The macromolecules condense into aggregates that are modelled as spheres with uniform density internally. For crystallization this theory also assumes that monomer bonding is inherently ordered, and so the molecular structure in a nuclei is indistinguishable to a large crystal as shown in Figure 3 [11]. Experimental evidence disputes this. Yau and Vekilov (2000) used atomic force microscopy to witness nucleation and notably reported that for apoferritin the nuclei were flat and “raft” like, rather than spherical as CNT assumes [11, 14]. The theory also assumes that aggregate growth occurs by the addition of a monomer, ignoring the addition of existing aggregates or the breaking of an aggregate into smaller parts, and that the aggregates do not rotate, vibrate or move. The aggregates are also assumed incompressible. The theory also analyses nucleation independently of time, and thus is based on steady state kinetics [6]. The surface energy of the aggregate is also assumed isotropic, which breaks down in light of non-spherical aggregates. Further, as the crystal grows, there are fluctuations in the density order parameter due the formation of the denser crystalline phase; reportedly, the only order parameter considered in the classical nucleation theory. This is untrue for nucleation from solutions. It has thus been understood for a century that there are two order parameter fluctuations: density and structure. As such, the two parameters are merged into one single-phase order parameter [15]. In other words, the molecules aggregate and simultaneously reorganise themselves in an array. However, this has fallen into dispute over the past decade and has prompted the formulation of an alternate “Two-step nucleation theory”. This describes how molecules aggregate in an initial step, then reorganise into an array in a second step. Literature, suggests that the

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theory is more representative of nucleation from experiments, theoretical study and computational simulation. This will be discussed later highlighting work be researchers such as Erdemir et al. (2009) [6], Oxtoby (2003) [16] and Vekilov (2004) [15] among others. 2.2. Crystal Growth

During the formation of the critical nuclei, the solution is at a metastable state where the surface energy of small crystals is sufficient to be relatively thermodynamically stable. A free energy barrier must be overcome, granted by sufficient supersaturation, prompting the instability of the preceding phase. This causes fluctuations in the density and structural order parameters resulting in a new phase [15] A theory that explains crystal growth as molecules are incorporated into the bulk crystal is the Terrace Ledge Kink (TLK) theory that suggests that growth is facilitated by the presence of surface irregularities, specifically, kinks on the crystal surface as shown in Figure 4 [17]. The Kossel model, represents the protein molecules as cubic units and has the units in a more structurally stable configuration by bonding with multiple facets, hence preventing its dissolution back into solution [18]. Vekilov (2007) states that the number of kinks per unit area, and enthalpic and entropic barriers for incorporation, determine the growth rate of a crystal [17]. In the Periodic Bond Chain theory outlined in Boistelle and Astier (1988), the faces of crystal growth are flat face, stepped face, and kinked face. The rate of growth is additionally in this order. Flat faces call for two-dimensional nucleation to induce growth, i.e. the formation of sheets of molecules. Stepped faces, commonly occurs because of spiral growth aided by a crystallographic screw axis [19] requiring only one-dimensional nucleation. Kinked faces do

Figure 3: a depiction of how the crystal can grow; the molecules here are assumed spherical. They subsequently aggregate and simultaneously arrange themselves in a crystalline structure. This was taken from Garcia-Ruiz (2003)

Figure 4: A diagrammatic representation of a kink face on the face of a crystal. Taken from Figure 1, Vekilov (2007)

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Figure 6: A computational representation of a protein folding

not require nucleation to promote further growth, and as a result grow the fastest and allow for continuous growth. It is thus clear to see that the nature of the growing crystal face controls the crystal growth rate [12, 19]. At metastable stable conditions crystal growth is thermodynamically favoured but the magnitude of supersaturation is not sufficient to yield spontaneous nucleation within a practicable timescale. The amount of supersaturation of the solution, with respect to the macromolecule, is proportional to the ease of formation of a critical nucleus due to the lower energy barrier. This is also shown in Figure 5 below [11]; the higher the supersaturation is, the lower the thermodynamic barrier to nucleation is. As the amount of supersaturation increases, there arrives a point where the size of the critical nucleus becomes smaller than the smallest structural unit. At this point, activation barriers break down and an amorphous phase forms [11]. However, detrimental effects can arise from excessive supersaturation. The resultant high nucleation rate creates numerous small crystals that limit space, and consumes the macromolecule limiting growth. Additionally, should an impurity-enriched zone form, impurities (foreign molecules, imperfect folding to name a few) can amalgamate quickly, thus reducing crystal quality [20]. Protein molecules also exhibit the ability to fold resulting in a large number of possible arrangements. Only one of them, however, is the most thermodynamically stable having the lowest free energy and thus, the greatest structural stability. The protein molecules must have sufficient time in which to “try” various orientations. A lack of time can lead to structural defects and thus a lower quality crystal, and even cease crystal growth. 2.3. Phase Diagram in Protein Crystallization Figure 7 depicts the phase diagram associated with protein crystallisation. It highlights the relationship between protein and adjustable parameters, which could include pH, temperature, precipitant concentration, or additive concentration [21]. Protein crystals require supersaturated solutions in order to form. Likewise, if the solution is undersaturated, it will

Figure 5: a graphical depiction from Garcia-Ruiz (2003) showing the how the degree of supersaturation, S, influences the energy barrier to nucleation.

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Figure 8: An assortment of protein and virus crystals grown for the purpose of X-ray diffraction under a variety of conditions

Figure 7: the phase diagram associated with nucleation. The major methods of crystallisation are highlighted on the diagram with (i) microbatch, (ii) vapour diffusion, (iii) dialysis and (iv) FID. It shows the dependence of protein concentration with “adjustable parameter” concentration where the adjustable parameter can include precipitant concentration, additive concentration, pH or the Temperature.

cause the protein crystals to redissolve back into solution. The solid line, which separates the distinct phases, is known and the ‘supersolubility curve’. To the right of this curve conditions where spontaneous nucleation occurs are present within a nucleation zone. To induce nucleation, supersaturation must be achieved to cross the supersolubility curve. If conditions are right, the protein concentration will diminish and metastable conditions will be attained. According to Saridakis (2009) and based on the analysis pertaining to CNT, under metastable conditions, the attainment of larger, better order, diffraction quality crystals are more readily formed [5]. Figure 5 [22], shows example of proteins that have been synthesised documented in a paper by McPherson (2004) and show a few of the morphological structures crystalline structures can form. 3. Savinase® 16.0L and Termamyl® 120L (α-amylase) of Novozymes 3.1. Background Proteases are macromolecules that hydrolyse the peptide bonds in proteins dividing them into peptides in a process called proteolysis, and are categorised into six groups. α-amylase functions in a similar manner facilitating in the hydrolysis and breaking down of starch. Thus,

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an application of this process is in the breakdown of protein-based stains on fabric or on hard surfaces such as dishes, where the proteins are broken down into smaller fragments. Other components of the washing liquor facilitate the removal of these fragments. As such, proteases have found use in laundry detergents worldwide aiding in the removal of tough stains such as grass and cocoa where they have become state-of-the-art. Proteases and α-amylases are currently essential components of biological detergent formulations due to safety and environmental concerns. They have made possible the development of detergents that function well at lower dosages, have reduced alkalinity, and lower operating temperatures. Additionally, given the performance profile of proteases and α-amylases as one of the active ingredients of biological detergents, there is a search for better performing enzymes via microbiological screening or protein engineering. Unlike low yield pharmaceuticals, these enzymes are manufactured as bulk chemicals. α-amylase is further used in industrial applications to synthesise or purify products in Bioprocessing. Crystallisation can help us understand the structures of the enzymes and how best to engineer them for industrial applications. Later, the enzymes amylase and lipase joined protease as an essential detergent ingredient. Despite the effectiveness of these enzymes in removing stains as laundry detergents, they only started being incorporated in dishwashing detergents in 1990s highlighted in a paper by Dalgaard (1991), the main reason being the conditions with which the formulations would be a part of during storage, and during use. The pH and ionic strength of the washing liquor have a very strong influence on the enzymes performance, and so the components of the final detergent are carefully chosen to complement the operating pH of the enzymes and ensure their optimal performance. The choice of anionic surfactant for example is carefully considered, and the addition of phosphate builders to reduce calcium concentrations in the wash liquor is required to maximise performance. Surfactants also can influence the performance and stability of the protease. Structurally, commercial detergent proteases are very similar having serine monomer active sites, and Ca2+ ions responsible for their thermal stability. Burrows, states that most commercial detergent proteases are classified as subtilisins which are extracellular serine endo-peptidases [23]. There are those that possess maximum activities in high pH, and are thus highly alkaline such as Maxacal and Savinase, and those that are less alkaline. They have a molecular weight between 20 and 30 kDa, and further possess a serine monomer in the active site as is evident in Figure 10. The proteins this report will focus on are Savinase® 16.0L (alkaline protease from Bacillus sp.), and Termamyl® 120L (alpha-amylase form Bacillus Licheniformis) of Novozymes. 3.2.1. Termamyl® 120L (alpha-amylase form Bacillus Licheniformis) Termamyl® 120 L, by Novozymes is a commercial α-amylase obtained from Bacillus Licheniformis, a bacterium commonly found in soil, via fermentation. The bacterium is cultured in order to obtain the α-amylase. Because of the nature of its adaption to high pH, the macromolecule can withstand high pH levels, thus making it ideal for use in biological washing formulations and in dishwashing detergents where it facilitates the hydrolysis and breakdown of starch. The molecular weight is approximately equal to 58 000 Da, and a representation can be seen in Figure 9 from Fitter et al. (2004) [24]. The figure shows a representation of the enzyme showing the calcium ions depicted in red, and sodium ions depicted in orange, which are responsible for its structural stability. The optimum pH is reported to be between 6 and 9 with application temperatures ranging from 25 to 100°C, which are beneficial for storage, and operation in the washing liquor. This creates advantages such as a lower energy requirements as α-Amylases act to increase detergent performance at lower wash temperatures, and yield milder detergent chemical systems [23].

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Figure 10: A schematic plot of the backbone of Savinase® centred on the active site of the macromolecule (Ser221) as depicted by Betzel (1992). It highlights Ile35, Thr57, and Gly161 residues, and the Ser221 binding site with an arrow. The figure also labels the two Ca2+ binding sites (Cal and Ca2).

Figure 9: Three-dimensional structures of α-amylase from Bacillus Licheniformis (BLA)

Experiments have further revealed that the addition of small amounts of calcium salts can enhance the stability of the calcium-dependent α- amylases [23], perhaps increasing likelihood of crystals. 3.2.2. Savinase® 16.0L (alkaline protease from Bacillus sp.) Savinase® 16.0L is an alkaline protease from Bacillus sp. which is an aquatic microbe [25]. The protease is characterised by a high isoelectric point (pI) of approximately 10 and is most active between pH 7-11 with high thermal stability at alkaline pH. The enzymes application temperature is between 15 and 75°C. Savinase® 16.0L has been commercialised by Novozymes with uses as a detergent enzyme where it functions as a protease. To do so, it must be active at the pH of detergent solutions (between 7 and 11) and at relevant wash temperatures (4 to 60 °C). The protein comprises 269 amino acids with a size of 28 kDa [26]. There are two Ca2+ ions labelled CaI (the high affinity site) and Ca2 in Figure 10 present in the backbone, with the high numbers of bridges suggested by Betzel (1992) to be the source of its thermal stability [27]. 4. The Nano-Templates These templates are typically mesoporous. The pores with diameters that have been designed to have pore sizes from 2 nm to 50 nm that are multiples of the Stokes radii with narrow pore size distributions. They are additionally designated Template A, Template B, Template C, and Template D due to intellectual property. They are categorised as nanoporous glass and are referred to as “Templates A/B/C/D”, templates, nanotemplates and nanoporous glass. The pore sizes are tuned to the sizes of the protein molecules Stokes Radius, which is one of their characteristics as the protein crystals are hydrates and solvates. The protein molecules diffuse into the pores, and from a two-step nucleation perspective, create a local dense phase of protein. The crystal will then form within this dense phase. The porous substrate also acts to stabilise the protein molecule by locally immobilising the molecules

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within the pores. This specific surface is one that has been engineered to restrict the degrees of rotation of the target protein and provide the maximum thermodynamic stability, locking them in their native orientation as the protein molecules diffuse into the pores of the nanoporous glass. The nanoporous glass templates operate based on providing a surface for nucleation. As the proteins assemble in arrays and are flexible molecules, the rate-limiting step is the bonding process as the protein tries various orientations whilst bonding to a neighbouring macromolecule. If there is a thermodynamic motivation for it to break the bonds it has formed or bond elsewhere, then a crystal is unlikely to form. They are synthesised using sol-gel based methods. Silica is used to minimise cost as silicon is a relatively cheap material and so will be useful for mass production emphasising economies of scale. Due to the protection of intellectual property, it is not possible for us to divulge the exact fabrication process of the nanoporous glass. It was further beyond the scope of the project to manufacture them. First, a surfactant is dissolved in an acid at room temperature. A silicon precursor is subsequently added drop wise to the solution and stirred for until the desired solution is attained undergoing various polycondensation and hydrolysis reactions. This reaction is an example of a ‘sol-gel’ process commonly used in material science. The surfactant then facilitates the control the pores size in the 3D porous network via the addition of organic solvents. The Sol product then undergoes additional conditioning processes in various steps with each stage requiring certain temperature, pressures, and times. The template is then extracted from the Sol-product either by acid treatment or via sintering. The final product is that of a fine powder which can then be administered to the crystallisation drop. Alternatively, the sol can be prepared as a solution to coat the cover glass slides. The sol is produced in a similar method as before but with variations in the acid used and volumes. Again, the solution is stirred until the desired solution is attained.

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5. Literature Review

5.1. Benefits of Protein Crystallisation

There are a range of benefits that encompass protein crystallisation and as such, the results of this project could have significant implications. One benefit that arises is the isolation and purification of proteins. In industrial applications were they have uses, this can act to streamline the manufacturing process and in turn, reduce the cost of the resultant products, be they biopharmaceuticals, or mass-produced such as the enzymes in detergents. Judge et al. (1998) performed experiments to determine the effectiveness of crystallisation to separate a model protein from a mixture of proteins and their results highlight the feasibility and purifying potential of protein crystallisation [28]. Secondly, by crystallising proteins, they become more stable. From a pharmaceutical point of view, this can result in the sustained release of a drug, and reduce chemical degradation possibly increasing the drug’s effectiveness. Govardhan et al. review Crosslinked Enzyme Crystals (CLEC®) and note the enhanced stability of the enzyme allowing a more diverse range of reaction conditions, and exhibit two to three orders of magnitude greater stability than the soluble enzyme [29]. Could this be applied industrially? Can they be utilised in our detergents so that more efficient chemistry takes place, enhancing their efficacy and storage potential? Proteins crystals can also be engineered to control the morphology. Vivares et al. (2006) experimented with urate oxidase in PEG solutions and found that by accurately controlling the crystallisation parameters, their group could influence the crystal morphology and selectively control it [30]. These are just three of the various advantages protein crystallisation can bring. 5.2. The Two-Step Theory of Nucleation The two-step nucleation theory is an alternate theory that describes the nucleation of crystals from supersaturated solutions [6]. Erdemir et al. (2008) reviews the shortcomings of classical nucleation theory in detail giving theoretical and experimental instances that suggest that Classical Nucleation Theory may not be the most suitable model in the journey to understanding nucleation. The multitude of discussions and examples suggest that nucleation follows a more complex route where an additional, or alternate, first step is the formation cluster of solute molecules to a sufficient size. The subsequent step is the reorganization of such a cluster into an ordered structure. The paper highlights that the two-step nucleation mechanism may be the cause of most crystallisation processes with the belief based on recent experimental and theoretical studies, including that of their research group, demonstrating the applicability of this theory to macromolecules and to small organic molecules. This mechanism for crystallisation has been proposed, underpinned by experimental studies, simulations and theories, where density fluctuations precede that of structure. In actuality, Talanquer and Oxtoby (1998) support this idea that the two parameters for transition do not necessarily have to occur simultaneously; one can dominate the critical nucleation and serve as a prerequisite for the other one [31]. Oxtoby (2003) [16] and Erdemir et al. (2009) [6] state that there are at least two order parameters, with the observable cases being, changes in density (small or large) and periodic structure (and hence different morphologies even within the same phase locality), are necessary to differentiate sufficiently between old and new phases. Vekilov (2004) additionally highlights this in his review on Two-step theory and its applicability to crystallisation. He further notes that the two order parameters can subsequently be grouped together into a single unified single-order parameter to remain true to classical nucleation theory [15]. This point is reinforced by Erdemir et al. (2009) stating that CNT is limited in its identification the different crystallisation pathways when various order parameters do not change simultaneously [16].

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Figure 11: In the two-step model proposed for protein crystallization, a sufficient-sized cluster of solute molecules forms first, followed by reorganization of that cluster into an ordered structure.

Erdemir et al. (2009) highlights in their review that one of the most significant failings of the classical theory, is the dependence on cluster radius to determine the potential to become a nuclei, suggesting size is the only decisive factor shown in Figure 2. Further, the development of CNT for the condensation of liquid into vapour, has resulted in no distinguishment between crystals and non-crystalline aggregates [6]. Their review also documents work Erdemir et al. (2009) carried out to demonstrate two-step theory such as the nucleation of AgBr in water which showed the formation of stable, disordered prenucleation clusters as large as Ag18Br18 providing further support to that the initial step in nucleation pertains to the formation of disordered clusters [32]. The paper also reports that theoretical studies, in addition to computational simulations provide evidence for the two-step nucleation mechanism where density functional theory has been applied to the study of crystal nucleation. Mathematical analysis in the form of calculations of the concentration profile and Gibbs free energies of the interface between protein crystal and solution confirmed the two-step nucleation mechanism [33]. The authors refer to Schmelzer et al. (2004) [34], highlighting that discrepancies have been found in the experimental and predicted kinetic factors from calculations of the thermodynamic driving force of the transformation using the chemical potentials of the respective macroscopic phases. They suggest that this may have been caused by the neglection of the movement of clusters in CNT, since the pre-exponential factor of the Arrhenius equation is associated with molecular mobility [6]. In regards to the assumption that the clusters are spherical, Georgalis suggests that cubes or polyhedra can represent better lattice forming shapes, adding to the invalidity of the model [35]. Whilst CNT can allow the estimation of the critical nucleus size and nucleation rate, it offers no information about the structure or how the solution transitions from solid to crystal according to Schüth (2001) [36]. Yau and Vekilov (2001) also found that the critical nucleus of apoferritin was organised in planar arrays two monomolecular layers thick arranged like that of a crystal, and so resembled a raft. Using atomic force microscopy, they also found that the nucleus shape cannot be approximated with a sphere because the surface tension is not well defined for cluster sizes smaller than 100 molecules [14]. This disagrees with the CNT assumptions and Erdemir comments that this points to invalidity of the model. Based on evidence supplied by literature, it is clear that Two-step theory is a contending theory for nucleation. It provides sufficient argument to highlight that crystallisation is a two barrier process thermodynamically; the first barrier required for the grouping of molecules being lower than the second, and main barrier necessary to transform them into a stable crystalline nucleus [6]. Figure 11 depicts a representation of the two-step nucleation model [6]. However, in light of this evidence, it is not clear how applicable the model is to protein crystallisation as literature suggests that experiments have not been completed in detail in regards to protein. Most of the experimental evidence pertains to the crystallisation of

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substances such as salts such as AgBr and primary alcohols, acknowledged by Vekilov (2010) [8] in his paper reviewing nucleation. Vekilov also noted that preceding nucleation, the occurrence of amorphous metastable aggregates must be present in solutions under homogeneous conditions to assess the validity of the two-step theory for the majority of untested systems, [8]. He also highlights that despite the theory being proposed for proteins, the mechanism has been more readily observed for colloids, low molecular weight organic materials, polymers, bio-minerals and for calcium carbonate in solution. Though they have been demonstrated additionally for a number of proteins, Vekilov also suggests that it is highly improbable that protein crystallisation solutions will support the existence amorphous precursors in solution for conditions that would allow nucleation of crystals within them [8]. 5.3. Crystallisation Methods Various methods can allow one to crystallise a protein given sufficient conditions and time. But, arguably the most effective based on that fact that vapour diffusion techniques have yielded more crystallised macromolecules that every other method combined [37]. Analysis of the various types will allow the implementation of a better investigation that will meet our aims more closely. Literature documents many examples one can implement in order to crystallise a protein. This section highlights the principle methods based on literature and we seek to take this knowledge to choose the crystallisation method we will implement. 5.3.1. Batch Crystallisation Chayen (1998) [38] gives a description of this method in her topical review of microbatch and vapour diffusion techniques. One mixes the protein in question and the necessary crystallising agents at their final concentrations at the beginning of the experiment. The mixing that follows facilitates supersaturation, and conditions only change when and during the precipitation of the protein out of solution into the growing crystals. As can be seen from Figure 7, there is evidently less exploration of the phase diagram, and Chayen further suggests that a single vapour-diffusion experiment is able to replace a several microbatch experiments [38]. Due to the large amount of material that is required to implement the method, the batch method is not widely used and thus, the microbatch technique was developed, where smaller crystallisation sample volumes are dispensed as small drops under oil, overcoming this issue with batch. Other difficulties (discussed below) arising from diffusion methods are also absolved. 5.3.2. Micro Scale Batch Experiments The method known as “micro-batch” is a method well documented in reviews of crystallisation techniques owing to the evolution of the method from batch crystallisation, applicability to high through-put methods requiring a robotic dispenser [1], and ease of handling [21]. The method involves the dispensing of nano-litre volumes of crystallization drops, incubated under low-density (0.87 g cm-3) paraffin oil as shown in Figure 12. The method is a variation of “batch crystallisation” but uses much smaller volumes in order to conserve the sample. The crystallisation drops remain submerged beneath the oil, as they are denser than the oil, protecting them from the effects of contamination, physical shock, and evaporation. Vapour

Figure 12: A schematic of the microbatch well. The sample droplet is submerged in low density paraffin oil to shield from contamination and evaporation. Taken from Chayen (1990)

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diffusion methods are dynamic in that their conditions change throughout the duration of the experiment, or until equilibrium is achieved. In micro-batch however, there is less exploration of the phase diagram as the samples undergo mixing at their final concentration preceding the experiment [21] triggering supersaturation upon mixing [37]. As such, the variables pH and volume are constant and a further benefit is that the crystals do not dissolve into the oil [38]. Bolanos-Garcia and Chayen (2009) [37] review current crystallisation techniques in their paper as one of their aims, and present a development by D'Arcy et al. (1996) [39]. By applying a mixture of silicone oil and paraffin oil, “Al's Oil”, in a 1:1 ratio by volume that covers the drop, the crystallization drop can concentrate thus facilitating a screening effect similar to that of vapour diffusion [37]. This allows the extensive sampling of the crystallisation parameter space analogous to vapour diffusion techniques according to Chayen and Saridakis (2008) [21]. Microbatch experiments are additionally the easiest to implement [21], and lend their use well to high throughput screening. This is beneficial as McPherson (2004) [22] states that carrying out 1000s of experiments is vastly impractical for many labs. This is in addition to the difficulty of manually working with such small volumes [38]. The method can be used for almost all known buffers, precipitants, additives, detergents, glycerol, and ethanol except volatile organics, such as phenol or dioxane, due to the dissolution of the volatile organic into the oil. Chayen and Saridakis (2008) note that labs with high throughput capabilities are able to perform thousands of screens per protein with the number falling to the region of 300-500 for independent labs [21]. 5.3.3. Free Interface Diffusion (FID) In Free Interface Diffusion (FID), also known as “Liquid/ Liquid Diffusion”, one places the protein and precipitant solutions adjacent to one another. One solution slowly diffuses into the other creating a concentration gradient that is time dependant [40]. Chayen (2008) [21] states that the system consequently ‘self-selects’ the optimal nucleation and growth supersaturation levels for the system. It is then noted that once suitable screening conditions have been found, this technique can prove powerful as a fine-tuning method [37]. There are versions of this technique that would allow multiple screening via the use of a crystallisation where capillaries can be concurrently charged with protein solution allowing the individual capillaries to come into contact with a different well containing a precipitant solution as implemented by Moreno et al. (2002) [41]. There exists several variations to the standard method such as diffusion into or from gelled solutions [41] such as a gel acupuncture method pioneered by Garcia-Ruiz et al. (2003) where the precipitant agent permeates through gel into a capillary filled with protein solution [42]. 5.3.4. Dialysis Chayen and Saridakis (2008) [21] document another method known as Dialysis in her review of protein crystallisation techniques. In the dialysis method, a process similar to that of membrane separation occurs. A semi-permeable membrane allows for the extraction of the protein from the precipitant solution. This allows the precipitant solution and protein molecules to mix albeit slowly, which cannot cross the membrane. Chayen suggests that method requires expertise, but offers a different route across the phase diagram [21]. 5.3.5. Microfluidics Another technique, which has gained interest in protein crystallisation, is the use of microfluidics. It is a practice that confines fluid in typically sub millimetre channels on a microfluidic chip and integrate complex chemical and biological trials on a micro fabricated chip [43]. Hansen and Quake (2003) [43] documented the use of microfluidic chips for high throughput crystallization screening, notes the unprecedented savings in time, and costs from minimal protein utilisation facilitating economies of scale. Hansen also suggests that by

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using microfluidics, one can harness the physics associated with fluid flow in micro channels and mass transport within the channels for the benefit of crystallisation [43]. Chayen claims however, that the benefit of using micro fluidics is offset by the requirement of dedicated and relatively expensive equipment and consumable materials, contrary to Hansen [21]. Sommer (2005) [44]reports that the use of microvalve-controlled microfluidic chips in experiments improved the number of successful conditions compared to that of conventional screens [44]. A schematic of the microfluidic chips used by Li and Ismagilov (2010) in their work on protein crystallisation is shown in Figure 13 below [45]. The method was originally intended to be relevant to microscale FID, but bears parallels to micro batch where the nano-droplets are dispensed within microchannels where they circulate. Work of this manner is discussed by Zheng et al. (2005) where nano-litre “plugs” (droplets) are formulated, dispensed within capillaries, and crystals growth is witnessed within the capillaries with the aim of understanding mixing in nucleation of crystals [46]. 5.3.6. Vapour Diffusion The method of vapour diffusion is the most widely used for crystallization and has proved to be widely successful. The protein solution is arranged in one of two set-ups: is hanging drop, which relies on the suspension of a drop containing macromolecule and crystallisation agent by surface tension on a cover slip [47], and sitting drop, where the droplet sits on a raised surface within the well. In hanging drop vapour diffusion, the cover slip is sealed over the reservoir with silicon gel to create a barrier. In sitting drop, the well is sealed with clear acetate. The respective volumes of the droplet and reservoir are 200 nL – 20 μL, and 20 μL – 1mL. In both configurations, water evaporates from the drop and enters the reservoir where the protein and crystallising agent concentrations increase and equilibrate. The reservoir contains crystallizing agents (buffer, precipitant, additives) at a higher concentration than that in the drop in order to create an artificial concentration gradient. This way, supersaturation can be induced leading to nucleation and crystal growth. Vapour diffusion, is a dynamic process with little freedom for control once set up due to the changing conditions. Chayen (1998) [38] states is vital in the formation of a crystal as there is extensive sampling of the parameter space. Referring to the phase diagram, the pathway followed is that directed by arrow (ii) in Figure 7. If the precipitant concentration is sufficient to cause nucleation, the protein concentration will diminish and the “route” will propagate toward the metastable zone [48, 49] where the crystal grows. Figure 14 shows a diagrammatic representation of the hanging drop configuration [50].

Figure 13: (a) A representation of a micro-fluidic chip used in protein crystallisation with the microbatch method. Different colours indicate different reagents with varying concentrations in the wells. (b) A schematic of the layout of the chip. From Li and Ismagilov (2010).

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There has been research into how the equilibration rate can be influenced to attain supersaturation more slowly. Luft (1994, 1996) documents one method, which involves altering the height of the drop from the reservoir. This controls the growth of the crystals [47, 51]. He states that the kinetics of water equilibration i.e. the rate at which water leave the hanging-drop determines the rate at which supersaturation is attained [47, 51]. If water diffuses from the hanging drop to the reservoir at a slower rate, the relative concentrations of the two volumes changes accordingly, and so the path through the different phases will vary. If one wishes it, one can alter the concentration of the drop simply by transferring a cover slip from one reservoir to another, or adding additional buffer solution to the droplet, which is free of protein [21]. Chayen and Saridakis (2008) [21] describe that by employing this, the number of nuclei can be limited. However, form an analytical point of view, should one wish to analyse the process of crystal growth i.e. examine the phases pertaining to nucleation and growth, one would hit barriers [38]. Further, Chernov (2003) [52], found that biomolecular crystals usually crack when transferred from solution to solution, as demonstrated in an experiment where lysozyme crystals were transferred from the original solution with a precipitant concentration of 3% wt of NaCl, to hypertonic (14% wt NaCl) and hypotonic (1% wt NaCl) solutions. The effect was more notable where the concentration differences between the original and new solution was greatest possibly due to the osmotic pressure differences between the intra-crystalline and the external solutions [20]. 5.3.6.1. Known and Possible Limitations The main limitation however, is reportedly the time it takes for the crystals of a particular quality to grow [53]. Chayen and Saridakis (2008) [21] states that evaporation, contamination, and mechanical shocks can be deleterious to results. They further comment that there are instances when vapour diffusion is not an ideal method due to the uncontrollable changes that occur in the volume of the drop and composition during crystallisation, the pH changes that may arise from volatile ions, and temperature fluctuations that cause the crystal to dissolve back into solution. Furthermore, transportation of trials is often difficult due to their delicate nature [21]. Another factor that is not examined is the prospect of density driven convection currents developing in the droplet. Diffusion refers to what is happening within the drop as water evaporates from the drop to the reservoir solution; nevertheless, convection is the process that dominates the transport of protein molecules to the crystal [54]. Further, as the protein crystal grows, a protein depleted zone around the crystal forms, which promotes further convection to the site. Luft (1994) [51] gives a reason they arise as follows. Usually when experiments are set up, a 1:1 volume ratio is used to mix the protein and crystallisation agents and then subsequently seal the droplet over the reservoir with an oil barrier. The initial concentration of crystallizing agent in the droplet is thus half that in the reservoir, with

Figure 14: Diagram of hanging drop method. Reservoir solution usually contains buffer and precipitant. The protein solution (hanging drop) contains the same constituents, but in lower concentrations. The protein solution may also contain trace metals or ions necessary for precipitation of particular proteins. For instance, insulin is known to require trace amounts of zinc for crystallization.

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Figure 15: a 24 well plate commonly employed for hanging-drop vapour diffusion on the left, and a 96 well plate for use in microbatch and in hanging drop, implemented robotically

the concentration gradient being Δ[C] = [C]reservoir - [C]drop = [C]reservoir/2. When [C]reservoir is large, the evaporation rate of water from the droplet to the reservoir is high. Rapid dehydration accompanies this establishing a solute convection current [55]. Due to the concentrations of the crystallising agent and protein rising quickly at the surface of the droplet, density gradients are also established, which, in the earth gravitational field create convection currents [51]. Bergfors (2009) [54] reports that due to convection, the sedimentation of crystals, and convection due to crystal growth has been observed. This convection has been the subject of many investigations and is thought to be detrimental to crystal quality. Speculation has also been made into the cessation of growth due to convection in the hanging drop instigating surface contamination [56]. Other suggestions are that the shear forces remove protein molecules from the surface of the crystal as they are held by weak bonds [57], and that variations in temperature and concentration can create local growth irregularities reducing growth potential. More suggestions are made by McPherson (1993) [58]. Methods which Bergfors (2009) suggests to limit this effect includes conducting experiments in microgravity. McPherson (1993) states that seemingly, the absence of gravity reduces density driven convection and/ or sedimentation. This in turn allows a more deliberate and graceful entry of individual molecules into the crystal lattice [58] resulting in improved morphology and diffraction quality of the crystals. The second way is to use a viscous gel such as agarose (0.1% concentration where it is still a liquid and not a gel) to increase viscosity. The third way involves using capillaries (200 μm or less) so that buoyancy forces are outweighed by diffusive processes [54]. A further method proposed by Luft (1994), requires diffusion cells to equate the initial concentration of the crystallising agent to that of the reservoir, or sufficiently deep reservoirs to avoid rapid dehydration. This way, convection currents caused by density differences can be negated too [51]. Further, the difference in effectiveness of hanging drop as opposed to sitting drop is rarely visited. An webpage by Rupp (2000) which discusses high through-put screening sought to address this question given his suggestion that there is no statistical evidence to prove that one method is better than the other [59]. They tested this with ConA and Lysozyme, which are termed “easy-to-crystallise” proteins, in four 96-well plates. All variables were held constant except the vapour diffusion method. Their results suggested no marked difference between the two methods, but one must also note that it is unpublished work and can be subject to scrutiny. Perhaps a detailed investigation can be made into the most effective method. One would typically use 24-well plates to implement the screens, charged with 0.5–1 mL reservoir solution. Figure 15 illustrates 24 and 96 well plates used for screens. At the micro scale, 96-well plates are standard. Manufacturers of these plates include Hampton Research or Molecular dimensions. To summarise, Chayen suggests that for ease of use, microbatch techniques are the method of choice for the novice. However, for the extensive sampling of the crystallization parameter

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space, the greatest control over crystallisation parameters, and ease of handling, vapour diffusion should primarily be used [21]. From this section of the literature review, it is clear that a favourable method to implement is a vapour diffusion method due to the above reasons highlighted by Chayen and Saridakis (2008). Dialysis will likely find use as a means to fine-tune the conditions for crystallisation as part of further work when suitable conditions present themselves. Further work may also include an investigation into convection rates that are favourable for the negation of convection currents, which in light of the insight from literature, may be worth investigating for the sake of crystal quality. This knowledge provides a further viewpoint to assess in our work; especially if there are difficulties crystallising the protein, as there are thoughts that microgravity may permit the crystallisation of proteins that may not be possible at terrestrial levels [56]. Chayen and Saridakis (2008) also highlight that filtering the protein solution through a 0.1-micron filter bears the potential to increase the likelihood of attaining a large, single crystal rather than numerous small crystals recommending it as an optimisation strategy [21]. This is rightly noted and we will hence incorporate this into our methodology. 5.3.7. High-Throughput Screening 5.3.7.1. Background and Brief History An understanding of the structure and function of proteins is desired for their applications often accomplished with X-ray diffraction, the most popular method. As such, there is a need for high quality crystals. However, there exists a bottleneck, where finding conditions that provide diffraction quality crystals is limiting progress, subsequently viewed as the greatest barrier according the Chayen (1990)[1]. As noted earlier in McPherson (2004), given the wide range of variables that can be altered in addition to their concentrations, the task of undertaking the repetitive and laborious task of screening manually for thousands of combinations, is, to say the least, disheartening and impractical. In light of the former, several automatic methods have since been developed, and are reported to be directed towards vapour diffusion methods [1, 60-63] according to publications written by Cox & Weber (1988) [61], Kelders et al. (1987) [62], Ward et al. (1988) [63] to name a few. This liquid handling system with the use of a robot was reportedly first pioneered by Cox and Weber (1987) and subsequently marketed becoming the first commercially available protein crystallisation robot [60, 64]. A few years later, Chayen (1990) utilised the system in her investigation of microbatch crystallisation techniques [1]. Consequently, the Impax system was designed by Douglas Instruments and again utilised by Chayen for microbatch experiments [64]. The use of high through-put screening techniques have widely been documented in literature describing the various systems and approaches used, such as in Stevens (2000) [65], Brown et al. (2003) [66] and DeLucas et al. (2003) [67], amongst others. The advent of technological progress has allowed the design of robots that dispense nanolitre volumes with up to 1535 experiments per 100 μL of protein solution. There is even evidence that suggests that the crystals obtained with this technique might have the potential to diffract to superior resolutions, such as in the work of Bodenstaff et al (2002) [68] and Yeh (2003) [69]. Vapour diffusion techniques are popular given the major advantage of dynamic conditions as water evaporates from the drop altering the concentrations in the droplet and reservoir. Bodenstaff et al. (2002) state that higher levels of supersaturation can be attained with smaller volumes [68]. Additionally, one is able to adjust the conditions very accurately and define them with high precision - even in a small volume of sample. Chayen (1990) further states that the system can be used in two stages: to find out the solubility properties and limits of a given protein requiring crystallisation, and to discover suitable conditions that induce crystallisation of the protein [1].

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Figure 16: (a) shows the micro-tip dispensing the droplet into the paraffin oil; (b) shows the completed task and profile view of the well; the sample droplet has sunk to the bottom of the well after the micro-tip has been removed from the oil

5.3.7.2. Investigations in Literature Cox and Weber (1987) implemented high through put screening for sixteen crystallization experiments conducted in a 4 x 4 array. Two component buffers were used to maintain pH. Solution pH is varied in the columns, and precipitant concentration in the rows [60]. The authors then proceed to describe all the experimental procedures in great detail ranging from the calculation processes for the screens they formulated, the dispensing of the droplets, and the conditions that proved successful in generating large crystals suitable for diffraction studies. They also assert that crystal growth was regularly sensitive to the pH, and comparatively insensitive to the choice of buffer. The ultimate finding however, in light of the novelty of the technique circa 1987, was that they succeeded in reducing the time required to execute experiments [60]. A few years later, Chayen et al. (1990), documented the utilisation of an automated system for micro-batch protein crystallisation where a PC loaded with dedicated software allows for the rapid design of experiments. During the design, the experiments were displayed in a matrix format during design and execution, and have inputs where concentration, volume (μL), volume percentage, and stepper-motor steps can be edited. She uses a 6 x 4 matrix and follows the procedures of micro-batch, thereby using paraffin oil to dispense the drops. The multiple dispensers filled eight wells at once. The micro-tip moves into each well in turn in synchrony with the software, and dispensed 24 drops in 45 s easily. The experimental set up used by Chayen (1990) is displayed below in Figure 16 and Figure 17; taken from her paper [1].

Figure 17: Chayen’s (1990) Experimental set up for High-throughput Screening

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Figure 18 above highlights how detailed the screen can be and further shows why high-throughput screening is such a powerful tool for determining crystallisation conditions. Producing all the individual screening conditions manually would require a significant amount of man-hours and that still has not taken into account setting up the experiments themselves. As a result, her results were promising and grew crystals for lysozyme, two forms of glucose isomerase crystals, and a novel crystal form of carboxy-peptidase G2 [1]. Jancarik and Kim (1991) also investigated screening conditions for high throughput screening forming 50 unique screens in an attempt to crystallise 15 previously crystallised proteins. They subsequently reported great success in crystallising proteins that had not been crystallised prior to the paper. They tested a wide range of pHs and for each pH, chose buffers, precipitants and additives that had presented itself to be suitable in the past for protein crystallisation such as PEG, MPD (2-methyl-2,4-pentanediol) and various salting out agents in addition to combinations of the agents [70]. An extremely detailed table of the individual screens listing buffer, additives, pH, and concentrations are listed along with which proteins they utilised the respective screens. To aid in their analysis, they subsequently performed the experiment again at a temperature of 277K as opposed to room temperature. They further list their results in a table highlighting which screen worked for each of the proteins they used and the crystal dimensions. Approximately 15 years from its first inception, a paper that highlights the advances in high throughput screening is that by Bodenstaff et al. (2002). In their paper, they document an alternate configuration they devised themselves adapting a piezoelectric dispensing system that passes through the piezoelectric crystal configured to restrict flow. The pressure generated varies the amount of liquid that can be dispensed per pulse. The main technological advance from an economic perspective is that they were able to dispense reservoir volumes of 1 – 250 nL, and droplets of 200 – 500 pL in volume. The apparatus allowed the dispensing of the volumes to be carried out 16 at a time and subsequently dispensed 144 individual experiments in 5 minutes. They do state however, that there are limitations to using this set-up in the form of dependencies on the viscosity of the volume dispensed, which can reduce accuracy. They propose an alternate configuration analogous to how an ink-jet printer dispenses ink additionally to address this limitation. They also highlight that as the droplet volume limits the size of the crystal that can be obtained, overly small volumes may result in crystals so small that micro focus beamlines are required for X-ray analysis [68]. However, one must not forget the power of high throughput screening to find suitable conditions, and so we believe that over small volumes should not be a limitation. One can simply note the conditions, and replicate the experiment with a standard

Figure 18: a print out of the screens that she attempted. This highlights how detailed the screens can become and why the method is very useful for finding screening conditions which can easily be missed.

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24 or 96 well plate (hanging or sitting drop) to obtain larger crystals whilst testing reproducibility. Following the success of investigations such as those noted, it is clear that high throughput screening will likely play a role in finding suitable conditions for not only the range of proteins that haven’t been crystallised yet, but also in our project perhaps should the need be required. 5.3.7.3. Limitations One concern raised by Li (2006) in his paper, is that despite the benefits that are derived from using high throughput screening in protein engineering, he argues that the cost of capital is relatively high and out of reach for regular users and most biologists. He also argues that if microbatch is used as the crystallisation technique there can arise times when the crystallisation components can interfere with crystallisation by interacting with paraffin the oil [71]. Given the accuracy that can be provided from these robots in terms of the nano-litre volumes that are employed on current apparatus, it is clear that the components are especially delicate and intricate. It is also clear that there is likely to be a demand for professional maintenance, which is an additional cost and barrier. These issues are wholly not raised in papers documenting their use. Further, given that the principle technique for high throughput screening is vapour diffusion (Figure 19), there is subsequently the consideration of all the limitations of the technique. If the initial rate of mixing is too high, there may be the occurrence of reagent-shock. Consequently, the protein may precipitate before it can nucleate. Additionally, given the diversity of the screens, there are solutions with varying viscosities. A publication by Fluidigm suggests that this may generate a lack of precision when transferring these solutions of various viscosities. Finally, the dehydration of the drop at the nano-litre scale can prompt the formation of salt crystals [72]. A further issue that must be considered is linked to the number of screens that can ultimately be implemented. There are two sides to this argument. First and more relevantly, is a situation where the protein is not abundant in supply due to its rarity for example. This will certainly limit the effectiveness of high throughput screening, as the number of experiments carried out will also be limited. Further, statistical relevance dictates the repetition of an experiment three times. This further adds a limit on the effectiveness on the technique. One can argue that a smaller crystallisation droplet could be used but there must be a threshold minimum volume because of mechanical constraints. On the other hand, assuming that the protein one wished to crystallise is relatively abundant, given the vast amount of screening parameters that can be altered, there are vast amounts of combinations and permutations that can be exercised. For statistical relevance, repeating an experiment three times is standard. This creates a vast amount of data to analyse which can take a great deal of time; i.e. imaging hundreds of experiments per screen.

Figure 19: A representation of the sitting-drop vapour diffusion configuration commonly employed for high throughput screening experiments

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5.4. Influencing the Kinetics of Crystallisation A vast amount of literature documents the ways researchers attempt to induce nucleation, where there is often a premium placed on having thermodynamically favourable conditions for crystallisation. However, some authors, such as Chayen and Saridakis (2008) [21], and Luft et al. (1996) [47] among others, argue that there is a requirement of suitable kinetic parameters additionally for crystallisation. These kinetic parameters are more readily controlled by how supersaturation is attained, the kinetics of evaporation and mixing, the surface-to volume ratio for the crystallisation droplet, the volume of said droplet drop and the mass transfer effects in the drop [21]. Chayen (2008) states that by changing the crystallization method, one can manipulate the kinetics in an individual screen. There are other methods one could also utilise to do so such as growing crystals in various gelled media like in the work of Garcia-Ruiz (2002) [73]. Crystals could also be grown under microgravity for example the insulin crystallisation experiments carried out in space, and in work by Snell and Helliwell (2005) [74], applying a very powerful magnetic field due to charged surface of a protein [75] or controlling the evaporation rate and preferably reducing it. This can be done by applying a silicon (or oil) barrier in a vapour diffusion set-up [76] (which is the easiest way), or by increasing the distance between the drop and reservoir [47]. 5.5. Screening Matrices and Solutions 5.5.1. The Relevance of Screening The solution composition, properties, and its preparation, can either serve to aid, or hinder nucleation. Thus different pH, temperature, and solution composition have been the subject of research for numerous years. Chernov (2003) states that different morphologies can arise by changing these parameters, and subsequently can result in different crystalline structures [20]. But because of the vast combinations that can arise from changing any one of these factor, finding suitable let alone the best can be very time consuming and thus algorithms must often be formulated called sparse matrices. These are essentially a programme where one factor is changed whilst the others are held constant and the results analysed. This will help develop what Garcia-Ruiz (2003) calls, a better general understanding of the nucleation process, helping to reduce the variables currently assumed to induce nucleation and thus make the process easier and more economic, financially and time-wise [11]. The nucleation step controls the structure of the resulting crystal and the number of nuclei (and thus the crystal size) appearing in a crystallization system. This information is critical for extensive protein crystallization [11]. It will then allow scientists to grow crystals of a predefined size, which could be vastly useful for drug production for example, where the routes of drug administration can be affected by where it is to be administered. For protein crystallography, crystals of a certain size and quality are preferred and ways to influence crystal shape and number of nuclei are garnering increasing economic interest. McPherson (2004) [22] notes factors that can be altered in crystallisation screens. As can be seen from Figure 7 (the phase diagram), the aim is to drive the pathway through the metastable zone to the nucleation zone and back to the metastable zone. The solubility curve, whose location is fixed and thermodynamic in nature, has a nucleation probability of zero with an infinite induction time. The metastable limit, or supersolubility curve, is the upper limit of the metastable zone, is kinetic in nature, and has a 100% probability of nucleation. Thus, the induction time for nucleation can be considered instantaneous. Given sufficient time, any solution inside the metastable zone will spontaneously nucleate where the induction time is a function of the degree of supersaturation [11]. Given this knowledge, the main problem is finding conditions (or rather the combination of conditions) from the screening variables that will give a favourable environment for spontaneous nucleation, and thus near zero induction time.

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Even once the ‘optimum’ conditions are found, there is still the more challenging prospect of optimising these conditions in order to obtain higher quality crystals as stated by Saridakis (2009) [5]. pH can vary activity of the protein where activity and nucleation are inversely proportional. The addition of a precipitant (which can include volatile and non-volatile organic compounds, salts and polymers) can aid flocculation, or together with salt additives, allow the competition of the binding of water to the solvation layer and the anions [22]. Proteins also tend to be sensitive to temperature and are more soluble at lower temperatures. The macromolecular concentration will change the starting point and pathway across the phase diagram. Depending on the protein, whichever variable you decide to change, there will be varying effectiveness per variable, as well as combination effects. The extent of agents and concentrations provides a challenge and thus a time consuming element of it. There is thus the hope that by using a template of nanoporous glass (or any porous template), the process can be made more time efficient. 5.5.2. Crystallisation Parameters Literature further highlights the rigours of screening conditions. McPherson (1999) for example, gives an example in his review of protein crystallisation. He takes the example of 48-well screen. If one were searching for a useful detergent, you would need to multiply the number of detergent by 48; the scale of the search becomes significant given that there are numerous potentially useful detergents. Using an example of three different 24 sample detergent kits, using the 48-well screen for each detergent, would mean 3456 trials must be performed. With automated systems, and sizeable amounts of material, this may be possible, but is impractical for most labs if done manually. It further appears that some detergents work best when small amphiphilic molecules such as LDAO are added, adding another dimension to consider [22]. In their report on screening and optimization strategies for macromolecular crystal growth, Cudney, Patel, Weisgraber, Newhouse and McPherson (1993) [77] highlight the highly empirical nature in determining successful crystallization conditions for any particular macromolecule. They implement the sparse-matrix and grid screening procedures, as they are the swiftest and most economical method to determine preliminary crystallization conditions and additionally optimised the initial conditions found for the growth of diffraction quality crystals for X-ray analysis. Their group tests a screening protocol, which employed less conventional precipitating agents further testing, the effects of 24 electrostatic crosslinking agents due to their ability to promote crystallization, and the effectiveness of 30 detergents given their abilities to prevent aggregation and influence crystal growth. Of the 20 macromolecules screened with the protocol, 14 produced crystals. In most cases, crystals were produced under several conditions included in the screen. Additionally, they experimented with electrostatic crosslinking agents, as did Chen (1993) [78]. Their rationale is that the exterior surfaces of macromolecules expose an array of unique functional groups and these form favourable interactions with other macromolecules as they condense under conditions of supersaturation [77]. Their results primarily highlight that crystallisation occurs under very specific conditions given they started with 250 individual screens, and based on the success of crystallising proteins, they reduced the number to 24 screens; under 10% of the screens they started with again, highlighting the effort that must be given to find useful conditions. Additionally, an investigation into the interactions between ions and macromolecules by Zhang and Cremer (2006), prompted them to study the Hofmeister Series shown below. Depending on the solubility of the ions, they will interact and affect nucleation in different ways. The ions are listed in a series known as the Hofmeister Series. The series categorises ions on their capacity to salt in or salt out proteins – more commonly listed as the latter – or rather the ions relative influence on the behaviour of proteins. The series was first proposed by Franz Hofmeister in 1888, and shown in Figure 20 [79]. Anions are further believed to

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have a greater effect than cations. Amongst the ways in which the ions can influence the behaviour of proteins is by affecting their stability in solution, their surface tension, and very importantly their solubility [79]. In industry, compounds such as ammonium sulphate are widely used as a precipitant as a separation technique to salt out proteins causing them to aggregate.

Zhang et al. (2006) studied the effects of 11 sodium salts on a specific polymer that modelled the protein to ascertain the anions effects on the lower critical solution temperature. Ways in which the ions influence the proteins was found to be the polarising effect they had on hydrogen-bonded water in the solvation layer on the proteins. They were also found to increase the surface tension of the polymer/ water interface lowering the lower critical solution temperature. Both these effects facilitated in the salting out of the polymer from solution [79]. Zhang et al. state that the achievement of their work is only an initial step in understanding the effects of solution conditions. They subsequently feel that a full study on the effects of cations and osmolytes on proteins must be undertaken additionally to fully understand their effects on proteins. They also state that the Hofmeister series should be analysed in terms of the effects the ions have on the proteins themselves, as changes in bulk water structure brought about by the salts do not explain the specific effects [79]. It is essentially believed that the salts acts by attracting water molecules from solution and (more importantly) from the protein solvation layer. This does two things: (a) it reduces the amount of water molecules that can bond with water precipitating it out of solution, and (b) they reduce the “shielding” the water molecules provide to secondary Van der Waals forces that then also facilitate the induction of supersaturation. It further provides potential for electrostatic interactions given the charged nature of the proteins. It is clear that the salt chosen in the screens is likely to be of high importance and even more when determining possible reasons nucleation may not be occurring. pH is another factor in screening that can influence nucleation. The pH can affect the mobility of the active site of the proteins influencing the activity. Savinse® for example has maximum activity at a pH of approximately 10.5, and so employing a pH close to this value

Figure 20: the Hofmeister Series showing the effects anions have on proteins; the green arrow indicates favourable effects and the opposite for the red arrow

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will reduce the proteins thermodynamic stability making nucleation more difficult. pH can further influence the surface charge of an enzyme as highlighted by Figure 36 [80] on page 43. Cox and Weber (1987) [60] note that solutions were sensitive to pH in their report on automated screening, and McPherson (1999) comments that screening with pH can be difficult given that a difference of less than 0.5 can be the difference between a large, single crystal, precipitates and micro-crystals [4]. pH can also directly affect the zeta-potential; a property of proteins that is attracting interest given that a protein solution can be treated as a colloidal dispersion. The choice of precipitant does not only extend to salts. They can extend to volatile organic solvents such as, ethanol and propanol and dioxane. Non-volatile solvents include compounds such as 2-methyl-2,4,-pentanediol. Polymers such as Jeffamine T, polyamine, and the most popular, polyethylene glycol in various molecular weights are used. Yamanaka (2011) [81] attempt to optimise the salt concentration range and pH for a 30% PEG 4000. They find that the greater the difference between the pH and pI (isoelectric point), the greater the salt concentration required for crystal growth and state that a well optimised salt concentration can be the determining factor success in trials. They also highlight an equation for calculating charge density of a target protein, and prove the linear dependence of the crystallisation solutions ionic strength, and the charge density of a protein [81]. According to McPherson (2004) in his review of protein crystallisation, there are an additional eight factors that can induce supersaturation. They include the following: mixing at the final concentrations as in batch methods, altering the temperature, adding ligands which adjust the protein solubility, adding cross bridging agents such as disulphide bonds, increasing the protein concentration, a means to remove water, and the removal of a solubilising agent [22]. 5.6. Induction of Nucleation The nature of primary nucleation can be divided into homogeneous and heterogeneous nucleation. Homogeneous nucleation is a random event that caused by the clustering of a sufficient amount of molecules locally and simultaneously forming a critical nucleus. Nucleation occurs purely derived from supersaturation only. Heterogeneous nucleation on the other hand, is facilitated by additional particles or surfaces on which the critical nucleus forms. The surface typically does this by taking advantage of charge differences and attracting the molecules electrostatically (for example in protein crystallisation), hydrophobically, induce other forms of interaction, or restrict their movement in some fashion. Epitaxy can even be induced by some heterogeneous nucleants promoting crystalline order [37]. Due to the rarity of homogeneous nucleation as opposed to heterogeneous nucleation at the required supersaturation levels, a common belief is that most protein crystals that were thought to have been grown homogeneously may have actually nucleated heterogeneously. It is intrinsically difficult to have a purely homogeneous phase given the existence of foreign surfaces, the exposure to microscopic impurities and insoluble material as examples as suggested by Nanev (2007b) [37, 82]. 5.7. Heterogeneous Nucleation Investigations 5.7.1. Rationale for Incorporation of Heterogeneous Nucleants Given the energetic advantages to using heterogeneous nucleation, there have been further investigations into the use of heterogeneous nucleants to induce nucleation of the target protein, and improve crystal quality. It can be understood that are benefits to selectively and deliberately control aspects such as nuclei numbers and the supersaturation point and so far, the preferred method has been to deliberately induce it at metastable conditions [5]. Further rationale is the prospect of inducing nucleation in more diverse crystallising conditions, particularly those that may have been deemed unsuitable for nucleation in the

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past. Because the conditions for spontaneous nucleation are narrow, there is sufficient scope to inadvertently miss conditions that may have been suitable for crystallisation, and is part of the reason why finding suitable conditions is difficult. As such the addition of a heterogeneous nucleant may aid in the finding of conditions that may have led to metastability and possibly find new ones [5, 83, 84]. 5.7.2. Porous Silicon In light of this information, literature suggests that Chayen et al. (2001) [85] was amongst the first to prove successful in the use of heterogeneous nucleants by using porous silicon. For their work, they electrochemically fabricated a 15 mm thick layer of porous silicon took on a silicon substrate. The average pore size was 5-10 nm, and a Gaussian distribution was exhibited when the dimensions of the pores were analysed with 3 nm standard deviation; i.e. a wide PSD [85]. A current density of 30 mA cm-2 was utilised by Chayen et al. to produce 15 mm thick layers with a porosity of 65%. Hydrofluoric acid (48% v/v) was used to etch the porous structure into the silicon substrate [85]. Her group chose this method as an alternate means to the use of seeding, charged surfaces, mechanical means, and epitaxy (growing a crystal of a certain orientation on top of another crystal with orientation determined by the underlying crystal). She argues that any environment that creates a higher local concentration of macromolecules bears potential to induce nucleation at that point with subsequent free energy reductions. Unsuccessful attempts to crystallise with rough surfaces like in poly-L-lysine and plastic turned her attention to porous silicon which consists of a network of pores and cavities [85]. An important point to note is that in these applications, the pore size is of similar size to that of the protein of whose Stokes radius is estimated to be in the range of 2-5 nm [5]. As such, the pores were designed to be of 5-10 nm in diameter with a standard deviation of 3 nm. This material had a wide pore distribution and highlights the fact that research at this point was seemingly based on the materials which would have a catalogue of pore sizes; one of which would induce nucleation.

Figure 21: This image is taken from Chayen (2001) and portrays the cross-section of the porous silicon she manufactured highlighting the “tree-like” structure of the material. The silicon appears white in the image whilst the pores appear as dark regions. .

Figure 22: This figure shows some of the results from the use of porous-silicon coated wafers as a nucleant. The first image shows lysozyme, the other, trypsin. An important feature is the growth of crystals on or in the proximity of the silicon fragments.

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Figure 23: This shows a schematic representation of protein molecules approaching and entering pores of a nucleant. Due to the wide pore distribution concerning shape and size, it is thought that some entrap the molecules as they enter the pores. Taken from Bolanos-Garcia (2009).

Other porous material were reported to have been tested by her group such as (alumina) silicates but were found to not influence nucleation significantly. When comparing the porous silicon with microfluidic silicon devices to investigate electrostatically driven heterogeneous nucleation of a protein, lysozyme, they found that the nucleation was dependent on the pH of the crystallization solution and the surface charge of the protein molecules. Such was not the case with the porous silicon they manufactured. This led them to believe that the pore induced mechanical constraint of the molecules, and consequently the creation of a localised supersaturation maximum is the primary means which aids crystallisation [85]. The paper reports that the porous silicon was successful at inducing nucleation at metastable conditions where large diffraction quality crystals were grown. It further reports that the crystals grew on the silicon with the concentration of crystals decreasing with distance from the silicon sample. According to Chayen and her groups work, the implications are significant as adding 0.06 mm2 silicon fragments to crystallization trials, proteins thought as difficult to crystallise, yielded crystals, enabling crystallisation at metastable conditions in 4 out of the 5 she tested where two of the results can be viewed in Figure 22 for Lysozyme and Trypsin. [86]. This further demonstrates the significance and effectiveness of using heterogeneous nucleants. Figure 23 below highlights a representation in Bolanos-Garcia (2009) highlighting macromolecules entering pores in a nucleant [37]. 5.7.3. Mineral Surfaces Porous Silicon however is not the only material with which success in some stage of the crystallisation process has been achieved. Mineral surfaces have additionally been utilised. Garcia-Ruiz (2003) states that the idea of inducing nucleation by the presence of different mineral surfaces was originally formulated by McPherson (1999) [11]. As such, heterogeneous nucleation has been studied for numerous glass substrates and hydrophobic surfaces with an example being the nucleation of Hen-egg-white lysozyme (HEWL) on templates of poly-L-lysine, and surfaces made hydrophobic with hexamethyl-disilazane by Nanev and Tsekova (2000) [87]. They attempted to determine the number of molecules in a HEWL nucleus subsequently compared the results with bare glass [87]. The presence of results indicates that they were successful in inducing nucleation. As an additional side-note, they also subsequently mention that when applying heterogeneous nucleation to grow diffraction quality crystals, care must be taken as there is potential to damage the crystal when detaching it from the substrate [87]. Seen as one of the aims to investigate the crystallisation potential of the relevant proteins (Savinase® 16.0L and Termamyl® 120L) with the pinnacle being diffraction quality crystals, this highlights an area of thought as to how the templates will be employed to the crystallisation droplet. Should we deploy the nucleant as a “chip” as Chayen et al. (2001) did in their paper on nucleation with

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porous silicon? It may be more practical to utilise a finer nucleant i.e. broken into smaller pieces. Will the crystals be detachable if attached to coated cover slips? 5.7.4. Heterogeneous Nucleation via Membranes and Membrane Crystallisation In the years commencing 2003, very interesting work with the use of membranes such as polypropylene or polyvinylidene porous hydrophobic membranes was noted in literature. Here we highlight in the work of Curcio et al. (2003) [88], Di Profio et al. (2003) [89], and Zhang et al. (2008) [90]. Membrane crystallisation is stated to be a relatively new technique developed within the past few yew years [90]. The method may have applications in future is the use of membranes. Curcio et al. (2003) investigated the use of microporous hydrophobic membranes to crystallise HEWL where the polymeric surfaces also acted as heterogeneous nucleants [88]. Di Profio et al. (2003) investigated the use of hydrophobic microporous polypropylene membranes supplied as hollow fibres, to crystallise HEWL, and used turbidity measurements to analyse the induction time and growth rates of the crystals. Amongst their findings, the most significant is the reduction in the induction time compared to other methods to between 1.2 – 10 hours, and the high growth rates with low supersaturation ratios [89]. Zhang et al. (2008) also further explored the use of membrane crystallisation to crystallise lysozyme using poly vinylidene fluoride (PVDF) hollow fibre membranes and investigated the effects of crystallisation parameters such as pH and precipitant concentration, and flow velocity of the stripping solution. They conclude that the membrane surface promoted nucleation, the induction time was significantly lowered, and could crystallise lower protein concentrations from 40 mg/mL to 20 mg/mL [90]. Further, Curcio (2003) reported that protein crystals were able to detach from the membrane surface providing the surface for further nucleation again [88]. This research further portrays the potential of heterogeneous nucleants to reduce induction times reduce the amount of target protein required for crystallisation. 5.7.5. Heterogeneous Nucleants Derived from Nature In the journey to find a universal nucleant, the nature-derived phenomena of nucleation prompted researchers to investigate the use of natural nucleants. There is a range of natural nucleants that can be used as they provide a naturally compatible with proteins and easy to obtain. Researchers such as Dekker et al. (2004) and Thakur et al. (2007) successfully employed cellulose, hydroxyapatite powders, horsehair, and dried seaweed as heterogeneous nucleants in addition to five others, which included substances such as sand. Their group utilised a high throughput screening method and reportedly witnessed positive effects, which they suggest from the number of crystals in the crystallisation droplet. From their results, it appears that dried seaweed and horsehair gave the highest number of crystals save for a combination of all nine nucleants [84]. The work by Thakur et al. (2007) however, does not refer to the effects on induction times and based on the images provided, the number of crystals may not have been the best method to gauge effectiveness despite the differences between with and without nucleant. 5.7.6. Computational Modelling of Heterogeneous Nucleation in Pores Page and Sear (2006) [91] in an investigation into optimum pore sizes suggested by Chayen et al. (2006), give a report on their study of nucleation in pores utilising computational modelling to simulate nucleation in pores. They investigate the benefits of using a heterogeneous nucleant and the mechanism behind nucleation with heterogeneous nucleation using the two-dimensional Ising model developed by Allen et al. (2005). Their investigation included finding out why protein crystals nucleate on the surface of the porous medium. They also state that according to work of researchers such as Chayen, surfaces that were not porous were found to be less effective at promoting nucleation [86]. They further suggest that this is evidence that the porous geometry is accelerating nucleation in some fashion. Based on further work, they also report that researchers have found that the porous structure is more effective when it was disordered and the pores had a size distribution. Materials such zeolites with uniform pore sizes reportedly did not induce

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nucleation [86, 91]. There most significant findings were that nucleation was orders of magnitude larger in pores than on planar surfaces, and that the rate was proportional to the pore size where there is a trade-off between nucleation within pores and rate of crystal growth. This directly links to our work. By investigating the use of four different sizes of template, we hope to assess what the optimal pore size to induce the nucleation of our target proteins is. 5.7.7. Surface Structure and the Role of Surface Chemistry Bolanos-Garcia (2009) [37] stated that for a disordered porous material, the wider the range of pore shapes and sizes available at the surface the more likely a given macromolecule will find an adequate pore size and shape to nucleate [37, 86]. As such, there has been recent interest in the function of the nanostructure of the nucleants, surface contours, and patterning, as the consensus is that they are of significance in the overall effectiveness of crystal nucleation and formation [91-93]. One of significance is the use of hair as a nucleant continuing the search within nature to find a universal nucleant. Hair has historically found use for years in macromolecular crystallization, transferring crystal seeds into metastable solutions, and not as a nucleant where the sharp microstructure of hair, particularly horse-hair derived from its overlapping cuticles, is ideal for trapping the microfragments of a crystal [94]. D’Arcy et al. (2003) further states in his report on the use of horse hair, that hair was used for streak seeding by Leung et al. (1989), and Stura and Wilson (1991). In their study, they prepared horsehair in different ways and administered the nucleant to the droplets. They reportedly noticed pronounced effects on nucleation and crystal growth for the proteins they tested with up to 125 seeds produced with glucose isomerase compared to only one without hair, for example. They also found that the crystals that grew on the hair could be transferred to a droplet at the beginning of a crystallisation without the seeds dissolving. However, a limitation of their report is that the test the nucleant as a means to generate seeds, or rather the ability to influence nucleation, and do not refer to the induction times. They suggest the investigation into the effects of different animal hairs as nucleants [95]. Human hair has also been effective in inducing crystallisation according to the work of Georgieva et al. (2007) [96]. Their study encompassed the crystallisation of three model proteins and of one protein, potato serine protease inhibitor, which is reportedly notoriously difficult to crystallise and for which no crystal structure was yet available [96]. A picture of the potato serine-protease inhibitor crystals growing on human hair is shown in Figure 24 below [96]. Further tests with confocal microscopy and atomic-force microscopy subsequently showed that protein molecules accrue on surface irregularities and the cuticle highlighting that a relationship exists between the keratin molecules and the cuticle structure, which was responsible for inducing nucleation. Experiments were undertaken to find the reasons hair is effective, and found that in particular the keratin molecules provide attractive protein–protein interactions, as denaturation of the keratin affected the nucleation properties. To distinguish between the role of the keratin and the role of the cuticle structure, a polymer replica of a hair fibre was made which preserved the shape of the cuticles but it did not induce nucleation, indicating that the keratin molecules have a crucial role in nucleation induction [5].

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This work indicates how important the surface chemistry of a nucleant as well as the surface structure plays in inducing nucleation, and is thus a factor that must be considered when assessing their effectiveness of our nucleant overall. The search for a universal nucleant however was not over. Just as McPherson (1999) stated that the gaining of a crystal should not signal the end of the hunt for better conditions in conventional screening, the search for a universal nucleant has not ended despite the effectiveness of some candidates. Tang et al. (2005) and Tosi et al. (2008) and investigated crystallisation with functionalised mica sheets and mica sheets silanised by 3-aminopropyl triethoxysilane (APTES) respectively. Tang and his group investigated their use with lysozyme and trichosantin and found better diffraction quality crystals [97]. In model proteins, Tosi et al. found that the surfaces often reduced nucleation time, and reduced the protein concentration and nucleation time unlike the surface of coverslips in vapour diffusion techniques [98]. Additionally, Sugahara et al., (2008) used the synthetic aluminosilicate crystalline polymer microporous zeolite as a catalyst and candidate for a universal hetero-epitaxic nucleant. This was implemented with regular micropores that reportedly promoted crystal nucleation that was form-selective. In his work, the pore size that yielded the best results was a pore size of 5Å [99]. It bound to Ca2+ ions which may be useful as Ca2+ are present in the backbone of Savinase® 16.0L which may help to possibly stabilise the molecule. The crystal quality was reported improved in five out of six proteins investigated and interestingly formed better resolution crystals in new forms. 5.7.8. Outlook for Heterogeneous Nucleation As of 2009, an amorphous mesoporous bioactive bio-glass, CaO-P2O5-SiO2, is reportedly the best material as a heterogeneous nucleant [37]. The material has a pore-size distribution in between 2-10 nm in diameter with highly varied pore contours [5, 86]. By introducing 100 mm grains of the bio-glass to the trial, Chayen et al. (2006) found that nucleation is promoted without irrespective of the conditions, molecular weight, pH, crystallising agent composition or set up [86] and has reportedly assisted to crystallisation of 14 proteins. The diffraction quality of the crystals is also reported to be far better than compared with standard techniques. However, according to Saridakis (2009), true universality cannot be granted unless a greater range of proteins are crystallised. That being said, the nucleant has proved vastly effective in crystallising numerous proteins unlike other nucleant, which are useful for a narrow set of nucleants and conditions.

Figure 24: This is an image that shows crystals grown on human hair. The crystals are those of potato serine-protease inhibitor and the scale bar represents a distance of 100 μm.

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5.7.9. Limitations of Literature Concerning Heterogeneous Nucleation Many papers that report work with heterogeneous nucleants however only report the effectiveness of the nucleant to induce nucleation – preferably in “difficult-to-crystallise” proteins, or proteins that have not currently been crystallised. Though they document successful results such as larger, higher diffraction quality crystals, or the proteins successful crystallisation if it has not been crystallised, there are few mentions of the effect on induction times. The work of two groups who attempted to investigate induction times are reviewed next. Rong et al. (2004) addresses the effect of heterogeneous nucleants in reducing induction times by using a commercially available porous glass substrate (Corning Porous Glass No.7930) to crystallise hen egg-white lysozyme (HEWL), apoferritin, and thaumatin. Amongst the results they report, one shows that the porous glass substrate promoted nucleation at lower levels of supersaturation. For industrial applications, this is very beneficial as this means lower concentrations of protein can be used to induce nucleation. Another finding, more significant to our aims was that the porous glass substrate reduced the induction time for nucleation and they reportedly obtained larger crystals with the porous glass than those obtained with non-porous glass substrates [93]. One shortcoming however is that it is not mentioned how much the induction time was reduced by. Takehara et al., (2008) experimented with semisynthetic micromica (semisynthetic and non-swollen layer silicate) which has a rough, irregular surface rather than pores. In the ten proteins he experimented with, 8 reportedly had a reduced induction time [83]. For example, Threonine Synthase had its induction time reduced from 72 hours to less than 24 hours when micromica was added. Though they successfully reduced induction times and improved the crystal diffraction quality with micromica, one problem they observed was the nucleation of crystals too small to recover and suggest be found to recover the crystals, or grow larger ones. They also found that the addition of the micromica allowed crystals to form without the need for precipitants such as high concentrations of salts suggest that in this way nucleants can remove the arduous task of screening meticulously. They also find the nucleant allowed even low concentrations of protein to be crystallised and state that the structural determination of proteins that are low in abundance may become possible as a result [83]. This work thus far has also underlined the significance heterogeneous nucleants carry in protein crystallisation. Chayen (2001) further suggests three reasons why the discovery of such agents is of significant importance. Primarily, they represent the steps taken to find a universal nucleant that would be able to facilitate nucleation of numerous proteins reducing cost and time in protein engineering and industry. Secondly, the benefit they can bring in the field of structural genomics is immense given that they have the potential to maximize the chances of obtaining diffractive quality crystals during initial screening of crystallization conditions. Finally, large diffraction quality crystals can be grown at metastable conditions;

Figure 25: this highlights a scanning electro-micrograph (SEM) of the surface texture of porous bio-glass revealing the highly porous nature of this material.

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conditions where slow growth and secondary nucleation facilitate this [100, 101]. This section of the literature review has highlighted the effects various nucleants induce be they synthetic or natural, they importance of a disordered surface structure 5.8. Nucleation In and Out of Pores – Theoretical and Practical Perspectives Although the consensus is that pores might be able to facilitate nucleation and crystal growth by restraining the protein molecules given they have right dimensions, a detailed description of the mechanism is missing. In an attempt to do so, Page and Sear (2006) [91] investigated the nucleation of macromolecules in a pore using computer models based on the two-dimensional Ising model, developed by Allen et al. (2005), and described and utilised by Sear (2006b) [102]. Their work is derived from the theory that there is an optimum pore size suggested by Chayen, Saridakis, and Sear (2006) [86] in their report discussing how the combination of theory and experiment can lead to a more efficient protocol to discover a heterogeneous nucleant. Statistical and mathematical analysis was used to determine the average rate as a function of pore size graphically, and subsequently tested their finding with mesoporous bio-active gel glass. They ultimately predict, based on graphical analysis, that for wide pore size distributions (PSD), the rate of nucleation will be rapid for proteins of a wide range of sizes. For a narrow PSD, they predict that the nucleant will only be effective for proteins of a specific size [86]. This is very relevant to our project given our aims to uses porous templates to reduce induction times. Their primary aim was to investigate nucleation in solutions that have a sample of porous material present and increase their understanding of the phenomena. They note that the energy barrier associated with the formation of the crystal and hence the rate of crystallization depends on the surface characteristics. The rate in particular, was reported to be very sensitive to the surface geometry [91].

They suggest, based on the simulations, that nucleation takes place initially in the corners of the pores. They also discovered that crystals appeared to be ‘stuck’ to the porous media suggesting that nucleation took place on the porous surface. Of the conclusions they made, the most significant is that the nucleation rate is orders of magnitude higher in the pores than on a flat surface if the pore density is one pore per million surface lattice sites [91]. They also found that for pores of a certain size, that nucleation occurred in two steps where the pore filled first, and then growth continued outside the pore once the pore filled. This is highlighted in Figure 26 above [91]. The figure highlights computational representations of pores presented by Page and Sear (2006) of

Figure 26: a depiction of the computer models Page and Sear (2006) used. Length was measured in “sites” and each image is 60 x 60 sites in size. The depth of the pores is 30 sites. The red represents the growing nucleus. The pores in (a), (b), (c) and (d) have a pore diameter of 13, 24, 9, and 9 respectively. One can see how a small pore diameter fills quicker than a wide pore. One can also see how the nucleus continues to grow even once the pore has filled termed the ‘breakout’. Also, notice how the corner of the pore is where growth starts. The red particles represent protein molecules.

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pore width 13, 24, 9 and 9 sites wide and show how the nucleus grows within different size pores; some taking longer to fill if the pore width is larger, and others filling quickly due to small pore widths. A further conclusion that Page and Sear made was that the optimal size of the pore should be approximately the same size as the critical nucleus to maximize the nucleation rate of a protein crystal. They recommend that in the design of a porous substrate, pores should ideally not be much smaller than the critical nucleus size for the crystal, as there will be a resulting low level of nucleation out of the pore. Nor should the pore size be much larger than the critical nucleus, as initial pore filling will be very slow too as a result [91]. Page and Sear (2006) [91] also explain that the surface geometry of the porous templates allows them to be so effective and behave as nucleating agents. In accordance with the Classical Nucleation Theory [103], let us consider two identical nuclei of the same radius. If one is taken and can ‘wet’ a perfectly flat surface so that the contact angle (θ) is 90°, the nucleus, now a hemisphere, is half the size of the nuclei in the bulk (homogeneous) meaning half the energy is required. Please refer to visual aid: Figure 27. Therefore,

⁄ where depicts the height of the free-energy barrier

to nucleation. Likewise, a quarter-spherical nucleus forming in a corner between two perpendicular flat surfaces,

⁄ [91, 104]. This work by Sear

(2006) highlights that nucleation is energetically favourable in the corners of pores and the nucleus subsequently fills the pore before growing out of it as in Figure 26. A homologous “seed surface” continues the crystal growth mechanism into the bulk phase when the crystal fills the pore [5]. The larger this surface is, the higher the probability the crystal will continue growing. The smaller in diameter the pore, the quicker the pore fills and the larger the pore, the more effective crystal growth outside the pore is. Consequently, for wide pores, nucleation is the slowest step and for narrow pores, the pore filling step is rate limiting [7, 91]. Therefore, given this trade of, it is clear that there is an optimal pore size, which will depend on the protein, as the pore must be larger than the molecular diameter. As no pore is identical, there is a vast array of sizes for a protein to find an optimal size. Experiments by Henschel et al. (2008) [105] on primary alcohols using porous silicon further suggested that the pores additionally align the enzyme molecules. In his paper, Seeds of Change, Frenkel (2006) also reviews the usefulness of seeds in unison with nucleants to highlight the usefulness of heterogeneous nucleants, templates that can kick-start crystallization [7]. He discusses the work of Chayen et al. (2001) [85] and highlights the unexpected finding of the effectiveness on nucleation initiation on highly disordered, porous particles. Based on this knowledge, he notes the surprise of finding that seeds of microporous silicon are effective in crystallising a variety of proteins [85]. He lists the qualities of the seed material being almost opposite to the qualities of what one would categorise as a good crystallization template; being sponge-like, full of holes and crevices, and with a highly disordered surface [7]. According to computer simulations on colloidal crystallisation, the curvature of a surface should make nucleation more difficult [106] making the concept of

Figure 27: A nucleus in homogeneous nucleation; a nucleus on a perfectly flat surface

(contact angle = 90°); a nucleus in a corner

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crystallization on such a rough, porous surface highly unperceivable. This is due to suggested deformity arising from the formation on a curved surface and thus should reduce the stability of the crystals attached compared to a flat surface with the probability of the crystal accurately following the curvature of the substrate highly unlikely; even if it is stress free. Finally, Page and Sear additionally suggest that the reason for the unexpected crystallization of proteins on a porous surface is that there will always be pores amongst the multitude of pores, which have the necessary shape for a macromolecule to attach and grow into a small crystal. 5.9. Pore Diameter There is now an establishment that proteins will require pores of a particular size to optimally grow in pores. One way to determine the size is to use photon correlation spectroscopy also known as quasi elastic light scattering (Quels), and dynamic light scattering (DLS). This is a method commonly used in colloid science where particles are suspended in solution and a scientist may seek to analyse the suspension by determining the size distribution. It is also applied to polymer analysis where a polymer scientist may again wish to determine the size distribution of the particles in solution and from this find a measure more widely known as the polydispersity and/ or the polydispersity index. The set-up of PCS experiments is similar to that shown in Figure 28 where a difference can be the scattering angle used. This method is used for measuring the Stokes radius. A sample is illuminated using a laser that undergoes scattering by dissolved macromolecules as it passes through. The Brownian motion that arises from the thermal agitation (thermodynamic differences) of the suspended molecules creates fluctuations in the intensity of the scattered light. This further causes constructive and destructive interference from which either a spectrum can be observed highlighting the intensity of the light for different sizes, or a bell distribution curve highlighting the mean particle radius. An interpretation of the results can lead to the size of the molecules being known taking into consideration the effect of the solvent and the shape of the molecule. Based on the work of Streimer et al. (2007) with ultrathin porous nano-crystalline silicon (pnc-Si) membranes [107], the size of proteins can be expected to be with the range of 5-25 nm given the membrane diameter. Fitter et al. (2004) implemented dynamic light scattering in their comparative investigation of two α-amylases (from Bacillus Amyloliquefaciens, and Bacillus Licheniformis). They sought to measure their Stokes radius to study their folding mechanisms as one of their objectives. Fitter (2004) used an Ar+ laser with a 488 nm wavelength and a scattering angle of 40°. He obtained a result of 4.0 ± 0.3 nm for folded α-amylase from Bacillus Licheniformis, and 5.2 nm ± 0.4 nm for the fully unfolded enzyme (brought about under 6 M GndHCl [guanidine hydrochloride] and with calcium depletion) [24]. However, an important fact is that the experimental set-up was different to the standard experimental set-up, such as that shown in Figure 28. The difference in scattering angle alone will influence the results greatly as the scattering intensity will not be comparable if the scattering angles are not where the size is proportional to the squared sine of the half angle [108] as shown in the equations below. K is the scattering vector, D is the diffusional constant, kB is the Boltzmann constant, T is the temperature, η is the viscosity, and rH is the Stokes radius.

Equation 5

Where (

)

Equation 6

Due to the applications of light scattering to determine characteristics of molecules suspended in solution and of emulsions, the technique can also be extended to analyse

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proteins in solution. As such, dynamic Light Scattering (DLS) is a technique that has over time, established itself as a useful means to screen the crystallisation ability of proteins quickly. The rationale is that, by analysing the particle size distribution of the molecules, one can ascertain the purity of the molecules, i.e. that there is no foreign material in the solution that may act to hinder nucleation, and that there are no protein aggregates in solution that may interfere with the nucleation process [109]. Further emphasis of the ease of the procedure is highlighted in the requirement of only the refractive index of the solvent, and the solvent viscosity. A key point missing is the way the data is used. Page and Sear (2006) have already stressed as a conclusion the importance of pore size for nucleation. They say the optimal size of the pore should be approximately the same size as the critical nucleus to maximize the nucleation rate of a protein crystal. Whereas Chayen (2001) however, designed the pores of her HF etched porous silicon substrate to have an average pore diameter 5-10 nm with a standard deviation of 3 nm. This was based on the Stokes radii of the proteins they used estimating them to be in the range of 2-5 nm [5]. As such, we believe this to be the reason why we use pore sizes that are multiples of the Stokes radii. The application of DLS to determine the size of the protein could be monumental, as it will ultimately allow for the design of a porous substrate that will optimally catalyse the process sufficiently to attain crystals with a short induction time. Dynamic light scattering does however have limitations. For example, the concentration ratio of the two or more species of vastly different sizes, can affect the amount of light scattered by the respective particles. If a particle is ten times larger than average, the analysis of the author suggests that these larger particle scatter approximately a million times more light. It is thus clear that a small number of large particles can wholly envelop the light that has been scattered by smaller particles. For this reason, DLS samples are often filtered to remove interfering dust particles. Once large particles are remove, particle resolution can be as low of 1 nm. The limit of detection for the DLS technique is attained when the concentration of the particles in solution is insufficient. Additionally, if the motion of the solvent particles and Brownian motion of the particles in the sample are comparable, another limit is reached [109]. 6. Aims and Objectives Our aims are to reduce the induction time primarily, initially by screening conditions, then by incorporating the templates. We will then aim to increase the diffraction quality of the crystal in a similar manner, additionally recording any significant changes in the yield. Firstly, we seek to analyse the effectiveness of the nano-engineered templates to reduce the induction time. Secondly, we seek to grow crystals of at least 30-microns in size with minimal defects and sharp phase boundaries, with the target being diffraction quality crystals. Thirdly, we wish to reduce the amount of target protein required to induce nucleation. Finally, we also seek to investigate the effects the nano-templates have on the morphology of the crystals, attempting to observe increased sharpness in the phase boundaries, or complete transformations, should that occur. From a product perspective, we will also note the effects of the screening matrices, and the templates on the crystal yield. 7. Methodology and Apparatus 7.1. The Stokes Radius The ‘Dictionary of Nanotechnology’ defines the Stokes Radius as the effective diameter of a particle in a liquid phase [110]. This will ultimately be a means of characterising of the proteins via Dynamic Light Scattering (DLS). This uses scattered light to measure the rate of diffusion of protein particles in order to create a distribution curve and from this determine

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Figure 29: A computational depiction of a lysozyme molecule highlighting, the geometric dimensions, the hard sphere diameter in red, the Stokes Radius in green, and further, an ellipsoid with identical diffusional properties in black.

the Stokes Radius. The Stokes-Einstein relationship is used for this where η is the diluent viscosity, μ, in poise, d is the equivalent spherical diameter, is the Boltzmann constant [111] shown in Equation 7. It is of particular importance to us, as the nano-templates we will be using will have a prescribed pore size tuned in multiples of these measurements. The minimum size will be that of the Stokes Radius. An assumption inherent in the model is that the molecule is that of a hard sphere. Figure 29 [112] shows a computational depiction of a lysozyme molecule highlighting, the geometric dimensions, the hard sphere diameter in red, the Stokes Radius in green, and further, an ellipsoid with identical diffusional properties in black. Using the Stokes-Einstein equation, Equation 7, the radius can be calculated from the diffusional properties of the molecule. The equation is shown below, where D is the diffusional constant, kB is the Boltzmann constant, T is the temperature, η is the viscosity, and rH is the Stokes radius.

Equation 7

7.2. Characterisation: Dynamic Light Scattering (DLS) The sample is dissolved or suspended in solution within a (micro) cuvette of 5 μL. This is then inserted into the apparatus where a laser emitting pulses of light at an incidence angle of 90°. This is because the particles are not sufficiently small to diffract the laser light as it passes through the sample. In samples where the particles are larger, there may be a possibility of the particle diffraction which can affect the accuracy of the mean sizes or particle distribution, as diffraction will cause alterations in the interference patterns of the scattered light. The scattering vector is a quantity that arises from tenuous scattering of light due to suspended macromolecules in solution. It can be thought of the time in which it takes for a

Figure 28: A schematic of PCS apparatus with a 90° scattering angle

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particle to diffuse through a distance of K-1 with the time being proportional to K-2 [113]. Wavelength of the laser (632.8 nm in the N4) and the angle, θ, is equivalent to 90 .

(

)

Equation 8

A typical time scale for a measurement is less than one minute with our apparatus’ being 40 seconds. The apparatus is the Beckman Coulter N4 Plus Submicron Particle Sizer and served the function of measuring the Stokes Radius. First of all a sample of solution is prepared pertaining to the ‘Sample Name’ in Table 1 located in the Appendix. The sample is placed in a clear vial. The vial has to initially be rinsed with DI water is such a way that all the water drains from the vial as quickly as possible. Any excess water is dried and wiped off the sides of the vial with lens cleaning tissue. The sample is then inserted into the particle sizer, and sealed in a dark chamber. A program for the apparatus is run and this simultaneously gives the apparatus instructions to project a laser beam through the sample at 90°. The statistics of the scattered light is detected by a photomultiplier, and a computer collects and analyses the results. For adequate statistical accuracy, sufficient light must be scattered by the molecules. A correlation function is accrued for the period in which the intensity is measure shown in Equation 9.

( ) ∫ ( ) ( )

⟨ ( )⟩ Equation 9

Under ideal conditions, the correlation function is expected to show a single instance of exponential decay where Dq2 is the decay rate and highlights the diffusion coefficient. The parameter β is a fitting parameter given as a ratio of coherent signal to incoherent signal [114]. Equation 10 below shows the single exponential decay.

( ) ( ) Equation 10

The Stokes-Einstein equation (Equation 7) can be used to calculate a Stokes radius. The measurement for the radius is given as an average known as a z-average. The data is often displayed additionally given graphically and a polydispersity index is calculated from the normalised standard deviation of the Gaussian particle size distribution [114]. 7.3. Characterisation: Polydispersity Polydispersity refers to how broad the range of sizes, shape, and mass distribution of a sample is. Samples can include polymers and colloidal suspensions among others. A sample of objects having uniform size, shape and mass distribution, is known as a monodisperse with example being water and acid. The reverse is termed a polydisperse. In practice, it is measured as an index. Protein Crystallographers tend to be very interested in the polydispersity of the sample as depending on its value, they can quickly ascertain the presence of protein aggregates that can interfere with the crystallisation process. As such, the polydispersity is also categorised as the relative standard deviation of a samples particle size. The polydispersity can be defined by three regions: monodisperse, if the sample polydispersity is less than 20%, medium disperse if the polydispersity is between 20% and 30%, and polydisperse if the polydispersity is greater than 30%. For the case of a polydisperse sample, if it is not intentionally manufactured to be polydisperse, such as if there will be applications to protein crystallography, then an additional filtration step would be essential to remove the large particles that may interfere with the dynamic light scattering process and ultimately, the crystallisation process [109]. 7.4. Materials The enzymes used include the following: Savinase® 16.0L, Protease from Bacillus sp., liquid, ≥16 U/g (Sigma) and has a concentration of a 40 mg/mL. Termamyl® 120L, α-

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amylase from Bacillus Licheniformis (BLA), Type XII-A, saline solution, 500 to 1,000 units/mg protein (biuret) (Sigma) and has a concentration of 22 mg/mL [115]. The enzymes were utilised in their received form. The salts used include the following: Anionic Trisodium Citrate, premium grade (Sigma Aldrich); Sodium Sulphate, ACS reagent grade, ≥99.0%; Sodium Chloride, BioReagent grade, suitable for cell culture, ≥99.5% (Sigma Aldrich). They also include: Ammonium Chloride, for molecular biology, ≥99.5% (Sigma Aldrich); Phenylmethanesulfonyl fluoride (PMSF) ≥98.5% (GC) (Sigma); Potassium phosphate monobasic, powder, suitable for cell culture, , ≥99.0% (Sigma); Calcium chloride dihydrate, ACS reagent grade, ≥99% (Sigma-Aldrich); and Potassium dihydrogen phosphate, BioUltra grade, for molecular biology, ≥99.0% (T) [115]. The acids, bases, polymers, and organic solvents used include the following: Ammonium Hydroxide, ACS reagent grade, 28.0-30.0% NH3 basis (Sigma-Aldrich); Hydrochloric Acid, 36.5-38.0%, BioReagent grade for molecular biology (Sigma); Acetone, HPLC grade, ≥99.9% purity (Sigma Aldrich). They also include the following: 1, 2-Propanediol, ACS reagent, ≥99.5% (Sigma-Aldrich); Glycerol, for molecular biology, ≥99% (Sigma), Citric Acid, ACS reagent, ≥99.5% (Sigma-Aldrich), PEG 6000, and Polyethylene Glycol 4000 [115]. For manual screening, 24-well plates were used. Pipetman® single-channel pipettes were utilised in sizes: 1 – 10 μL (± 0.05 μL), 2 – 20 μL (± 0.05 μL), and 10 – 1000 μL (± 5 μL), given the uncertainty is taken to be half the smallest unit on the piece of apparatus [116]. The ART® self-sealing barrier pipette tips are utilised to dispense the droplets into the reservoirs and onto the cover glass slides. The diameter of the cover glass slide used is 18mm. 7.5. Sample Preparation The solutions were prepared as per normal protocols and then pH matched with a digital pH meter with an uncertainty of ±0.005. Prior to pH matching, the pH meter was calibrated with the in-built calibration instructions. The meter’s electrode is inserted into a pH calibration solution at the pH the apparatus asks for. They are pH7, pH10, and pH4. The electrode was rinsed with DI water in between transferences to other solutions. To match the pH, a pipette is used to add acid (HCl) or base (NaOH). ≤5μL is recommended to prevent overshoots and simultaneous stirring with a Magnetic Stirrer. 7.6. Hanging Drop Vapour Diffusion Set-up Following the literature review, the experimental set up that was set up, was that of the hanging drop given its success in the past for a range of other proteins. It was chosen particularly because of the dynamicity of the conditions, which will likely aid in the crystallisation of Savinase® 16.0L and Termamyl® 120L. 24 cover-glass slides (18mm diameter) were cleaned with acetone and rinsed with deionised water (DI water) a minimum of three times. They were then dried and checked for cleanliness. Simultaneously, the 24-well plate were washed with Savona® D60 – an all-purpose, viscous, neutral detergent [117] – then rinsed with copious amounts of deionised water and dried. The buffer systems were formulated as was required, and adhered to buffer recipes in literature or obtained from external sources. Pipettes were used to charge the reservoirs with 1 mL of buffer solution, and 15 or 10μL hanging drops. The hanging drops were 50% v/v protein [51]. To achieve varying concentrations, it was diluted with pH matched DI water. Chemplex® 710 Silicon Compound was applied to the rims of the 24 wells as a means to control the rate of evaporation. The set-up drops on the cover glass were then placed, with

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Figure 30: the coated cover-glass slides and vials filled with the Sol for batch experiments

Figure 31: the surface structure of the coated hydrothermally treated cover glass slides. x20 magnification

care, over the wells resting on the rims; light pressure was applied to seal the well. The finished plate was then transferred to an incubator with an internal temperature of 18.0 ± 0.05°C. 7.7. Nano-Templates Preparation Once the Sol is ready, the cover glass undergoes the same cleaning procedure documented above. Once cleaned, they are dipped and submerged in the Sol solution for one minute. The cover glass is then pulled out very slowly over a period of 30 seconds for the 18 mm diameter glass slides. The larger square 24 x 24 mm glass slides are pulled out over a period of 60 seconds. The length of time required is proportional to the size of the cover glass, and the thickness of coating required. The cover glass slides were then left to dry for 24 hours. The dried cover-glass slides can be seen in Figure 30. The vials were left for 5 days where the Sol coated the inside of the vial. The process of drying left behind an intricate pattern on the surfaces of the glass. After the required dry periods, they were hermetically sealed and hydrothermally aged for two days at different temperatures depending on the final product requirements. The glass slides will now have a clear porous substrate lining it and is subsequently ready to use. The coated cover glass then subsequently undergoes a hydrothermal treatment process to create the surface structure as shown in Figure 31: the surface structure of the coated hydrothermally treated cover glass slides. x20 magnification. 7.8. Microscopy – Droplet Imaging An Olympus made microscope with Olympus lenses, of 10, 20, 40 and 50 magnifications, were utilised for imaging with the image analysis software “analySIS” ® Soft Imaging Software. 7.9. Mosquito Nano-litre Robot Fourteen commercially available screens were provided by the CSB crystallisation facility. The choices of screens are chosen to limit the amount of repetition and cover the broadest range of variables possible. The screens were pre-dispensed into 96 well MRC plates. A TTP lab-tech manufactured Mosquito nano-litre high throughput robot shown in Figure 32, performs the experiments using positive displacement disposable tips on a reel. This eliminates any possible chance of cross contamination or requirements for cleaning the tips and thus results are more reliable. The required time to set up each plate is three minutes.

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y = 0.0016x2 - 0.0213x + 7.9788 R² = 0.9962

0

5

10

15

20

25

0 12.5 25 37.5 50 62.5 75 87.5 100

Sto

ke

s R

aiu

s (

nm

)

Protein Concentration (%) Figure 33: a plot of Stokes Radius vs. Protein Concentration showing the relationship

Figure 32: The Mosquito apparatus utilised in high throughput screening

The screens used were the Hampton Research Crystal Screen HTTM and HT2TM, Wizard Screen I, II, III, JCSG, Morpheus, MemGold crystal screens. Plates are stored at 6 degrees in the fridge next to the Mosquito. Prior to setting up the experiments, the plates were allowed to reach room temperature as some of the well solutions are very viscous so the solution dynamics can be very different at 6 degrees Celsius to that when at 20 degrees Celsius [118]. Once the experiments have been formulated, they are stored in a vibration-free crystallisation incubator that is temperature controlled. In order to view the plates, there are two Leica M165C microscopes. It is equipped with a CCD camera linked to a PC to enable pictures to be taken or view the plates live on the monitor [118]. 8. Results

8.1. Results of PCS Measurement

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The table in the Appendix (Table 1) shows the raw data obtained from the measurements gives the Stokes radius as a Z-average. The results suggest that the Stokes Radius is approximately 7.6 ± 0.1 nm. Further, polynomial trend analysis highlights that the data fits a second order polynomial with an R2 value of 0.9962. The y-intercept is slightly greater than the value we suggest the Stokes radius to be, however, this is likely to be caused by the point that does not fall on the trend line. Fitting the data to a third order polynomial gives a y-intercept of 7.35 nm, and a fourth order, yields an intercept of 6.71 nm, all without a significant change in the R2 value. This only proves a point made by Galkin and Vekilov (1999) that dynamic light scattering data is difficult to interpret clearly [119]. Fitter (2004) obtained a result of 4.0 ± 0.3 nm for folded α-amylase from Bacillus Licheniformis, and 5.2 ± 0.4 nm for the fully unfolded enzyme (achieved by adding 6 M GndHCl [guanidine hydrochloride], and with calcium depletion) [24]. Considering the fact that the protein is likely to be in the folded state, the Stokes radius of the protein is approximately twice as large. However, the experimental set-up differs from our own. For example, Fitter et al. (2004) used an Ar+ laser with a 488 nm wavelength, and a scattering angle of 40°. We use 90° as larger particles in solution will scatter light at a lower intensity for this angle, and so smaller particles, which will scatter at a higher intensity, should take precedence in analysing results. This single difference will influence the Stokes radius greatly as the scattering intensity will not be comparable if the scattering angles are not. It has been reported that measurements of size are highly sensitive to the scattering angle, more so for angles less than 120°. From their groups work it appeared that the size was present as the squared sine of the half angle used for scattering [108]. Equation 11highlights this where D is the diffusional constant, kB is the Boltzmann constant, T is the temperature, η is the viscosity, and rH is the Stokes radius, τR is the relaxation time [120].

(

)

Equation 11

Equation 12

These results should not be taken to be the exact size as proteins are certainly not spherical with their Stokes’ radius being dependant on their conformation and molecular weight. Despite the water molecules being relatively small compared to the protein molecule, they still affect the proteins diffusion [111] as the water molecules are bound the protein molecule. As such, the Stokes radius can diverge considerably from the actual size [111]. The Stokes-Einstein equation, shown in Equation 11, relates the diffusion coefficient to the Stokes Radius of an equivalent sphere [24]. Therefore, from Equation 8, it is clear the greater the diffusion coefficient of the protein, the smaller the radius. The diffusion coefficient is a not a constant but a term which depends on the viscosity of the solution, temperature and particle sizes. The lower the protein concentration, the less viscous the solution will become. This results in a higher diffusion coefficient. From the equation, the higher the diffusion coefficient, the smaller the Stokes radius becomes as shown in Figure 33. An error however may arise as the concentration varies. By changing the protein content of the solution, the refractive index of the solution will subsequently be altered. Thus, from Equation 11, one can see that a change in the Stokes radius rH will result. Figure 33 includes 5% error bars. 8.2. Screens Employed 8.2.1. Screen 1 We initially implemented the conditions of Betzel et al. (1992) [27] as a starting point in our crystallisation study. The reservoir solution was composed of 10% (w/v) PEG 4000, 1M NaCl, 5 mM CaCl2, 50 mM Sodium Citrate Buffer (pH 6.5). The concentrations in the hanging drop were: 4% (w/v) PEG 400, 0.33M NaCl, 1.5 mM CaCl2, 18 mM Sodium Citrate

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Figure 34: A crystal on the right of the image and two small joined crystals in the middle of the image; x 20 magnification taken after 5 days

Figure 35: A crystal highlighted by an arrow. x20 magnification taken after 5 days

Buffer (pH 6.5) [27]. The concentration of protein in the droplet was 20 mg/mL, filtered. Once we set-up the experiments, we incubated them at 18.0 ± 0.05°C as in the original experiment of Betzel et al. (1992), the obtained crystals at 18°C. Results of Screen 1

The results of this initial screen appeared to be irreproducible. Betzel et al. (1988) reports finding monoclinic crystals with sizes of up to 0.5mm x 0.5mm x 1.5mm [121]. He however did not state the induction time to obtain these crystals. The images were taken after 5 days.

We deemed the results irreproducible in light of the quality of the crystals obtained. Only two of the 12 identical wells produced a crystal that interacted with light, and were approximately 10 microns in size (Figure 34 and Figure 35). Repetitions of the experiment yielded crystals with defects, microns in size, or protein aggregates. The purity of the chemicals may have resulted in the ions interacting differently. For example, in the original literature by Betzel et al. (1988) [121] that outlines the methodology used in Betzel et al. (1992), the protein underwent special procedures to prepare it for use. It was initially dissolved and equilibrated with a three-component buffer by passing it through a Sephadex G25 column. The sample then further underwent ion-exchange chromatography on CL-6B in the same buffer system, finally undergoing ultra-filtration to approximately 30 mg/mL. A subsequent separation step included inhibiting the enzyme with PMSF and further gel filtration on Sephacryl S-200 in a two component buffer system resulting in a final concentration of 23 mg/mL [121]. Our methodology requires only the use of the received form and so there are subsequent difference in the purity and a slight divergence in the concentration used, which is likely to have an effect on the nucleation step. Maybe the precipitant concentration was not suitable for diffraction quality crystals to form. Of the many effects that precipitants have on nucleation, they can affect the solution viscosity influencing the diffusion coefficient, and hence the transport of molecules to the crystal. If the PEG concentration was too great, then the solution might have been too viscous. Perhaps PEG was influencing the proteins solvation layer too greatly, decreasing the electrostatic shielding, and aggregating the proteins too quickly to bond in their most thermodynamically stable state. A separate investigation was made into this at a later stage to determine how PEG affected nucleation. Additionally, according to the Hofmeister Series, there could be the possibility that the salt CaCl2 was not salting out the protein (decreasing its solubility) to the required degree.

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Figure 36: Titration curves for Savinase® 16.0L. The inverted triangles are 0.001M, squares are 0.01M, triangles are 0.05 M, and circles are 0.1M. The isoelectric point occurs where the net charge is zero; pH 10. From Duinhoven et al. (1995).

Figure 37: a graph highlighting a percentage activity – pH graph of three detergent proteases at 25 ◦C. The reaction time is 10 min. The graph is from Herbots et al. (2000)

We have already discussed that the higher the ions position on the series, the more effective the ion is at attracting water molecules from solution and (more importantly) from the protein solvation layer. This reduces the “shielding” the water molecules provide to the secondary Van der Waals forces that facilitate the condensation of the protein molecules, and subsequent nucleation. Anions are believed to have a greater effect than cations [79] therefore, a phosphate or sulphate should be used. In protein purification, ammonium sulphate is used, and because of the high solubility of ammonium sulphate, high ionic strengths are permitted. However, considering the buffer, a sodium citrate buffer appears favourable from the series. Citrate follows the sulphate ion, which is known to be a good salting out agent in addition to sodium from sodium chloride. pH further affects the surface charge on the proteins as shown in Figure 36 [122], and a pH-activity curve is shown in Figure 37 [123]. A pH of 6.5, which the buffer was matched to, gives an approximate surface charge of 5 C, and is additionally seen how the pH influences the surface charge of Savinase® 16.0L. Ideally, with respect to charge, the ideal operating point is around the isoelectric point to maximise Van der Waals interactions between the molecules, however, this is also the where the protein appears to be the most active. From a molecule aggregation point of view, it is necessary to utilise a pH that allows for these coagulation properties to be optimised; i.e. sufficient for stable aggregation and not too great for immediate precipitation (insufficient time for the protein to find the correct orientation that minimises its free energy, or even form some kind of crystalline structure). Further, the pH used was 6.5 but the effects of this pH on crystallisation need to be determined. pH will affect the mobility of the active site, and so a lower pH will result in a reduction in activity creating a stabilising effect compared to approximately 10.5 where it is most active. However, pH also affects factors such as the zeta-potential as one can treat the protein solution as a colloidal dispersion. It will certainly influence the surface charge of the protein, which in turn will affect the ease of nucleation. Further work will be needed to determine the zeta potential from theoretical models, and match buffer components and the pH to be more favourable to nucleation. Imaging the experiments a further five days later, highlighted the growth of two new crystals and many more aggregates. The growth of new crystals (one of which is relatively large)

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may indicate a very long induction time with this buffer system given that these images in Figure 39 and Figure 38 were taken after 10 days. To ascertain this, more experiments were carried out to test the effects of various parameters that affect nucleation such as pH, the effects of PMSF (the serine protease inhibitor), precipitants, and heterogeneous nucleants.

8.2.2. Screen 2 A Savinase® 16.0L crystallisation screen was devised under the conditions of 100 mM Tris-HCl Buffer, pH 8; no additives or precipitants were added in the reservoir. The reservoir was 1 mL in volume, and the hanging drop had a volume of 15 μL. The same buffer system and conditions were utilised in the droplet mixed in a 1:1 ratio. The protein concentration was 20 mg/mL in the droplet. It was further filtered prior to the set-up and subsequently incubated at 18.0°C. Results of Screen 2

We took images of the experiments after 6 ± 2 days, and the results appear to be largely unsuccessful. In the Appendix, Figure 104 portrays examples of very small crystals less than 5 microns in size that precipitated in solution. The experiments were imaged again after 2 days to further gauge the nucleation rate, and further observe whether any further nucleation had taken place. Figure 105, also located in the Appendix, shows a crystal that had grown marginally in solution in the additional two days. This experiment was deemed unsuccessful due to the lack of crystals greater than 10 microns in size to allow their analysis. In comparing these results with the Tris-HCl buffer to the citrate buffer, relatively very few aggregates formed, suggesting that this buffer system bore potential to be optimised by finding suitable pHs, and precipitants and additives to incur nucleation with a lower induction time. The absence of crystals after 6 days may point the final droplet concentrations being in the soluble region of the phase diagram. 8.2.3. Screen 3 For this screen, we administered Savinase® 16.0L filtered with a flat disk filter of concentration 20 mg/mL to the droplets. The droplets were 15 μL. To each of the droplets, a few microns of the nano-porous template were incorporated: Template A, B, C, and D. They were administered to all of the four rows respectively. Tris-HCl of 100 mM concentration (pH 8) was used with no further precipitant or additive. The same buffer system was used in the reservoir of 1 mL, again with no precipitant or additives. This was designed to test the effectiveness of the nanoporous glass compared to the previous screen that did not incorporate the templates.

Figure 39: a new crystal spotted after 10 days with x40 magnification

Figure 38: another large crystal taken after 10 days with a magnification of x40

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Results of Screen 3

All images were taken after 3 ± 1 day. From looking at the results below the experiments yielded larger crystals, such as in Figure 40 compared to the crystals of the previous screen such as in Figure 39 and Figure 38. Small crystals appeared in solution after 3 days and so the reduction in induction time is very clear. The templates have not only reduced the induction time from 6 days to 3 days, but have produced better quality crystals compared to the preceding screen after 3 days on account of the sharper phase boundaries witnessed in Figure 40. However, after a further 3 days, the crystal in Figure 40 did not increase in size or improve in quality comparable to Figure 38 or Figure 39. The template only seemingly reduced the induction time. In comparing the effects of the respective templates, Template B grew precipitates frequently, whereas Template A did not induce nucleation. The occurrence of precipitates, such as that shown in Figure 106 located in the Appendix, possibly indicate that the buffer concentration is too great, or pH is unsuitable for nucleation and subsequent crystal growth. Nucleation was ostensibly aided by the addition of Template C in these instances, and thus more effective that Template A and B. This is likely to be the case because the pore size is more compatible with the Stokes Radius of the protein, allowing sufficient condensation within the pores, sufficient local immobilisation, and local supersaturation. Comparing the results of with and without Templates, there are stark differences. With comparable buffer systems, the induction time without templates is much greater than with templates. The induction time has at best been cut by a half; taking into account the frequency of viewing the experiments. Although the induction time was six days, there is a two day period in which nucleation may have occurred. The fourth template, Template D, was unsuccessful in inducing nucleation. More images were taken after 3 days and are shown below.

Figure 40: An image of what looks to be an unsymmetrical diamond; Template C, x40 magnification taken after 3 days

Figure 42: A further new crystal that has grown after an additional 3 days with Template A. The magnification is x 40

Figure 41: New crystals that have grown three days after initial imaging with Template A. the magnification is x 40

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After a further 3 days, the experiments presented no change in the crystal size or quality for the existing crystals. However, new crystals formed in the droplets which incorporated Template A and D. Figure 41 shows what appears to be two additional crystals in the experiment incorporating Template A. Template A also induced further nucleation producing crystals approximately 20 microns large shown in Figure 42. Figure 106 located in the Appendix, shows an aggregate whereas Figure 43, highlights a small trigonal crystal that appears to be of diffraction quality. The growth of crystals in the smallest and largest pore sized templates (A and D), significantly later than the intermediate sized templates (B and C), support Page and Sear’s (2006) observation that there is an optimum pore size to minimise induction time and maximise crystal growth. The crystal fills the pores quicker in narrower pores as it grows, but grows slowly in the bulk phase, whereas wider pores fill slowly but the crystal grows in the bulk quicker [7, 91]. The size and time it takes to grow could indicate unfavourable conditions in the buffer. Given there are no precipitants, the only variables are the concentration and pH. Further factors to consider could include the zeta-potential of the nucleant; the nanoporous template. The nucleant carries its own net charge, which is affected by the pH of the solution. For favourable condensation of a dense phase from which a crystal could nucleate, the zeta potential of the solution containing protein and template, should ideally be as low as possible or optimised so that there is a reduction in the repulsive forces to induce local supersaturation quicker. We have not yet determined the zeta-potential of the nucleant and the protein, so the extent of attraction and repulsion between the nucleant and protein is further unknown. Nor have we studied the effects of changing the pH on the electrostatic forces between the protein and nucleant. 8.2.4. Screen 4 An investigation into the effects of phenylmethylsulfonyl fluoride (PMSF), the serine protease inhibitor required the addition of the compound the droplet. The compound acts as an inhibitor bonding specifically and covalently to the active site, reducing the activity of the macromolecule. Savinase® 16.0L, the protease, will be susceptible to its effects. Betzel et al. (1988, 1992) utilised the molecule in their screening experiments. Our reservoir solution contained 10 mM Tris-HCl; lowered to verify whether the buffer was too concentrated beforehand. We further added no additional additives or precipitants. The columns incorporated pHs of 7.2, 7.6, 8.0, 8.4, 8.6, and 9.0 to reflect the pH range where the protein is less active. The droplets had matching pHs and a Tris-HCl buffer of 5 mM to ensure a concentration gradient and influence the evaporation rate. We divided the 4 x 6 array into two horizontally so that the first two rows (2 x 4) were void of PMSF. Subsequently, for the latter rows, we added PMSF (10% v/v, 3 mM) to the droplets. The protein was pure and filtered with a 0.2 micron disk filter, and had a concentration of 20 mg/mL.

Figure 43: A trigonal crystal taken with x40 magnification with Template D after 6 days.

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Results of Screen 4

A pH of approximately 8.6 was revealed to effective in inducing nucleation. The pHs 7.2, 7.6, and 8 did not provoke nucleation in the first three days. The lack of crystals for pH 9 suggests that a pH which is closer to where it is most active is unfavourable for nucleation given Savinase® is most active at pH 10 [80]. It additionally reiterates how sensitive proteins are to pH change as a 0.4 change is the difference between a large poor quality crystal, and very small crystals. Comparing the results for PMSF, shown in Figure 44 and Figure 45, and without PMSF, shown in Figure 46 (which was one of the only examples of crystal growth), the crystals certainly appear to be larger when PMSF was added with more pronounced phase boundaries, despite defects present, as opposed to without PMSF. This reveals that the inhibiting effect of the protease inhibitor, PMSF, is aiding nucleation. One mechanism being the inhibition effect PMSF has on Savinase® 16.0L when it bonds to the active site. The reduction of its activity increases thermodynamic stability aiding nucleation. Again, Figure 47 highlights the above finding that PMSF and a lower pH yield a better crystal compared to that with no PMSF and a pH closer to the pH of maximum activity. However, there appears to be a range of effectiveness as a pH of 8.4 grew the largest crystal, albeit with a longer

Figure 45: x40 magnification image taken after 3 days, pH 8.6, and with the addition of PMSF

Figure 44: a crystal taken with x40 magnification, pH 9 and PMSF. Notice that the crystals are smaller for this pH

Figure 47: A large crystal taken after 6 days with PMSF added, pH 8.4; x 40 magnification

Figure 46: A crystal taken in a pH 8.6 crystallisation solution, taken after 3 days, without the addition of PMSF and x40 magnification

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induction time. For pHs lower than 8.4, the instance of crystallisation was rarely present with or without PMSF, and not present for pHs 7.2. This might indicate that a pH of 8.4 ± 0.2, promotes favourable electrostatic interactions and hence nucleation, resulting in the pH 8.4 yielding the best results. For these experiments, the concentration of the buffer was reduced from 100mM (Screen 2 and 3) to 10 mM in the reservoir, and 5mM in the hanging drops to provide the pHs required and to further assess the effects different concentrations in the reservoir and crystallisation droplet had on nucleation. Theoretically, the results should show that a lower concentration of buffer is beneficial. Despite there not being an evident reduction in the induction time, this screen comparatively produced better crystals, with an observed greater yield, than Screen 2. The addition of PMSF further influenced nucleation positively yielding larger crystals, with that of Figure 47 the largest thus far.

8.2.5. Screen 5 We furthered our study on the effects of polyethylene glycol (PEG) on the induction time of Savinase® 16.0L crystallisation. We divided the 4 x 6 array into two vertically with the left side (4 x 2) focusing on PEG 4000, and the right, PEG 6000. The reservoirs contained 10 mM Tris-HCl buffer solution (pH 8) in light of the results of the previous screen, suggesting lower concentrations were more effective at inducing nucleation. The reservoirs also contained 15% w/v PEG. We charged the reservoir with 1 mL of reservoir solution and the hanging drops were 15 μL in volume. The droplets contained the same buffer system and precipitants for their respective side of the well plate. The protein was at a concentration of 20 mg/mL in the droplet. Results of Screen 5

The results of the experiment were deemed a failure given the induction time. A duration of 6 ± 1 days were required to witness any results, and the results showed that they were additionally aggregates, such as in Figure 108 located in the Appendix. In all other replications where precipitates were not present, the droplet remained clear as in Figure 109. It was not ascertained why nucleation was not induced after such a long period, and subsequently why no crystals grew. One theory could be that the heat flow affected nucleation. Condensation developed around the droplet on the cover glass, and there is a possibility that this condensation sufficiently diluted the hanging drop to cause the dissolution of any crystals that may have formed [124]. Figure 48 highlights the condensation on the cover glass slide. The right of the boundary portrays the space outside of the drop. This may be emphasised by the formation of precipitates indicating that here was possibly the potential for crystals to grow, but it is likely that they dissolved back into solution. The condensation may have arisen from the difference between the temperatures in the incubator and external environment in the lab causing condensation around the droplet. Another possibility is if the initial rate of mixing was too high, there may have been the occurrence of reagent-shock. Consequently, the protein may precipitate before it can nucleate [72], possibly explaining the occurrence of precipitates and not crystals.

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Figure 49: x40 magnification; Template C, taken after 3 days, with PMSF

8.2.6. Screen 6 Filtered Savinase® 16.0L of concentration 20 mg/mL was administered to the droplets. To each of the droplets, the template was incorporated with each of the four sizes (Template A, B, C, and D), corresponding to an individual row to follow the previous findings of reduced induction times with templates. Tris-HCl of 10 mM concentration (pH 8.6) was used with no further precipitant or additive. The 4 x 6 array was further divided into two vertically with PMSF, the serine protease inhibitor, added to the droplets on the right (4 x 2) of that division. The same buffer system was used in the reservoir, again with no precipitant or additives. Results of Screen 6

The results once again showed the difficulties of crystallising Savinase® 16.0L. Due to the success of reducing induction times with the incorporation of templates and PMSF separately, we sought to incorporate both the parameters at once to see if a combined effect would reduce the induction time further. Comparing the results for Screen 3 (pH 8) and this Screen (pH 8.6) with focus on the effects of the templates, there was seemingly no apparent improvement despite it being found that pH 8.6 should favour nucleation. This screen also demonstrated that Template C was more effective inducing nucleation in a shorter period than the other template sizes. Precipitates still formed however, as shown in Figure 110 located in the Appendix, and the frequent precipitation of very small crystals less than 5 microns within a comparable period. From the results of Screen 3, Figure 40 seems to suggest that Screen 3 was more successful yielding better quality crystals. The addition of PMSF however, did present itself to improve crystals quality significantly, confirming past findings that suggested its inhibiting effect allowed larger crystals to grow.

Figure 48: An image showing the level of condensation that has arisen in the droplet, which

is reported to cause dissolution of crystals back into solution via dilution of the drop.

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Overall, the difficulty in crystallising Savinase by systematically changing crystallisation parameters was difficult thus far. If precipitates did not form, the crystals that did form were of poor diffraction quality and/ or very small with a very low yield as shown in Figure 49. 8.2.7. Screen 7 One final screen to analyse the effects of pH, and the incorporation of Templates was implemented. Filtered Savinase® 16.0L of concentration 20 mg/mL was administered to the droplets. To each of the droplets, the template was incorporated with each of the four sizes (A, B, C, and D), corresponding to an individual row. 5 mM Tris-HCl was used with no further precipitant or additive in the droplets. The reservoir solution contained 10 mM Tris-HCl and no additives or precipitants. The columns incorporated a pH’s of 7.2, 7.6, 8.0, 8.4, 8.6, and 9.0. This screen was designed to test the effectiveness of the templates to induce nucleation at different pHs, and verify whether a pH of 8.6 was best with this buffer system. Results of Screen 7

The results for crystallising this protein are once again very poor. The plates were viewed after 72 ± 24 hours. The only definitive result after performing the experiment twice is the crystal in Figure 50. It has pronounced phase boundaries but they are insufficiently sharp to be termed high quality. Surprisingly, this grew with pH 8, which contradicts the results of Screen 4 that show a pH of around 8.6 yields the best crystals. This may be a result of the surface charge of the nucleant.

The design of Screen 4 was such that half the wells did not include PMSF, just like this screen. Thus, save the addition of templates, this screen is comparable to that of Screen 4. Comparing the results, we found it evident that the templates had positively influenced crystal growth where PMSF is not used as an additive. However, comparing the results to that of Screen 3 for example Figure 50 and Figure 42, which also tested templates, show that this screen was not as successful given the poorer crystal quality. Upon evaluation of the respective template sizes, Template C was once again observed to be the most successful in inducing nucleation and reducing induction time due to comparatively larger crystals. The Template D, the largest pore size, did not generate crystals. In implementing these matrices, it is clear that many parameters and additives require further optimisation. From the results, it is apparent that the Templates have enhanced nucleation. Template C was revealed to be the most effective overall in reducing the induction time, nevertheless, there was potential for template sizes such as that of A to yield higher quality crystals after longer time periods. More experiments will need to be carried out with more suitable buffer systems to test this however. Our results revealed that a pH of 8.6 ± 0.2 yielded the best quality crystals with a lower concentrated Tris-HCl buffer system with the largest growing with a pH of 8.4. However, based on the results of Screen 7, the addition

Figure 50: pH8; x 40 magnification; taken after 72 hours; Template B

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of templates indicates a lower pH of 8 is more suitable, possibly as a result of the nucleants properties. These results further revealed the sensitivity of crystallisation of proteins to parameters such as pH. This is noted, as a pH in the range of 7 or 9 did not yield crystals agreeing with Cox and Weber (1987) and McPherson (1990) who found and note respectively, that crystallisation is very sensitive to pH with a range of 0.5 being the difference between a crystal or a precipitate [4, 60]. However, this is very specific to this buffer system. The ions within the buffer formulation are expected to interact with the macromolecules in a way specific to the buffer, and as such, is the reason why some buffer systems are not suitable for certain proteins. We further ascertained that the addition of PMSF improved crystal quality producing larger crystals with comparatively more crystalline features such as clarity, and reduced the induction time without templates. The induction time did not significantly change upon the addition of templates. In implementing a change in the buffer system from a citrate buffer (pH 6.5) to Tris-HCl (pH 8), the induction time was reduced from 6 ± 2 days, to 3 ± 1 days. A lower concentration, and thus ionic strength of the Tris-HCl buffer, was further found to yield crystals that had fewer defects, were larger comparatively, and had sharper phase boundaries. To further this study and find the optimal concentration, a working phase diagram could have been created to understand which conditions pertain to the precipitation zone, and which pertain to the nucleation zone. To find better crystallisation conditions we decided to opt for high throughput screening as it will allow a vast range of crystallisation parameters to be tested on a “hit” basis; i.e. does a condition yield a crystal or not? These results will be documented shortly. 8.2.8. Screen 8 We additionally focused our attention on Termamyl® 120L and thus sought to assess the effectiveness of a literature derived screen for α-amylase from Bacillus Licheniformis. The conditions used, were those outlined in Suzuki et al.(1990) [125] and his work with α-amylase. A 1 ml reservoir was charged with an Ammonium Hydroxide, Ammonium Chloride buffer system of pH 10.5 and 50 mM concentration. 5% (v/v) 10 mM EDTA, and 1.2 M Na2SO4 were also added. The droplet conditions also adhered to that of their corresponding reservoir. We further divided the array into two vertically and incorporated the templates into one-half (4 x 2) of the crystallisation plate. The four nano template sizes were administered to the rows respectively. A few microns of the template were administered to the 15 μL drop with a different size for each row. Results of Screen 8

By comparing the results of this protein and those of Savinase® 16.0L, it is immediately clear the yield of crystals has increased. The images shown in Figure 51 and Figure 111 portray the high nucleation rate in the droplet with these conditions. This was the general result for all the experiments without the incorporation of template. The quality of crystals was such that none were observed that had sharp phase boundaries. Crystals grew on top of each other, and larger non-crystalline forms precipitated. This protein has subsequently already shown signs that it may be easier to crystallise than Savinase® 16.0L. However, the buffer systems are not comparable, and so this observation may not be appropriate.

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Figure 51: x 40 magnification; 48 hours; NO Template

Figure 54: x40 magnification; taken after 48 hours, Template B

Figure 52: A large single crystal a-amylase from Bacillus Licheniformis. Crystal dimensions are reported to be 0.2x0.2x0.8 mm.

These results were found to be largely irreproducible of Suzuki et al. (1990) experiment with α-amylase from Bacillus Licheniformis. They document the acquirement of large, single crystals that belonged to the tetragonal system when he crystallised the protein. These results do not reveal that, as shown in Figure 51 and another example located in the appendix Figure 111. The results are more characteristic of their results for the crystallisation of α-amylase from Bacillus Amyloliquefaciens. It is important to note however, that they received large single crystals after 10 days, so we further left the experiment for a longer period; the crystals did not change in size or quality. Another point to note is that Suzuki screened different EDTA concentrations, from 10 mM EDTA to less than 2.5 mM EDTA. Their results indicate that lower concentrations of EDTA yield better quality crystals with his best crystal being grown in 2.5mM EDTA, an example of which can be seen in Figure 52 [125]. The results of using a lower concentration will be documented shortly. We then further assessed the effect the Templates had on the nucleation rate and yield. The nucleation rate appears to have vastly increased upon the incorporation of templates, the only variable. The crystals also appeared to have better quality with greater crystalline properties compared to not using the templates. Figure 54 above shows an image where the crystals forming, appear to be concentrating around two points.

Figure 53: x40 magnification, imaged after 48 hours; Template B

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Figure 56: Template C; x 40, 48 hours

This may be due to the template’s ability to create local supersaturation. The level of supersaturation however, is in all probability too great; a precipitate is forming instead of a crystal. Further, a concentration gradient may exist around the precipitate reducing the local protein concentration to a level where crystals can form. This is suggested as the number of nuclei reduces proportionally with distance from the locality. As this occurs, new surfaces for the proteins to grow on could be formed, and from these sites, crystals can nucleate. This is what appears to be occurring in those two sites. One result, which seems unusual, is that of Figure 53 that shows an image of a comparatively large crystal amongst numerous other small crystals. This relatively large crystal of approximately 7-10 microns goes against reasoning and knowledge from literature that high nucleation rates should consume the crystal building resources: the protein molecules and the space to grow. However, the apparent rate of nucleation is still not as great as the apparent rates in Figure 56, and so there may be opportunities for relatively large crystal to grow. An important point to note is the yield of crystals with the use of template compared to that without the use of template. With templates, the yield of crystals is much greater. Given the identical system – same precipitant concentration, same buffer, same protein concentration etc. – the Template is clearly affecting the nucleation rate, increasing it. The induction time is 48 hours ± 48 hours, and so the difference in yield should indicate that the induction time has indeed reduced by a certain amount. This agrees with the findings of Chayen et al. (2001) and Takehara et al. (2008) amongst other researchers, which found that the use of heterogeneous nucleants aided nucleation and yielded better quality crystals. The crystal quality is generally unsatisfactory with non-sharp phase boundaries, but compared to experiments without templates, there is a marked improvement. This further agrees with Takehara et al. (2008), as the induction time has reduced, akin to what his experiments with heterogeneous nucleants also indicated. The rate of nucleation for Template C incorporation has comparatively peaked, highlighting the greater effectiveness of this template size compared to that of Template B. One possible application may be the separation of these crystals from the bulk solution to enhance purification of the protein. We believe that it is highly unlikely that the protein is 100% pure and given that the cells which produce the protein also produce numerous other proteins, there is a chance that electrophoresis may not separate the proteins completely. Although there are hardly any diffraction quality crystals, there are certainly crystals, all of which are pure protein; separated from the constituents of the solution. Further, we are using a received form of the protein whereas in the literature, Suzuki et al. (1990) purified the

Figure 55: x40, 48 hours, Template D

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protein numerous times; initially by high performance liquid chromatography (HPLC) and subsequent dialysation processes and equilibration with a range of buffers they prepared. The protein we are utilising is not comparable in purity, which will affect crystallisation. The rate of nucleation appears to have decreased for the largest pore size pertaining to Template D, as shown in Figure 55. If better conditions are found, then Template C is certainly the more favourable template to use due to its apparent strength in inducing nucleation. Template A did not yield any results within 48 hours and after 3 days, the crystals were similar to Template D. Referring to a phase diagram, possibly the concentration of precipitants is too large for the there to be metastable conditions resulting in an excess of nucleation. As a result, we reduced the precipitant concentration in later screening matrices. 8.2.9. Screen 9 We also sought to investigate the effects of Polyethylene Glycol (PEG) on the induction time for Termamyl® 120L (α-amylase). We further took this opportunity to test an alternate buffer in light of the thoughts that the buffer was causing the growth of small crystals a few microns large. We divided the 4 x 6 array into two vertically with the left side (4 x 2) focusing on PEG 4000, and the right focussing on PEG 6000. The reservoirs contained 10 mM Tris-HCl buffer solution (pH 8) and 15% w/v PEG. We charged the reservoir with 1 mL of reservoir solution and the hanging drop was 15 μL in volume. The droplets contained the same buffer system and crystallisation agents for their respective side of the well plate. The protein was at a concentration of 11 mg/mL in the droplet.

Results of Screen 9

For this screen, we utilised another buffer system and precipitate. The results follow.

The results display crystals that precipitated from solution in Figure 57 and Figure 58. They were approximately 20 and 10 microns in size respectively and both the yield and nucleation rate were lower than the previous screen. Like the results for Screen 5, there was also a build-up of condensation on the cover-slip and so the incidence of crystal dissolution may have resulted due to drop dilution [124]. The crystals are of apparent higher quality than the previous screen with sharper phase boundaries as shown in Figure 58 highlighting a trigonal crystal. The induction time has also increased from 24 hours, to 96 hours and so Tris-HCl was determined to be unsuitable. This may also highlight why the results for Savinase® 16.0L were not ideal and highlights the need for a more suitable buffer to be sought out.

Figure 57: A crystal imaged after 4 days; x40; PEG 4000

Figure 58: A crystal imaged after 4 days; x40, PEG 6000

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8.2.10. Screen 10 Following the conditions of Suzuki et al. (1990), an Ammonium/ Ammonium Chloride buffer system of pH 10.5 was employed. 1 ml reservoirs contained 2.5 mM EDTA at 5% v/v and 0.5 M Na2SO4. We reduced the concentrations because we believed the higher concentrations were creating an excess of nucleation. Looking at a phase diagram, this could also be a result of the protein concentration. As a result, in this screen, we sought to investigate the effects of protein concentration and formulated amylase solutions of different concentrations diluted with pH matched DI water. The concentrations used were 2.2, 4.4, 5.5, 6.6, 8.8, and 11 mg/mL. The same concentrations of buffer solution and precipitants were added to the drop. Results of Screen 10

The results highlight the evident divergence from literature results such as Suzuki et al. (1990) [125]. Figure 60 above shows the high nucleation rate that was observed for the previous screen despite the reductions in precipitant concentrations. The crystals were highly faceted with sharp phase boundaries. This might indicate that the buffer is responsible, and we should have perhaps reduced the buffer concentration additionally. However, Cox and Weber (1987) [61] found in their experiments that crystallisation was insensitive to buffer changes and highly sensitive to pH changes. The pH may additionally be affecting factors such as the yield given the changes in pH where the pH in this screen is 10.5, and the previous screen was pH 8. In light of the following results, it is believed that the crystal in Figure 59 may be an anomaly. However, this result is the one of the only results, which is comparable to literature results being a large single crystal, though of poor crystalline order. We imaged these experiments after 24 hours, and there was no subsequent change after longer periods. As the protein concentration reduces from 100% to 60% there appears to be an increase in the crystal quality, which is marked when comparing, Figure 60 and Figure 62 for example. The size again indicates that the system may be in the nucleation zone however.

Figure 59: x40 magnification; crystal that appears to be anomalous, 11 mg/mL 24 hours

Figure 60: Very small crystals that grew; x40, imaged after 24 hours, 11 mg/mL protein concentration

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.

Figure 62: Another image of the crystals obtained x40 magnification after 24 hours highlighting the morphology; 8.8 mg/mL protein concentration

Figure 61: Crystals that have nucleated and once again are very tiny; x 40 magnification, after 24 hours; 6.6 mg/mL Protein Concentration

Figure 63: Another relatively large crystal that has nucleated in the hanging drop. x40 magnification and taken after 24 hours; 5.5 mg/mL

Figure 64: x20 image to highlight the similar crystal morphology to the 6.6 mg/mL and 8.8 mg/mL experiments. There is a 5.5 mg/mL protein concentration in this droplet

Figure 65: Some good quality crystals have nucleated; x40 magnification; 24 hours; 2.2 mg/mL protein concentration

Figure 66: Crystals that grew after 24 hours. x40 magnification and 4.4 mg/mL protein concentration

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Figure 63 portrays one of only two larger crystals that appeared after 24 hours. The other crystal also had a similar morphology. They were markedly larger than crystals obtained at higher concentrations and obtained after 24 ± 24 hours. It initially appeared that at lower concentrations of protein, where more feasible in growing relatively large crystals in comparison to higher concentrations. However, in light of results, such as Figure 64, which is also for 5.5 mg/mL, Figure 63 did not follow the trend. This may have been a result of experimental practice derived from the evaporation rate. It is unlikely that the silicon barrier sealed the wells equally due to different amounts of silicon on the rims, and different pressures applied to the cover glass slides to seal them. Different evaporation rates will influence the route taken to attain nucleation and subsequent growth, and evaporation rate may have been such that they were allowed to grow to such a size. DeLucas (1986) and McPherson (1993) also theorise that density driven convection currents can limit the nucleation rate, limit crystal growth and even prevent nucleation if sufficiently significant [57, 58]. Could the evaporation rate be such that the crystal size was limited? The yield is clearly reducing as the concentration decreases shown in Figure 64 and Figure 66 and subsequently Figure 65. The figures also highlight the similar well faceted crystal morphology that is present in all samples, but it was observed that the quality decreased proportionally with concentration. The very small crystals growing, again, could be a result of an unfavourable buffer system, or maybe the precipitants are not ideal, as toward the lower concentrations, namely 4.4 mg/mL and 2.2 mg/mL, the crystal yield does not appear to be representative of the nucleation zone. These results also seem to reveal that Termamyl® 120L can crystallise even at 2.2 mg/mL in this buffer; however, the size of the crystals are not favourable for structural determination. The limitation was that we did not expect this, and did not design the experiment with lower concentrations. From a purification point of view, if the crystals can be separated from the solution, then the high rate of nucleation will certainly be beneficial. With an interest in the yield, the best crystals seem to grow with a 6.6 mg/mL protein concentration. 8.2.11. Screen 11 Again, following the conditions of Suzuki (1990), an Ammonium/ Ammonium Chloride buffer system of pH 10.5 was employed. 1 mL reservoirs contained 2.5 mM EDTA, and 5% v/v of 0.5 M Na2SO4. We sought to investigate the effects of protein concentration with the incorporation of the templates to the hanging drops to determine a “threshold” for the templates, based on the thought that there is likely a minimum concentration of protein required for the templates to be effective. We formulated Termamyl 120L ® solutions of different concentrations diluted with DI water. The concentrations used were 1.1 mg/mL, 2.2 mg/mL, 3.3 mg/mL, 4.4 mg/mL, 5.5 mg/mL, and 6.6 mg/mL in the 15 μL hanging drops. The same concentrations of buffer solution and precipitants were added to the drop. The nano porous templates were additionally incorporated into the screens. We employed Templates A, B, C, and D, with a different size (corresponding to a letter) used per row. A few microns of the template were administered to the drop with a pipette tip. Results of Screen 11

At 6.6 mg/mL, the template that appeared to produce the best crystals was Template C. They are once again very small but they do appear to be larger than the rest and of better quality. The difference is more marked when comparing Figure 68 and Figure 67. It is immediately clear that the crystals are larger and have enhanced crystalline features when comparing Template C, to A. This once again ascertains that Template C is more effective. An interesting observation that must be made however is the seemingly lower yield with templates (Figure 67) than without (Figure 61).

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With a 5.5 mg/mL protein concentration, the nucleation rate appears to have increased from that of 6.6 mg/mL. The crystals appear to manipulate light in a more effective manner that the crystals in Figure 67. Surprisingly, Template A, the smallest pore size, yielded the best results for this concentration; the other templates provided crystals of similar quality to those in Figure 68. Upon comparison of Screen 10 (without templates) and this screen, it is also clear that the templates improve the crystal quality with improved phase separation. This difference is more marked when comparing the 5.5 mg/mL protein concentrations in Figure 64 (without template) and Figure 69 (with template). From a theoretical standpoint, this makes sense. Once the molecules have diffused into the pores, they are immobilised in their lowest energetic orientation increasing their thermodynamic stability. Without templates, there is a chance the molecules will not bond in their most stable state and will thus give rise to defects. This theoretically should give rise to a better crystal lattice and less structural defects, and hence superior crystals.

At lower concentrations, the crystal yield has evidently reduced and the quality has reduced compared to that of the higher concentrations. Nucleation appears to have become more difficult than before. At 4.4 mg/mL protein concentration, the crystal yield appears to have

Figure 67: x 40 magnification, image taken after 24 hours, Template C, 6.6 mg/mL protein concentration

Figure 69: the best crystals that nucleated; image taken after 24 hours, x40 magnification, 5.5 mg/mL protein concentration; Template A

Figure 70: x40 magnification; Template B, 4.4 mg/mL protein concentration; image taken after 24 hours

Figure 68: image taken after 24 hours; x40; 6.6 mg/mL protein concentration, Template A

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reduced by a large amount, but again comparing these results with that of the previous screen (Screen 10) such as in Figure 66, the yield is comparatively greater.

For the 3.3 mg/mL protein crystallisation screen, the Template, D, did not produce any crystals at all. Template A yielded poor results comparatively with smaller crystals and apparent crystal defects. Likewise, Template B cultivated poor quality crystal with respect to the size being seemingly less than 10 microns, as shown in Figure 72. Template C once again produced the best crystals amongst the templates tested. However, it can be observed that the crystal habit is starting to deteriorate with crystal defects visible in the image. Perhaps, the templates themselves are reaching a threshold of effectiveness. A concentration of 3.3 mg/mL protein is nevertheless lower than the proposed limit without templates of 6.6 mg/mL, based on crystal yield and quality. For a 2.2 mg/mL protein concentration, crystals precipitated from solution, but crystal yield reduced greatly. Template D proved to be unsuccessful in the provision of crystals within 24 hours compared to other templates. Using Template A, we witnessed tiny crystals with evident defects, approximately one per square millimetre. One crystal that appeared to resist the trend was that of Figure 73. The crystal is much larger than all other concentrations in this screen, and was larger than those obtained with different template sizes for this concentration were. There appears to be a minor defect, but it appears to be of diffraction quality. It was believed that its precipitation might have been due to experimental practices, as the result was irreproducible. Template C, deemed the most successful thus far, did give a higher crystal yield, however it was not significant with up to two small crystals present per square millimetre on average.

Figure 72: Template B, x40 magnification, images taken after 24 hours, 3.3 mg/mL protein concentration

Figure 71: Crystals that nucleated with Template C, x40 magnification, imaged after 24 hours, 3.3 mg/mL protein concentration

Figure 73: a crystal taken after 24 hours with x40 magnification using Template B; 2.2 mg/mL protein concentration

Figure 74: x40 magnification, imaged after 24 hours, 1.1 mg/mL protein concentration, Template C used

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With a 10% protein concentration, the quality of crystal (when present) was almost void making it unclear whether they were crystals or not. One crystal present in Figure 74 shows what appears to be a crystal with two trigonal (or square-based) pyramids joined at the base. This result, like that of Figure 73, was irreproducible, and only occurred once.

The fact that quality of crystal has deteriorated in terms of size and quality, it was estimated that 3.3 mg/mL protein concentration is the limit of effectiveness to gain good crystals with this buffer system. Tests with other buffers will need to be implemented, but the general finding is that concentrations of 6.6 ± 1.1 mg/mL will yield larger, higher quality crystals, and around 4.4 ± 1.1 mg/mL with the use of templates.

Due to difficulty of gaining reproducible results in line with literature, and good crystals, we opted to try high throughput screening to gain a better understand and have an indication of the type of conditions, which would produce better crystals. However, we also feel that the results are not valueless. For diffraction studies, the crystal are likely too small to analyse, but α-amylase from Bacillus Licheniformis also has uses in bioprocessing, where from a reaction engineering point of view, small crystals will have a higher surface area increasing the rate of reaction. Furthermore, as crystals, they are a pure form of the protein. These two factors should warrant interest from an economic perspective reducing the raw material required and possibly reducing process times. One would however need a means to extract the crystals. 8.2.12. Results of High Throughput Screening Following the general failure to obtain high quality crystals following screening, the methods of high throughput screening were implemented. The results are given for Termamyl® 120L first and Savinase® 16.0L next. An 11 mg/mL protein concentration was used for Termamyl® 120L and 20 mg/mL concentration for Savinase® 16.0L in all experiments. In all cases, the reservoir was 15μL and the droplet was 200 nL in volume. The pictures taken were taken after 5 days, but crystals appeared after 1 day. 8.2.12.1. Termamyl® 120L High throughput Screening Results Screens used included the Hamptons Research Crystal Screen 1&2, Wizard Screen I, II, III, JCSG PlusTM, MemGold, and MorpheusTM. There were 480 experiments implemented per enzyme. This highlights the degree of variation one can have in the conditions, and its effectiveness in finding crystallisation conditions. JCSG-plusTM produced the best results for Termamyl® 120L crystallisation. In Figure 113 located in the Appendix, the conditions of 0.2M Magnesium formate dehydrate seemed to nucleate needle shaped crystals with apparent twinning. Figure 76 shows what appears to be the first instance of suitable conditions for crystallisation. They grew in a 0.1 M Na/K Phosphate Buffer, a pH of 6.2, 25% w/v 1, 2 – propanediol, and 10% v/v glycerol, and appear to have sharp phase boundaries. The crystals however, appear to overlap. An interesting occurrence is the growth of the crystal near the inside of the droplet interface. The crystal in Figure 75 was grown under the conditions of 0.1 M Na/K Phosphate Buffer, a pH of 6.2, 0.2 M NaCl, 50% PEG 200 and shows a diffraction quality crystal. The result also highlights the suitability of a Na/K phosphate buffer to generate diffraction quality crystals. The proof that they are crystals is evident in the birefringence exhibited by the crystals. 8.2.12.2. Savinase® 16.0L High Throughput Screening Results We feel it is debateable which is the best result from the figures below, but based on the quality of the crystals, and their independence in solution (i.e. not overlapping), we feel the JCSG-plusTM by Molecular Dimensions Ltd. The Screen containing 0.1 M Na HEPES buffer at a pH of 7.5, 0.8 M sodium dihydrogen phosphate, and 0.8 M potassium dihydrogen phosphate, produced the best results for Savinase® 16.0L crystallisation shown in Figure

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78. In Figure 112, located in the Appendix, and Figure 77, the conditions produced crystals that appear to overlap with each other with twinning in Figure 112.

8.2.13. Screen 12 For this screen, we administered filtered Termamyl® 120L of concentration 11 mg/mL to the droplets. The droplets were 15 μL in volume. The buffer utilised was 0.1M Na/K Phosphate Buffer, at pH of 6.2, with 25% w/v 1, 2-propandiol, and 10% v/v glycerol from the JCSG-plusTM screen by Molecular Dimensions Ltd. The same buffer system and precipitants were used in the reservoir of 1 mL. We also varied the protein concentrations by diluting the unconcentrated solution with pH matched DI water. The concentrations used were 11, 8.8, 6.6, 5.5, 4.4, and 2.2 mg/mL varied per column respectively.

Results of Screen 12

After a 90-minute period, crystals were discovered indicating the induction time of 90 ± 90 minutes. 11 mg/mL protein concentration proved to be ineffective in nucleating crystals of any size or quality. 8.8 mg/mL proved to be more successful growing the crystal shown in Figure 80. Its crystalline order however is very low despite the strong phase separation. The

Figure 78: Savinase® crystals from cell C5S in 0.1 M Na HEPES buffer at a pH of 7.5, 0.8 M sodium dihydrogen phosphate, and 0.8 M potassium dihydrogen phosphate; JCSG-plusTM by Molecular Dimensions Ltd.

Figure 76: Termamyl® 120L crystals from cell C9A in 0.1M Na/K Phosphate Buffer, a pH of 6.2, 25% w/v 1,2-propandiol, 10% v/v glycerol; JCSG-plusTM by Molecular Dimensions Ltd.

Figure 75: Termamyl® 120L crystals from cell D3A in Na/K Phosphate Buffer, a pH of 6.2, 0.2M NaCl, 50% PEG 200; JCSG-plusTM by Molecular Dimensions Ltd.

Figure 77: A Savinase® crystal from cell F9S in 0.1 M MES buffer at a pH of 6.5, 0.1 M Sodium phosphate monobasic monohydrate, 0.1 M Potassium phosphate monobasic and 2.0 M Sodium chloride; Crystal Screen HTTM manufactured by Hamptons Research.

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phase boundaries are not sharp however. Smaller trigonal crystals also precipitated from solution. As the concentration decreased, the crystal quality, in terms of morphology, was observed to decrease proportionally, yielding small trigonal crystals after 90 minutes. There were instances where crystals, such as that in Figure 79, grew. This was with a 6.6 mg/mL concentration, and given its shape is a likely a planar crystal. How and why the crystal grew to this size is uncertain, but it was not the only occurrence, as can be viewed in the Appendix in Figure 123. Other needles grew in solution specifically for this concentration when the experiment was left for a longer period.

In lower concentrations, crystal growth is observed but with weak phase boundaries, and are at times amorphous. Interestingly, the crystal grew on the inside of the droplet interface and concentrated there at time. The quality was however deemed unsatisfactory in light of the size being less than 20 microns frequently. The crystals were imaged again after three hours. The crystal in Figure 80 did not grow any larger from our judgement. An 11 mg/mL protein concentration only inspired the creation of aggregates. There were no apparent changes in the 8.8 mg/mL experiments, but new crystals were observed in the 6.6 mg/mL concentration experiments, which were of similar form and quality to that in Figure 83. With a 4.4 mg/mL concentration, the yield remained comparable to higher concentrations but crystals appeared to have more structural defects in comparison, for example in Figure 84. A 2.2 mg/mL protein concentration mostly yielded

Figure 80: A very interesting crystal viewed under x40 magnification taken after 90 minutes. 8.8 mg/mL protein concentration

Figure 79: 6.6 mg/mL protein concentration taken after 90 minutes, x40 magnification. This appears to be a planar crystal.

Figure 81: 5.5 mg/mL protein concentration, x40 magnification, imaged after 90 minutes

Figure 82: 4.4 mg/mL protein concentration, x40 magnification, imaged after 90 minutes

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negative results not showing signs of crystal growth, indicating the protein concentration possibly was insufficient to induce nucleation with this buffer.

After 24 hours and after 7 days (which can be viewed in the Appendix in Figure 116 to Figure 144), very interesting shapes formed as shown in Figure 85 and Figure 86 highlighting a multitude of crystal morphologies and sizes displaying what we think is twinning. Examples can be viewed below, and are certainly noteworthy. It appears that they are twinned from a variety of points on the crystal. Seen as the yield is low and are often very large, there could be emphasis on using these crystals for diffraction analysis if pieces or the whole crystal form can be extracted from the droplet.

This crystal in Figure 87 looks flower-like. There also seems to be a portion of the crystal that has grown outside the crystallisation drop, which is not the first instance; another example is noted in the Appendix. Again, it has grown on the edge of the drop. This shall be discussed shortly.

Figure 86: x40 magnification of the upper half of the crystal, 11 mg/mL protein concentration, imaged after 24 hours

Figure 85: x40 magnification of the lower half of the crystal, 11 mg/mL protein concentration, imaged after 24 hours

Figure 84: 4.4 mg/mL protein concentration, x40 magnification and imaged after 3 hours

Figure 83: another trigonal crystal that has nucleated in 6.6 mg/mL protein concentration, imaged after 3 hours, x40 magnification

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The crystals imaged before remained the same size as well as the needle shaped crystal of Figure 79. Figure 83 shows a new crystal that has grown with the 6.6 mg/mL protein concentration. For this buffer without the use of templates, it appeared that higher concentrations, specifically 8.8 and 6.6 mg/mL, produced the best quality crystals with the shortest induction times. The interesting manner of crystal growth after longer periods indicates there is a positive effect on growth attributed to the Na/K Phosphate buffer (pH 6.2). The largest crystals grew with 11, 8.8, and 6.6 mg/mL, with size increasing with increasing concentration. As the concentration reduced further, the size of the crystals reduced greatly with the 5.5 mg/mL protein concentration producing the highest yield. After three days, more large crystals precipitated from solution with interesting structures, which can be viewed in the Appendix along with those after 7 days. Despite their nature, it is clear that there are high quality crystals with powerful phase separation compared to all the previous results, and so if they can be separated manually, they could be useful. What could be investigated is why the crystals appear to twin as they do, and why do they grow so large? In terms of size they are on average at least 50 microns in size with some larger than 100 microns such as Figure 117 or Figure 119.

8.2.14. Screen 13 – Creating a phase diagram using Na/K Buffer (pH 6.2) For this screen, we administered filtered Termamyl 120L® of concentration 11 mg/mL to the droplets. The droplets were 10 μL in volume. The buffer utilised was 0.1M Na/K Phosphate Buffer, at pH of 6.2, with 25% w/v 1, 2-propandiol, and 10% v/v glycerol from the JCSG-plusTM screen by Molecular Dimensions Ltd. The same buffer system and precipitants were used in the reservoir of 1 mL. We implemented this screen to investigate the effects of the buffer concentration in unison with protein concentrations for economic reasons. We have already discovered that the induction time is 90 ± 90 minutes with 24 hours required for high quality crystal. If better quality crystals can be grown with lower concentrations i.e. single crystal unlike those in Figure 86, the results will be of great significance for protein engineering. We opted to formulate a screening matrix for each of three protein concentrations: one screen for 11 mg/mL, one for 8 mg/mL, and one for 5 mg/mL. We further created four buffer concentrations. The stock solution was diluted with pH matched DI water in the following ratios: 1 part buffer, 3 parts DI water (25%); 2 parts buffer, 2 parts DI water (50% buffer); 3 parts buffer, 1 part DI water (75%); and pure stock solution (100% buffer). In the screens, we used a 4x4 array with one column for each buffer concentration. The first row pertained to a control experiment where there was pure buffer and no protein in the droplet. The remaining three wells in the column were replicated experiments for statistical accuracy. There were three well plates, one for each protein concentration. We initially investigated the induction times as per our aims of reducing the induction time. We then imaged the experiments every 90 minutes for 6 hours for induction times, then

Figure 87: a x20 magnified image showing a number of crystals attached to a central point, 8.8 mg/mL protein concentration, imaged after 24 hours

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Figure 90: our depiction of the phase diagram for Na/K Phosphate Buffer (pH 6.2) system. The large blue circles are conditions where precipitates were observed. The green diamonds are conditions where crystals such as those in Figure 92 and Figure 96 were observed. The red crossed-circles are conditions where the solution remained clear after more than seven days. The solid line is our idea of where the supersolubility curve lies, and the dashed line is our idea of where the precipitation zone lies.

again after 24 hours and 7 days to formulate the phase diagram. Based on our observations in regards to the presence of crystals, precipitates or a clear solution, the results can be plotted in a working phase diagram as seen below. We used different icons to indicate the difference in phases and the nature of the precipitates, be they crystalline or not. We have attempted to highlight the region where we observed precipitates with a dashed line. Our rationale for plotting them in their respective conditions is the consistency in the results obtained for each buffer concentration, and thus highly reproducible. For example, in the plate for 5 mg/mL protein, with undiluted buffer, we observed crystals in all the three wells like those in Figure 91.

Figure 89: a small crystal that has appeared after 3 hours. X40, 8 mg/mL protein, 50% buffer

Figure 88: an image of what we believe to be the aggregation of protein molecules before the subsequently reorganise into a crystalline form bearing parallels to two-step theory; x 40, 8 mg/mL protein, 75% buffer concentration

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Figure 92: 75% buffer concentration and 5 mg/ml taken after 24 hours; x40 magnification.

Upon comparison between the different concentrations and conditions, the best crystals that grew were with 5 mg/mL protein full concentrated buffer. Crystals precipitated in solution after 90 minutes like in the previous screen and a further 90 minutes later, began to develop sharp phase boundaries with some crystals displaying this after 90 minutes as shown in Figure 88, and after 3 hours, were apparently crystalline in nature albeit small as in Figure 89. After 24 hours, fully formed crystals like those shown in Figure 92 and Figure 96 for example were present. However, there was an 18 hour period in which these crystals could have formed. For all protein concentrations, without the use of the template our aim of reducing the induction time has been realised. The crystals were imaged after a day where they evidently grew during the 6 and 24 hours they were left to grow. The crystals shown in the images below are those taken after 24 hours. The precursors to these crystals were present after 3 hours ± 90 minutes. For the best crystals however, it is desirable it appears to wait at least 24 hours. They subsequently were imaged after 7 days again to view changes and ascertain or thoughts on the effectiveness of the conditions to induce nucleation and crystal growth. The crystals appear to grow with the two morphologies as shown in Figure 92, Figure 91, and Figure 95 where they are grew simultaneously. Evident features in all images are the clear, sharp phase boundaries, and appear to be diffraction quality with very few defects when present.

Figure 91: 100% buffer concentration, 5 mg/mL; 24 hours; x40 magnification; arrows represent their position

Figure 94: three crystal that grew with 5 mg/mL protein, 75% buffer; x 40. Arrows indicate the locations of the crystals.

Figure 93: 100% buffer, 5mg/mL; x 40 magnification, 24 hours; three trigonal crystals near the droplet boundary

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A further experiment for 2mg/mL could be implemented to further verify the limits of the phase diagram. We feel there may have been potential to crystallise the protein at a lower concentration. If it did not, we would have subsequently attempted to incorporate templates based on the results of Screen 11, where the templates have allowed the crystallisation of Termamyl at 2.2 mg/mL. One could also examine whether the morphology is influenced upon addition of the templates; an experiment we failed to complete due to time constraints. 8.2.15. Screen 14 – Sol Coated Coverslips For this screen, we administered filtered Termamyl® 120L of concentration 11 mg/mL to the droplets. The droplets were 10 μL in volume. The buffer utilised was 0.1M Na/K Phosphate Buffer, at pH of 6.2, with 25% w/v 1, 2-propandiol, and 10% v/v glycerol from the JCSG-plusTM screen by Molecular Dimensions Ltd. The same buffer system and precipitants were used in the reservoir of 1 mL. We implemented this screen to investigate the effects of the coated cover slides that we prepared previously. We opted to formulate a screening matrix for 8 mg/mL and 5 mg/mL, as from the previous screen, appeared to be the most suitable. We further utilised the buffer concentrations that had been deemed to be the most suitable for crystallisation based upon the graphical results of Figure 90: our depiction of the phase diagram for Na/K Phosphate Buffer (pH 6.2) system. The large blue circles are conditions where precipitates were observed. The green diamonds are conditions where crystals such

Figure 95: an image showing the different morphologies that have grown in solution after 24 hours; x 40 magnification; 8 mg/mL; 100% buffer

Figure 96: a crystal imaged after 24 hours; x 20 magnification; 8 mg/mL; 75% buffer

Figure 98: a crystal imaged after 24 hours; x 20 magnification; 8 mg/mL; 100% buffer

Figure 97: 4 crystals imaged after 24 hours; x20 magnification; 8mg/mL; 50% buffer concentration.

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as those in Figure 92 and Figure 96 were observed. The red crossed-circles are conditions where the solution remained clear after more than seven days. The solid line is our idea of where the supersolubility curve lies, and the dashed line is our idea of where the precipitation zone lies.This was achieved by diluting samples of the stock solution with pH matched DI water to the required dilutions which were 50%, 25% and no dilution for 8 mg/mL, and 50% and no dilution for 5 mg/mL. Results of Screen 14 The results or this experiment were deemed unsuccessful. The Sol coated cover slips were treated accordingly as per the methodology, but upon the dispensing of the droplet to the glass cover slip, the droplet was found to highly wet the coated surface, if not wet it completely. As such, we subsequently found that locating the droplet in the microscope to be challenging. Additionally, the hydrothermal treatment creates a textured surface, as shown in Figure 99 and Figure 100, which was the prominent feature in any attempts to image the experiments after every 90 minutes, for 4 hours. We thus sought to obtain a sol formulation, which did not result in a highly wetting surface as this experiment highlighted, but could not complete the experiment due to time constraints. As such, we propose this as further work. If the same situation arises, we suggest investigating the use of the fine powdered template to reduce the protein concentration requirements further. Our results without templates highlight that even 5 mg/mL is sufficient to precipitate diffraction quality crystals, and our result in Screen 11, shows that the templates can reduce the protein concentration further. 8.3. The Significance of Crystal Growth on the Inside of the Interface The observation of crystals forming on the inside of the droplet interface is not an occurrence, which has been witnessed only in Figure 87. The instances are visible in images such as Figure 101 and Figure 102, which are from Screen 10, and have occurrences in other screens of which have been noted previously. They are also evident in results in High Throughput Screening such as Figure 76 and Figure 78. Several reasons we propose could be the cause of this, include the level of mixing in the droplet. Perhaps the mixing in the droplet not being consistent throughout the droplet volume, is possibly creating harsh conditions to sustain the aggregation of protein molecules with seemingly favourable conditions for nucleation near the vapour-liquid-solid point.

Figure 100: the textured surface of the Sol coated cover slides that have been hydrothermally aged. This highlights a different focus to that of Figure 100. x20 magnification.

Figure 99: the textured surface of the Sol coated cover slides that have been hydrothermally aged. This highlights a different focus to that of Figure 100. x20 magnification.

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Figure 101: Screen 10 – Template A; 2.2 mg/mL; x40 magnification, 24 hours

Where the crystal does not appear to adhere to the vapour-liquid-solid point, possibly, mass transfer is quicker in the volume on the inside of the droplet interface reinforcing. This would reinforce the above effect as considering a hemisphere, the volume at r R (around the circumference) is less than the volume at the r=0, and so protein molecules in this locality aggregate quicker. This could additionally be a separate effect where molecules near r=0 must diffuse over greater distances before colliding with another protein molecule compared to at the circumference increasing the induction time. The edge of the drop could be acting like another “surface” due to surface tension. Similar to a hypothetical rectangular pore with two perpendicular walls forming the corners, we proposed that the same effect is occurring but with an acute angle dependant on the contact angle. This “corner”, the vapour-liquid-solid point, would fill quicker than a rectangular pore

and as r R, distance between the solid and vapour-liquid phase boundary decreases. We think that this can easily model a pore with a distribution of sizes explaining occurrences such as Figure 101 and Figure 102. Thus, a protein can easily find an appropriate size. Also from Page and Sear (2006) [91], considering a droplet with a contact angle of 90°. The reduction in free energy barriers to nucleation should be

⁄ [91,

104] as that of a corner. A lower contact angle should theoretically cause reductions in the free energy barrier. If so, a higher wetting could reduce the contact angle and logically the free energy barrier too. Please refer to figure below for a graphical illustration of this point taken from Chernov (2003) [52].

(

) Equation 13

Figure 102: Screen 10 – Template D; 2.2 mg/mL; x40 magnification, 24 hours

Figure 103: this figure highlights the free energy barriers as a function of the contact angle

for heterogeneous nucleation. The contact angle is α.

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Figure 103, taken from Garcia-Ruiz (2003) graphically portrays Equation 13. If the crystallisation drop is completely non-wetting such that the contact angle, α, is 180°, then substitution into Equation 13 shows that . Subsequently, when the contact

angle α is 90°,

, which shows that the free energy for nucleation has halved

due to the heterogeneous nucleant. As the contact angle, α, reduces, the lower the activation energy for nucleation. At α = 0, i.e. the drop completely wets the substrate, the activation energy is also equal to zero. 8.4. Experimental Errors We believe there could also have been errors in the buffer preparation. There is an associated error with electronic weighing scales, and so in the preparation, the ionic strengths of the buffer may have been slightly inaccurate. This would have been more significant if precipitants or salt additives are included, as they can have a profound effect on the precipitation of a protein crystal from supersaturated solutions. We also recognize that there were likely errors in the pH calibration of the buffer solutions where calibration was lengthy, and often the meter would not display the correct pH despite calibration prompting further recalibration. Once the meter was deemed to be “calibrated”, the pH balancing process was highly difficult due to sensitivity causing over and undershoots of the required pH. This prompted the addition of small amounts of NaOH or HCl to adjust the pH. We believe this may have been significant as an incorrect pH will certainly affect crystallisation. Cox and Weber (1987) note that solutions were sensitive to pH [60] in their report on automated screening, and McPherson comments that screening with pH can be difficult given that a difference of less than 0.5 can be the difference between a large, single crystal, precipitates and micro-crystals [4]. Further, what effect would the excess and have on crystallisation? They may have been responsible for the formation of precipitates. One must also examine and take into account possible contamination. Images such as that in Figure 134 and Figure 136 located in the Appendix highlight instances of contamination in the droplets. Upon consultation, they are believed to be hairs. As a positive however, they do show the power of heterogeneous nucleation given that for those conditions, they were the only crystals observed in the droplet. It is possible that in cleaning the cover glass, the DI water may have gradually increased its acetone concentration, creating a harsh environment in the crystallisation droplet due to residual ions remaining on the glass. In analysis of our results, we believe further areas in the methodology that may have led to experimental errors. The silicon gel is the most obvious example. All though an applicator is utilised to apply the silicon gel to the rims of the wells, they amount of gel on each well can vary. Additionally, the same amount of pressure is certainly not going to be applied to the cover slips to seal the wells. As such, this can lead to varying rates of evaporation, which from a phase diagram is significant. Depending on the rate of evaporation, the time taken to reach the nucleation zone is altered affecting the induction times, assuming the conditions are suitable. Further, if evaporation takes place too quickly, literature and books suggest that density driven convection currents within the drop can hinder nucleation and crystal growth [54, 57, 58]. 9. Conclusion We carried out this investigation to investigate the effects of a nano-engineered template as a nucleant. We carried this out with an initial screen to investigate the effects of various screening parameters in unison and in combination on the induction time and morphology of the crystals.

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We initially measured the Stokes radius of the enzymes. For Termamyl® 120L, it was found to be 7.6 ± 0.1 nm. For Savinase(R) 16.0L, the data was deemed unusable given persistent inconsistencies in the data, and the magnitude of the size being in the range of 30 nm at its lowest value. This is certainly capacity to re-evaluate this. Prior to the use of high throughput screening, we found that, as literature suggests, for the buffer system we utilised, the crystals were significantly sensitive to the pH with a narrow range being effective in precipitating a large crystal and reducing the induction time for Savinase® 16.0L. For Savinase® 16.0L, we also found that the addition of PMSF to the screens increased crystal size and comparatively reduced induction times as a result of reducing the activity of Savinase® 16.0L. We additionally noted the significant decrease in induction times with the incorporation of templates with an increase in size and quality with often, sharper phase boundaries, and more faceted crystals for Termamyl in the Ammonium/Ammonium chloride buffer. The template discovered to be the most effective overall for Savinase, was the template designated C, which has an intermediate pore size in comparison to the other templates. The lowest induction we attained was 3 ± 1 days with the incorporation of templates, with the potential to be reduced further given our success with the buffer system obtained from High Throughput Screening for Termamyl® 120L. For Termamyl®120L, we found that the enzyme was easier to crystallise than Savinase with an induction time of 48 ± 24 hours to witness crystals in solution. We found that reducing the ionic strength of the buffer system improved the diffraction quality of the crystals but still witnessed the precipitation of highly faceted crystals approximately 5 microns in size. Upon investigations with concentration, we find that to maintain yield and morphology of the crystals, the minimum concentration that could be crystallised was 6.6 mg/mL, although 2.2 mg/mL was feasible by sacrificing yield and diffraction quality. With the addition of templates, we found that their effects allowed the minimum concentration that could crystallise to reduce to 3.3 mg/mL. Again, a lower concentration – in this case 1.1 mg/mL – showed potential to be crystallised though infrequently. With the incorporation of templates, we observed induction times of 90 ± 90 minutes, and once more, Template C proved to be the most effective. However, given the respective molecular weights of the proteins, it is unusual why Template C is effective for both proteins. Possibly a definitive measurement of the Stokes radius of Savinase may help point to an answer. The change of the buffer to that obtained with High Throughput Screening, allowed the precipitation of diffraction quality crystals rarely possessing defects ranging from 15 to 40 microns in size. We also discovered that the buffer facilitates the precipitation of what we believe are twinned crystals, and crystals that where often larger than 100 microns after 3 ± 2 days. Without the incorporation of templates, we believe we sufficient evidence to show crystal growth is more effective with approximately 5 mg/mL for the Na/K phosphate buffer system (pH 6.2) and its precipitants; one of the best conditions from High Throughput Screening. The crystals obtained appear to be of diffraction quality given their sharp phase boundaries, clarity with no twinning and few occurrences of defects, and relatively large size compared to every other experiment we had carried out with a size of at least 50 microns on average such as in Figure 98. Subsequent growth was also witnessed yielding crystals that appear to be twinned in several cases. However, they are also at times large enough to be used for X-ray diffraction such as that in Figure 119. 10. Future work Concerning the Stokes radius, we believe further work could be made to include size exclusion chromatography (SEC). One effect that is not considered in DLS, is the effect of folding of the protein, which will affect the apparent Stokes radius of the molecule. SEC is a method, which bears the potential to distinguish between the folded and unfolded forms of the enzyme and so a more accurate representation of the Stokes radius.

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We further did not obtain reliable results for the Stokes radius for Savinase® 16.0L and so it is not known definitively why the template designated “C” was apparently the most effective in inducing nucleation. We feel that the answer could lie in the template itself. The zeta potential is one property. As the template is deployed as a fine powder with a pipette tip, by changing the pH, the potential can be influenced, affecting the proportions of attraction and repulsion between the protein and the templates. Further investigations could be made into the zeta-potential of the proteins so that buffers can be formulated to match the pH that enhances nucleation by promoting attractive forces to an extent where crystals quality is improved. Further investigations could be made into the incubation of the crystals at different temperatures. Despite this adding another crystallisation parameter, the temperature will change the rate of mass transfer and heat diffusion, and thus has the potential to influence the rate of nucleation, and the rate of growth [126]. Investigations could be made into the effects of the density driven convection currents. Their existence is noted in Bergfors (2009) [54] and Luft (1994) [51] and they have been theorised to have adverse effects on nucleation. One could investigate the size of these forces and possibly determine how they affect nucleation with Atomic Force Microscopy for example. Are they limiting the size of the crystal? Are they ceasing nucleation? To what extent? Perhaps a model protein could be synthesised as Zhang (2006) [79] did with a polymer, and if possible utilise a radioactive tracer to model mass transfer with the droplet. X-ray diffraction studies could possibly be undertaken to determine the morphology of the crystals that we grew. The crystal lattice creates a diffraction pattern and from this the lattice structure, and hence morphology can be ascertained. Further, this technique can be used to judge the diffraction quality of the crystals. The technique can ascertain mean bond lengths to a resolution of Angstroms (Å) and bond angles to an accuracy of a tenth of a degree.

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References 1. Chayen, N.E., et al., An automated system for micro-batch protein crystallization and

screening. Journal of Applied Crystallography, 1990. 23(4): p. 297-302. 2. How Insulin Crystals Grow. http://www.medicalnewstoday.com/releases/3727.php. 3. Shenoy, e.a., Biotechnology and Bioengineering, 2001. 73: p. 358-369. 4. McPherson, A., Current approaches to macromolecular crystallization. Eur J

Biochem. , 1990. 189(1): p. 1-23. 5. Saridakis, E. and N.E. Chayen, Towards a ‘universal’ nucleant for protein

crystallization. Trends in Biotechnology, 2009. 27(2): p. 99-106. 6. Erdemir, D., A.Y. Lee, and A.S. Myerson, Nucleation of Crystals from Solution:

Classical and Two-Step Models. Accounts of Chemical Research, 2009. 42(5): p. 621-629.

7. Frenkel, D., Physical chemistry: Seeds of phase change. Nature, 2006. 443(7112): p. 641-641.

8. Vekilov, P.G., Nucleation. Crystal Growth & Design, 2010. 10(12): p. 5007-5019. 9. Crystallization. http://www.cheresources.com/cryst.shtml. 10. Classical Nucleation Theory.

http://marie.ph.surrey.ac.uk/~phs1rs/rodnuc/node1.html. 11. Garc a-Ruiz, J.M., Nucleation of protein crystals. Journal of Structural Biology, 2003.

142(1): p. 22-31. 12. Boistelle, R. and J.P. Astier, Crystallization mechanisms in solution. Journal of

Crystal Growth, 1988. 90(1-3): p. 14-30. 13. Sear, D.R.P., Classical nucleation theory.

http://marie.ph.surrey.ac.uk/~phs1rs/rodnuc/node1.html. 14. Yau, S.T. and P.G. Vekilov, Direct Observation of Nucleus Structure and Nucleation

Pathways in Apoferritin Crystallization. Journal of the American Chemical Society, 2001. 123(6): p. 1080-1089.

15. Vekilov, P.G., Dense Liquid Precursor for the Nucleation of Ordered Solid Phases from Solution. Crystal Growth & Design, 2004. 4(4): p. 671-685.

16. Oxtoby, D.W., Crystal nucleation in simple and complex fluids. Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 2003. 361(1804): p. 419-428.

17. Vekilov, P.G., What Determines the Rate of Growth of Crystals from Solution? Crystal Growth & Design, 2007. 7(12): p. 2796-2810.

18. Cubillas, P., Synthesis Mechanism: Crystal Growth and Nucleation. http://www.wiley-vch.de/books/sample/352732514X_c01.pdf.

19. Crystallization Theory. http://www.xtal.tsinghua.edu.cn/group5/web/material/Protein%20Crystallization%20Theory%20and%20Practice.htm.

20. Chernov, A.A., Protein crystals and their growth. Journal of Structural Biology, 2003(142): p. 3-21.

21. Chayen, N.E. and E. Saridakis, Protein crystallization: from purified protein to diffraction-quality crystal. Nat Meth, 2008. 5(2): p. 147-153.

22. McPherson, A., Introduction to protein crystallization. Methods, 2004. 34(3): p. 254-265.

23. Herbots, I., et al., Enzymes, 4. Non-food Application, in Ullmann's Encyclopedia of Industrial Chemistry2000, Wiley-VCH Verlag GmbH & Co. KGaA.

24. Fitter, J. and S. Haber-Pohlmeier, Structural Stability and Unfolding Properties of Thermostable Bacterial α-Amylases:  A Comparative Study of Homologous Enzymes. Biochemistry, 2004. 43(30): p. 9589-9599.

25. Luis David Alcaraz, G.M.H., Luis E Eguiarte, Valeria Souza, Luis Herrera-Estrella and Gabriela Olmedo, Understanding the evolutionary relationships and major traits of Bacillus through comparative genomics. BMC Genomics, 2010. 11(332).

Page | 74

26. M. Lyndsay REMEROWSKI', H.A.M.P., Cornelis W. HILBERS' and Frank J. M. VAN DE VEN', Backbone dynamics of the 269-residue protease Savinase determined from N-NMR relaxation measurements. European Journal of Biochemistry, 1996. 235(3): p. 629-640.

27. Betzel, C., et al., Crystal structure of the alkaline proteinase Savinase™ from Bacillus lentus at 1.4 Å resolution. Journal of Molecular Biology, 1992. 223(2): p. 427-445.

28. Russell A Judge, E.L.F., Michael R Johns, Marc L Pusey, Edward T White, The Feasibility of Bulk Crystallization as an Industrial Purification and Production Technique for Proteins 1998.

29. Chandrika P, G., Crosslinking of enzymes for improved stability and performance. Current Opinion in Biotechnology, 1999. 10(4): p. 331-335.

30. Vivares, D., et al., Polymorphism of Urate Oxidase in PEG Solutions. Crystal Growth & Design, 2005. 6(1): p. 287-292.

31. Talanquer, V. and D. Oxtoby, Crystal nucleation in the presence of a metastable critical point. J. Chem. Phys. , 1998. 109(223).

32. Shore, J.D.P., D.; Shnidman, Y., Simulations of the Nucleation of AgBr from Solution. J. Chem. Phys., 2000. 113: p. 6276–6284.

33. Haas, C., The Interface between a Protein Crystal and an Aqueous Solution and Its Effects on Nucleation and Crystal Growth. The Journal of Physical Chemistry B, 1999. 104(2): p. 368-377.

34. Schmelzer, J.W.P.G., A. R.; Fokin, V. M. , Dynamics of First-Order Phase Transitions in Multicomponent Systems. A New Theoretical Approach. . J. Colloid Interface Sci., 2004(272): p. 109–133.

35. Georgalis, Y., et al., Protein crystallization screening through scattering techniques. Advances in Colloid and Interface Science, 1995. 58(1): p. 57-86.

36. Schüth, F., Nucleation and crystallization of solids from solution. Current Opinion in Solid State and Materials Science, 2001. 5(5): p. 389-395.

37. Bolanos-Garcia, V.M. and N.E. Chayen, New directions in conventional methods of protein crystallization. Progress in Biophysics and Molecular Biology, 2009. 101(1-3): p. 3-12.

38. Chayen, N., Comparative Studies of Protein Crystallization by Vapour-Diffusion and Microbatch Techniques. Acta Crystallographica Section D, 1998. 54(1): p. 8-15.

39. D'Arcy, A., et al., A novel approach to crystallising proteins under oil. Journal of Crystal Growth, 1996. 168(1-4): p. 175-180.

40. McPherson, A., Crystallization of Biological Macromolecules1999, New York: Cold Spring Harbor Laboratory Press. 586.

41. Moreno, A., E. Saridakis, and N.E. Chayen, Combination of oils and gels for enhancing the growth of protein crystals. Journal of Applied Crystallography, 2002. 35(1): p. 140-142.

42. Ng, J.D., J.A. Gavira, and J.M. Garc a-Ru z, Protein crystallization by capillary counterdiffusion for applied crystallographic structure determination. Journal of Structural Biology, 2003. 142(1): p. 218-231.

43. Hansen, C. and S.R. Quake, Microfluidics in structural biology: smaller, faster… better. Current Opinion in Structural Biology, 2003. 13(5): p. 538-544.

44. Sommer, M.O.A. and S. Larsen, Crystallizing proteins on the basis of their precipitation diagram determined using a microfluidic formulator. Journal of Synchrotron Radiation, 2005. 12(6): p. 779-785.

45. Ismagilov, L.L.a.R.F., Protein Crystallization Using Microfluidic Technologies Based on Valves, Droplets, and SlipChip. Annual Review of Biophysics, 2010. 39: p. 139-158.

46. Zheng, B., C.J. Gerdts, and R.F. Ismagilov, Using nanoliter plugs in microfluidics to facilitate and understand protein crystallization. Current Opinion in Structural Biology, 2005. 15(5): p. 548-555.

Page | 75

47. Luft, J.R., et al., The Rate of Water Equilibration in Vapor-Diffusion Crystallizations: Dependence on the Distance from the Droplet to the Reservoir. Acta Crystallographica Section D, 1996. 52(6): p. 1098-1106.

48. http://www.springerimages.com/Images/LifeSciences/1-10.1007_978-1-60761-762-4_5-11.

49. The Phase Diagram in Protein Crystallization. http://www.p212121.com/2009/11/15/the-phase-diagram-in-protein-crystallization/.

50. Sawaya, h.p.m.u.e.s.m.d.C.t.h.M.R., Hanging drop vapour diffusion method of crystallization explained

51. Luft, J.R., et al., A macromolecular crystallization procedure employing diffusion cells of varying depths as reservoirs to tailor the time course of equilibration in hanging- and sitting-drop vapor-diffusion and microdialysis experiments. Journal of Applied Crystallography, 1994. 27(4): p. 443-452.

52. Chernov, A.A., Protein crystals and their growth. Journal of Structural Biology, 2003. 142: p. 3–21.

53. Protein Crystallisation. http://www.bio.davidson.edu/Courses/Molbio/MolStudents/spring2003/Kogoy/protein.html.

54. Bergfors, T.M., Protein Crystallization. 2 ed2009: International University Line. 55. Fowlis, W.W., et al., Experimental and theoretical analysis of the rate of solvent

equilibration in the hanging drop method of protein crystal growth. Journal of Crystal Growth, 1988. 90(1-3): p. 117-129.

56. Marangoni convection and protein crystallisation. www.descsite.nl/Publications/Thesis/Molenkamp/molenkamp_c5.pdf.

57. DeLucas, L.J., et al., Preliminary investigations of protein crystal growth using the space shuttle. Journal of Crystal Growth, 1986. 76(3): p. 681-693.

58. McPherson, A., Effects of a microgravity environment on the crystallization of biological macromolecules. Microgravity Sci. Technol. VI/2, , 1993: p. 101-109.

59. Rupp, B., High Throughput Protein Crystallisation. http://www.ruppweb.org/Xray/tutorial/High_Throughput_EMBL_full.htm#_Toc490635209, 2000.

60. Cox, M.J. and P.C. Weber, Experiments with automated protein crystallization. Journal of Applied Crystallography, 1987. 20(5): p. 366-373.

61. Cox, M.J. and P.C. Weber, An investigation of protein crystallization parameters using successive automated grid searches (SAGS). Journal of Crystal Growth, 1988. 90(1-3): p. 318-324.

62. Kelders, H.A., et al., Automated protein crystallization and a new crystal form of a subtilisin:eglin complex. Protein Engineering, 1987. 1(4): p. 301-303.

63. Ward, K.B., M.A. Perozzo, and W.M. Zuk, Automatic preparation of protein crystals using laboratory robotics and automated visual inspection. Journal of Crystal Growth, 1988. 90(1-3): p. 325-339.

64. Pusey, M.L.e.a. and W.T. Zhi-Jie Liu, Jeremy Praissman, Dawei Lin, Bi-Cheng Wang, Jose´ A. Gavira, Joseph D. Ng,, Life in the fast lane for protein crystallization and X-ray crystallography. Progress in Biophysics and Molecular Biology, 2005. 88: p. 359–386.

65. Stevens, R.C., High-throughput protein crystallization. Current Opinion in Structural Biology, 2000. 10(5): p. 558-563.

66. Brown, J., et al., A procedure for setting up high-throughput nanolitre crystallization experiments. II. Crystallization results. Journal of Applied Crystallography, 2003. 36(2): p. 315-318.

67. DeLucas, L.J., et al., Efficient protein crystallization. Journal of Structural Biology, 2003. 142(1): p. 188-206.

68. Bodenstaff, E.R., et al., The prospects of protein nanocrystallography. Acta Crystallographica Section D, 2002. 58(11): p. 1901-1906.

Page | 76

69. Yeh, J., A manual nanoscale method for protein crystallization. Acta Crystallographica Section D, 2003. 59(8): p. 1408-1413.

70. Jancarik, J. and S.-H. Kim, Sparse matrix sampling: a screening method for crystallization of proteins. Journal of Applied Crystallography, 1991. 24(4): p. 409-411.

71. Li, F., Automated high throughput protein crystallization screening at nanoliter scale and protein structural study on lactate dehydrogenase, 2006, Iowa State University: Ames, Iowa.

72. Advantages of the TOPAZ Approach for Protein Crystallisation. http://www.fluidigm.com/home/fluidigm/docs/White_Paper_Advantages_of_TOPAZ_for_Protein_Crystallization.pdf.

73. Garcia-Ruiz, J.M., et al., Granada Crystallisation Box: a new device for protein crystallisation by counter-diffusion techniques. Acta Crystallographica Section D, 2002. 58(10 Part 1): p. 1638-1642.

74. Snell, E.H.a.H., John R, Macromolecular crystallization in microgravity. Rep. Prog. Phys., 2005. 68(799).

75. M. C. Heijna, P.W.P., K. Tsukamoto, W. J. de Grip, P. C. Christianen et al., Magnetically controlled gravity for protein crystal growth. Appl. Phys. Lett. , 2007. 90(264105).

76. Chayen, N., A novel technique to control the rate of vapour diffusion, giving larger protein crystals. Journal of Applied Crystallography, 1997. 30(2): p. 198-202.

77. CUDNEY, P., WEISGRABER, NEWHOUSE AND MCPHERSON, Screening and Optimization Strategies for Macromolecular Crystal Growth. Acta Crystallographica Section D, 1994: p. 414-423.

78. Chen, W. and J.C. Berg, The effect of polyelectrolyte dosage on floc formation in protein precipitation by polyelectrolytes. Chemical Engineering Science, 1993. 48(10): p. 1775-1784.

79. Zhang, Y. and P.S. Cremer, Interactions between macromolecules and ions: the Hofmeister series. Current Opinion in Chemical Biology, 2006. 10(6): p. 658-663.

80. Duinhoven, S., et al., Driving Forces for Enzyme Adsorption at Solid-Liquid Interfaces: 2. The Fungal Lipase Lipolase. Journal of Colloid and Interface Science, 1995. 170(2): p. 351-357.

81. Yamanaka, M., et al., Optimization of salt concentration in PEG-based crystallization solutions. Journal of Synchrotron Radiation, 2011. 18(1): p. 84-87.

82. Nanev, C.N., On the Slow Kinetics of Protein Crystallization. Crystal Growth & Design, 2007. 7(8): p. 1533-1540.

83. Takehara, M., et al., Use of layer silicate for protein crystallization: Effects of Micromica and chlorite powders in hanging drops. Analytical Biochemistry, 2008. 373(2): p. 322-329.

84. Thakur, A.S., et al., Improved Success of Sparse Matrix Protein Crystallization Screening with Heterogeneous Nucleating Agents. PLoS ONE, 2007. 2(10): p. e1091.

85. Chayen, N.E., et al., Porous silicon: an effective nucleation-inducing material for protein crystallization. Journal of Molecular Biology, 2001. 312(4): p. 591-595.

86. NE Chayen, Emmanuel Saridakis, and R.P. Sear, Experiment and theory for heterogeneous nucleation of protein crystals in a porous medium. Proc. Natl. Acad. Sci. U. S. A., 2006. 103: p. 597–601.

87. Nanev, C.N. and D. Tsekova, Heterogeneous Nucleation of Hen-Egg-White Lysozyme — Molecular Approach. Crystal Research and Technology, 2000. 35(2): p. 189-195.

88. Curcio, E., G.D. Profio, and E. Drioli, A new membrane-based crystallization technique: tests on lysozyme. Journal of Crystal Growth, 2003. 247(1-2): p. 166-176.

89. Profio, G.D., et al., Membrane crystallization of lysozyme: kinetic aspects. Journal of Crystal Growth, 2003. 257(3-4): p. 359-369.

Page | 77

90. Zhang, X., et al., The study of continuous membrane crystallization on lysozyme. Desalination, 2008. 219(1-3): p. 101-117.

91. Page, A.J.a.S., Richard P., Heterogeneous Nucleation in and out of Pores. 2006. 92. Liu, Y.-X., et al., Influence of the Roughness, Topography, and Physicochemical

Properties of Chemically Modified Surfaces on the Heterogeneous Nucleation of Protein Crystals. The Journal of Physical Chemistry B, 2007. 111(50): p. 13971-13978.

93. Rong, L., et al., Protein crystallization by using porous glass substrate. Journal of Synchrotron Radiation, 2004. 11(1): p. 27-29.

94. Bergfors, T., Seeds to crystals. Journal of Structural Biology, 2003. 142(1): p. 66-76. 95. D'Arcy, A., A. Mac Sweeney, and A. Haber, Using natural seeding material to

generate nucleation in protein crystallization experiments. Acta Crystallographica Section D, 2003. 59(7): p. 1343-1346.

96. Georgieva, D.G., et al., Heterogeneous nucleation of three-dimensional protein nanocrystals. Acta Crystallographica Section D, 2007. 63(5): p. 564-570.

97. Tang, L., et al., Effects of the silanized mica surface on protein crystallization. Acta Crystallographica Section D, 2005. 61(1): p. 53-59.

98. Tosi, G., et al., Crystallization of proteins on functionalized surfaces. Acta Crystallographica Section D, 2008. 64(10): p. 1054-1061.

99. Sugahara, M., et al., Nucleant-mediated protein crystallization with the application of microporous synthetic zeolites. Acta Crystallographica Section D, 2008. 64(6): p. 686-695.

100. Ataka, M., Protein crystal growth: An approach based on phase diagram determination. Phase Transitions, 1993. 45(2-3): p. 205-219.

101. Feher, G.K., Z., Nucleation and growth of protein crystals: general principles and assays. Methods Enzymol., 1985(114): p. 77-112.

102. Sear, R.P., Heterogeneous and Homogeneous Nucleation Compared:  Rapid Nucleation on Microscopic Impurities. The Journal of Physical Chemistry B, 2006. 110(10): p. 4985-4989.

103. Debenedetti, P.G., Metastable Liquids1996: Princeton University Press: Princeton. 104. Sear, R.P., On the Interpretation of Quantitative Experimental Data on Nucleation

Rates Using Classical Nucleation Theory. The Journal of Physical Chemistry B, 2006. 110(43): p. 21944-21949.

105. Henschel, A., P. Huber, and K. Knorr, Crystallization of medium-length 1-alcohols in mesoporous silicon: An x-ray diffraction study. Physical Review E, 2008. 77(4): p. 042602.

106. Cacciuto, A., S. Auer, and D. Frenkel, Onset of heterogeneous crystal nucleation in colloidal suspensions. Nature, 2004. 428(6981): p. 404-406.

107. Striemer, C.C., et al., Charge- and size-based separation of macromolecules using ultrathin silicon membranes. Nature, 2007. 445(7129): p. 749-753.

108. Dynamic Light Scattering - Introduction. http://mxp.physics.umn.edu/s05/projects/s05lightscattering/introduction.html.

109. ViscotekEuropeLimited, Dynamic Light Scattering - an Important Tool for Protein Crystallography and Nanotechnology. http://www.chemeurope.com/en/whitepapers/61632/dynamic-light-scattering-an-important-tool-for-protein-crystallography-and-nanotechnology.html.

110. Dictionary of nanotechnology - Hydrodynamic diameter. http://www.nanodic.com/Nanomaterial/Hydrodynamic_diameter.htm.

111. Laser Light Scattering. http://www.ap-lab.com/light_scattering.htm. 112. Protein Characterization Using Dynamic & Static Light Scattering Techniques From

Malvern Instruments - Shape Estimates. http://www.azonano.com/article.aspx?ArticleID=1203.

113. Coulter N4 Sub Micron Particle Sizer Manual, B.C., 1995. 114. ULF NOBBMANN, M.C., BRENDAN FISH, PAUL VARLEY, CHRIS GEE,

SANDRINE MULOT, JUNTAO CHEN, LIANG ZHOU, YANLING LU, FEI SHENG,

Page | 78

JUNMING YI AND STEPHEN E. HARDING, Dynamic light scattering as a relative tool for assessing the molecular integrity and stability of monoclonal antibodies. Biotechnology and Genetic Engineering Reviews, 2007. Vol. 24: p. 117-128.

115. Sigma-Aldrich. http://www.sigmaaldrich.com/united-kingdom.html. 116. C. Accuracy and Estimation.

http://www.scidiv.bcc.ctc.edu/Physics/Measure%26sigfigs/C-Uncert-Estimate.html. 117. Washing Up Liquids - Savona® D60 12014.

http://www.premiereproducts.co.uk/chemicals/catering?page=shop.product_details&flypage=flypage.tpl&product_id=158&category_id=71&vmcchk=1.

118. X Ray Crystallisation Facility. http://www3.imperial.ac.uk/xraycrystallography/crystn. 119. Galkin, O. and P.G. Vekilov, Direct Determination of the Nucleation Rates of Protein

Crystals. The Journal of Physical Chemistry B, 1999. 103(49): p. 10965-10971. 120. Techniques, H.A., Dynamic Light Scattering.

http://www.horiba.com/us/en/scientific/products/particle-characterization/technology/how-this-technique-works/.

121. Betzel, C., et al., Crystallization and preliminary X-ray diffraction studies of an alkaline protease from Bacillus lentus. Journal of Molecular Biology, 1988. 204(3): p. 803-804.

122. Duinhoven, S., et al., Driving Forces for Enzyme Adsorption at Solid-Liquid Interfaces: 1. The Serine Protease Savinase. Journal of Colloid and Interface Science, 1995. 170(2): p. 340-350.

123. Protein Applications, Webinar: Characterizing Nanoparticles used in Bio Applications. http://www.horiba.com/scientific/products/particle-characterization/applications/proteins/.

124. Stewart, P.S., Harvesting Crystals from Microbatch for Cryocrystallography. http://douglas.co.uk/rep2.htm.

125. Suzuki, A., et al., Crystallization and Preliminary Crystallographic Study of Bacterial α-Amylases. Journal of Biochemistry, 1990. 108(3): p. 379-381.

126. Saridakis, E., Temperature in macromolecular crystallisation. http://www.centeo.com/_fileupload/Temperature%20Control%20in%20PXTL.pdf.

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APPENDIX

Table 1: Results of Stokes Radius Measurements

Screen 2

Sample

Name

Termamyl

120L

220nm filt.

Z-

Average

(r.nm)

CONTIN

Peaks

Diffusion

Coefficient

(µ²/s) PdI

PdI

Width (r.nm)

100% v/v 22.06 56.6 11.2 0.247 10.95

100% v/v 22.12 56.8 11.1 0.245 10.95

100% v/v 21.88 56.1 11.2 0.244 10.8

50% v/v 10.7 27.1 23 0.222 5.038

50% v/v 10.76 27.2 22.9 0.218 5.026

50% v/v 10.83 27.3 22.7 0.219 5.067

25% v/v 8.666 22.3 1.46 28.4 0.242 4.266

25% v/v 8.633 22 28.5 0.237 4.202

25% v/v 8.697 22.5 28.3 0.242 4.279

12.50% v/v 7.756 19.4 1.27 4410 31.7 0.314 4.344

12.50% v/v 7.759 20.3 1.44 4490 31.7 0.32 4.392

12.50% v/v 8.995 17.7 1.22 5430 27.4 0.205 4.077

6.75% v/v 7.566 18.5 3010 32.5 0.383 4.685

6.75% v/v 7.763 18.5 2760 1.04 31.7 0.33 4.458

6.75% v/v 7.618 18.7 2340 1.89 32.3 0.393 4.775

Figure 104: taken after 8 days to verify the crystal yield in solution. X40 magnification

Figure 105: x40 magnification image of small crystal taken after 6 days

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Screen 3

Screen 5

Screen 6

Figure 106: A x40 magnification image of what we believe is an aggregate taken after 3 days; Template B

Figure 107: A precipitate that grew with the incorporation of Template A. It may also be a type of needle. x40 magnification taken after 6 days

Figure 108: A protein aggregate that formed after 6 days taken with x 40 magnification. PEG 4000 was the precipitant.

Figure 109: x40 magnification image showing nothing precipitating after 6 days. It remained like this henceforth

Figure 110: x40 magnification; Template C, taken after 3 days, without PMSF

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Screen 8

Results of High throughput Screening

Screen 11

Screen 11

Figure 111: another instance that highlights the excess of nucleation occurring in the drop;

x40 mag, 48 hours; NO Template

Figure 113: Termamyl 120L ® crystals from cell D8A in 0.2M Magnesium formate dehydrate; Crystal Screen HTTM manufactured by Hamptons Research.

Figure 112: Savinase crystals from cell C11S in 0.1 M Na HEPES buffer at a pH of 7.5, 0.8 M Na phosphate monobasic monohydrate, 0.8 M K phosphate monobasic; Crystal Screen 2 HTTM; Hamptons Research.

Figure 114: 6.6 mg/mL protein concentration in the hanging drop, x 20 magnification, imaged after 24 hours

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Figure 115: x 20; 11 mg/mL; x20 magnification, imaged after 7 days

Figure 116: x 20; 11 mg/mL; x20 magnification, imaged after 7 days

Figure 117: 11 mg/mL; x20 magnification, imaged after 7 days

Figure 118: x 20; 11 mg/mL; x20

magnification, imaged after 7 days

Figure 119: x 20; 8.8 mg/mL; x20 magnification, imaged after 7 days; an extremely large crystal

Figure 120: x 20; 8.8 mg/mL; x20 magnification, imaged after 7 days

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Figure 123: x 20; 6.6 mg/mL; x20 magnification, imaged after 3 days; a needle crystal

Figure 125: x 20; 6.6 mg/mL; x20 magnification, imaged after 3 days; a needle crystal

Figure 122: 8 x 20; 8.8 mg/mL; x20 magnification, imaged after 7 days

Figure 126: x 20; 6.6 mg/mL; x20

magnification, imaged after 7 days

Figure 121: x 20; 8.8 mg/mL; x20 magnification, imaged after 3 days

Figure 124: 80%; x 20; 8.8 mg/mL; x20 magnification, imaged after 3 days

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Figure 129: x 20; 5.5 mg/mL; x40 magnification, imaged after 3 days

Figure 130: x 20; 5.5 mg/mL; x20 magnification, imaged after 3 days

Figure 131: x 20; 5.5 mg/mL; x40 magnification, imaged after 7 days

Figure 128: x 20; 6.6 mg/mL; x20 magnification, imaged after 7 days

Figure 127: x 20; 5.5 mg/mL; x20 magnification, imaged after 7 days

Figure 132: x 20; 5.5 mg/mL; x40 magnification, imaged after 24 hours

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Figure 135: Imaged after 7 days, 4.4

mg/mL; x20 magnification

Figure 133: 4.4 mg/mL protein concentration; x 40 magnification; taken after 24 hours; growth on a hair

Figure 134: 4.4 mg/mL protein concentration; x 20 magnification; taken after 24 hours; growth on a hair

Figure 136: Imaged after 7 days, 4.4

mg/mL; x20 magnification

Figure 138: Imaged after 7 days, 4.4 mg/mL; x20 magnification

Figure 137: Imaged after 7 days, 4.4 mg/mL; x20 magnification; growth on a hair

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Figure 143: Imaged after 7 days, 2.2

mg/mL; x20 magnification

Screen 13

Figure 142: crystals growing from a central region where other hexagonal looking crystals that are forming, x40 magnification, imaged after 3 days, 20%

Figure 141: Imaged after 3 days and shows evident defects; 2.2 mg/mL, x 40 magnification

Figure 139: Imaged after 3 days, 2.2 mg/mL; x40 magnification, nucleated near droplet boundary

Figure 140: Imaged after 24 hours, 2.2 mg/mL; x20 magnification; nucleated near droplet boundary

Figure 144: Imaged after 7 days, 2.2

mg/mL; x20 magnification

Page | 87

Figure 150: 5 mg/mL protein; 100% buffer concentration; x20 magnification; imaged after 7 days

Figure 146: 5 mg/mL protein; 75% buffer concentration; x20 magnification; imaged after 7 days

Figure 145: 4.4 mg/mL protein concentration, x40 magnification, imaged after 24 hours showing what seems to be two needle crystals attached, and smaller crystals growing

Figure 148: 5 mg/mL protein; 50% buffer concentration; x20 magnification; imaged after 7 days

Figure 149: 5 mg/mL protein; 100% buffer concentration; x20 magnification; imaged after 7 days; growth on a hair

Figure 147: 8 mg/mL; 100% buffer concentration, x 20 magnification; imaged after 7 days

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Figure 151: 11 mg/mL protein; 50% buffer concentration; x20 magnification; imaged after 7 days; grew through the droplet interface

Figure 153: Template A, 2.2 mg/mL; imaged after 3 days; x 40 magnification; the power of heterogeneous nucleation

Figure 154: Template B, 2.2 mg/mL; imaged

after 3 days; x 40 magnification

Screen 10

Figure 152: 8 mg/mL protein; 75% buffer concentration; x20 magnification; imaged after 7 days; grew near inside of the droplet interface