CZ5226: Advanced BioinformaticsCZ5226: Advanced Bioinformatics

Lecture 8: Molecular Modeling Method Lecture 8: Molecular Modeling Method

Prof. Chen Yu ZongProf. Chen Yu Zong

Tel: 6874-6877Tel: 6874-6877Email: Email: csccyz@nus.edu.sgcsccyz@nus.edu.sghttp://xin.cz3.nus.edu.sghttp://xin.cz3.nus.edu.sg

Room 07-24, level 7, SOC1, Room 07-24, level 7, SOC1, National University of SingaporeNational University of Singapore

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References on Modeling of MHC Binding PeptideReferences on Modeling of MHC Binding Peptide • Protein Sci. 2004 Sep;13(9):2523-32• J Am Chem Soc. 2004 Jul 14;126(27):8515-28• Proteins. 2004 Feb 15;54(3):534-56• Hum Immunol. 2003 Dec;64(12):1123-43• Immunity. 2003 Oct;19(4):595-606• Mol Med. 2003 Sep-Dec;9(9-12):220-5• Nature. 2002 Aug 1;418(6897):552-6• Eur J Immunol. 2002 Aug;32(8):2105-16• Immunol Cell Biol. 2002 Jun;80(3):286-99• Ann N Y Acad Sci. 2002 Apr;958:317-20• Mol Immunol. 2002 May;38(14):1039-49• J Pept Res. 2002 Mar;59(3):115-22• Mol Immunol. 2002 Feb;38(9):681-7• Tissue Antigens. 2002 Feb;59(2):101-12• J Comput Aided Mol Des. 2001 Jun;15(6):573-86• J Mol Biol. 2000 Jul 28;300(5):1205-35• J Comput Aided Mol Des. 2000 Jan;14(1):71-82• J Comput Aided Mol Des. 2000 Jan;14(1):53-69• J Mol Graph Model. 1999 Jun-Aug;17(3-4):180-6, 217

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What is Docking?What is Docking?

• Given two molecules find their correct association:

+

=

Recep

tor Ligand

T

Complex

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General Protein–Ligand BindingGeneral Protein–Ligand Binding• Ligand

- Molecule that binds with a protein

- DNA, drug lead compounds, etc.

• Protein active site(s)- Allosteric binding

- Competitive binding

• Function of binding interaction

- Natural and artificial

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What is Protein-Ligand What is Protein-Ligand Docking?Docking?

• Definition: Computationally predict the structures of protein-ligand

complexes from their conformations and orientations. The orientation that maximizes the interaction reveals the most accurate structure of the complex.

• Importance of complexes- structure -> function

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Example: HIV-1 ProteaseExample: HIV-1 Protease

Active Site(Aspartyl groups)

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Example: HIV-1 ProteaseExample: HIV-1 Protease

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PDBfiles

Surface Representation

Patch Detection

Matching Patches

Scoring & Filtering

Candidatecomplexes

Docking StrategyDocking Strategy

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Issues Involved in DockingIssues Involved in Docking

• Protein Structure and Active Site- assumed knowledge (PDBs, etc.)- PROCAT database: 3d enzyme active site templates

• Ligand Structure- pharmacophore (base fragment) in potential drug compound - well known groups

• Rigid vs. Flexible- solution or vacum- structure

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Algorithmic Approaches to DockingAlgorithmic Approaches to Docking

• Qualitative– Geometric– shape complementarity and fitting

• Quantitative– Energy Calculations– determine global minimum energy– free energy measure

• Hybrid– Geometric and energy complementarity

– 2 phase process: soft and hard docking

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..Design of HIV-1 Protease InhibitorDesign of HIV-1 Protease Inhibitor

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..Design of HIV-1 Protease InhibitorDesign of HIV-1 Protease Inhibitor

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..Design of HIV-1 Protease InhibitorDesign of HIV-1 Protease Inhibitor

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..Design of HIV-1 Protease InhibitorDesign of HIV-1 Protease Inhibitor

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Scoring in Ligand-Protein DockingScoring in Ligand-Protein Docking

Potential Energy Description:

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Preprocessing Preprocessing • Determine internal representation

- convert coordinates of both molecules from PDB files

- e.g. Michael Connolly’s MS program (www.biohedron.com)

- dot surface

- AutoGrid

- 3d grid (array) with discrete values

- often used in rigid docking

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Some techniquesSome techniques

• Surface representation, that efficiently represents the docking surface and identifies the regions of interest (cavities and protrusions)

• Connolly surface• Lenhoff technique• Kuntz et al. Clustered-Spheres• Alpha shapes

• Surface matching that matches surfaces to optimize a binding score:

• Geometric Hashing

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Surface RepresentationSurface Representation

• Dense MS surface (Connolly)

• Sparse surface (Shuo Lin et al.)

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Surface RepresentationSurface Representation

• Each atomic sphere is given the van der Waals radius of the atom

• Rolling a Probe Sphere over the Van der Waals Surface leads to the Solvent Reentrant Surface or Connolly surface

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Lenhoff techniqueLenhoff technique

• Computes a “complementary” surface for the receptor instead of the Connolly surface, i.e. computes possible positions for the atom centers of the ligand

Atom centers of the ligand

van der Waals surface

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Kuntz et al. Clustered-SpheresKuntz et al. Clustered-Spheres• Uses clustered-spheres to identify cavities on the receptor and

protrusions on the ligand• Compute a sphere for every pair of surface points, i and j, with

the sphere center on the normal from point i• Regions where many spheres overlap are either cavities (on the

receptor) or protrusions (on the ligand)

i

j

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Alpha ShapesAlpha Shapes

• Formalizes the idea of “shape”• In 2D an “edge” between two points is “alpha-exposed” if

there exists a circle of radius alpha such that the two points lie on the surface of the circle and the circle contains no other points from the point set

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Alpha Shapes: ExampleAlpha Shapes: Example

Alpha=infinity

Alpha=3.0 Å

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Surface MatchingSurface Matching

• Find the transformation (rotation + translation) that will maximize the number of matching surface points from the receptor and the ligand

First satisfy steric constraints…• Find the best fit of the receptor and ligand using only geometrical

constraints

… then use energy calculations to refine the docking• Selet the fit that has the minimum energy

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..Design of HIV-1 Protease InhibitorDesign of HIV-1 Protease Inhibitor

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Docking ProgramsDocking Programs

More information in: http://www.bmm.icnet.uk/~smithgr/soft.html

The programs are:

• DOCK (I. D. Kuntz, UCSF)

• AutoDOCK (Arthur Olson, The Scripps Research Institute)

• RosettaDOCK (Baker, Washington Univ., Gray, Johns Hopkins Univ.)

• INVDOCK (Y. Z. Chen, NUS)

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DOCK as an ExampleDOCK as an Example

DOCK works in 5 steps:• Step 1 Start with crystal coordinates of target receptor• Step 2 Generate molecular surface for receptor• Step 3 Generate spheres to fill the active site of the

receptor: The spheres become potential locations for ligand atoms

• Step 4 Matching: Sphere centers are then matched to the ligand atoms, to determine possible orientations for the ligand

• Step 5 Scoring: Find the top scoring orientation

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DOCK as an ExampleDOCK as an Example

1 2

3

- HIV-1 protease is the target receptor- Aspartyl groups are its active side

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DOCK as an ExampleDOCK as an Example

4 5

• Three scoring schemes: Shape scoring, Electrostatic scoring and Force-field scoring• Image 5 is a comparison of the top scoring orientation of the molecule thioketal with the orientation found in the crystal structure

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The DOCK AlgorithmThe DOCK Algorithm

Two steps in rigid ligand mode:

Orienting the putative ligand in the siteGuided by matching distances, between pre-defined site points on the target to interatomic distances of the ligand.The RT matrix is used for the transform of the ligand.

Scoring the resulting orientationEach orientation is scored for each quality fit. The process is repeated a user-defined number of orientations or maximum orientations

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.. .

.

..

. .

N

NH

N

SO

F

.. .

N

NH

N

SO

F

.

N

NH

N

SO

F

N

NH

N

SO

F

1. Define the target binding site points.

2. Match the distances.

3. Calculate the transformation matrix for the orientation.

4. Dock the molecule.

5. Score the fit.

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Site Points Generation in DOCKSite Points Generation in DOCK

• Program SPHGEN identifies the active site, and other sites of interest.

• Each invagination is characterized by a set of overlapping spheres.

• For receptors, a negative image of the surface invaginations is created;

• For a ligand, the program creates a positive image of the entire molecule.

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The MatchingThe MatchingCan be directed by 2 additional features:

• Chemical matching - labeling the site points such that only particular atom types are allowed to be matched to them.

• Critical cluster - subsets of interest can be defined as critical clusters, so that at least one member of them will be part of any accepted ligand “match”.

Increase in efficiency and speed due to elimination of potentially less promising orientations!

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Other Docking programsOther Docking programs

AutoDock– AutoDock was designed to dock flexible ligands into receptor

binding sites– The strongest feature of AutoDock is the range of powerful

optimization algorithms available

RosettaDOCK– It models physical forces and creates a very large number of

decoys – It uses degeneracy after clustering as a final criterion in decoy

selection

INVDOCK– Docking strategy and algorithm similar to DOCK, but with the

capability of finding the receptors to which a molecule can bind to.

Conformational Ensembles Conformational Ensembles DockingDocking

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Conformational Ensembles DockingConformational Ensembles Docking

Observations:

1. Generating an orientation of a ligand in a binding site may be separated from calculating a conformation of the ligand in that particular orientation.

2. Multiple conformations of a given ligand usually have some portion in common (internally rigid atoms such as ring systems), and therefore, contain redundancies.

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Conformational Ensemble DockingConformational Ensemble Docking

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Conformational Ensemble DockingConformational Ensemble Docking

• Conformational ensembles are generated by overlaying all conformations of a given molecule onto its largest rigid fragment.

• Only atoms within this largest rigid fragment are used during the distance matching step. The RT matrix is defined.

• Each of the conformers is oriented into the site and scored. The score measures steric and electrostatic complementarity.

• One matching steps - all the conformers are docked and scored in the selected orientation.

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Overview of the Ligand Ensemble MethodOverview of the Ligand Ensemble Method

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Advantages of Conformational Ensemble DockingAdvantages of Conformational Ensemble Docking

Speed increase due to:

• One matching step for all the conformers.

• The largest rigid fragment usually has fewer atoms (less potential matches are examined).

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Disadvantages of Conformational Disadvantages of Conformational Ensemble DockingEnsemble Docking

• Loss of information when the orientations are guided only by a subset of the atoms in molecule. Orientations may be missed because potential distance matches from non-rigid portions of the molecule are not considered.

• The ensemble method will fail for ligands that lack internally rigid atoms.

• The use of chemical matching and critical clusters is limited.

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Results of Docking StudiesResults of Docking Studies

The docked (blue) and crystal (yellow) structure of ligands in some PDB ligand-protein complexes. The PDB Id of each structure is shown.

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Protein-Protein cases from protein-protein docking benchmark [6]:Enzyme-inhibitor – 22 casesAntibody-antigen – 16 cases

Protein-DNA docking: 2 unbound-bound cases

Protein-drug docking: tens of bound cases (Estrogen receptor, HIV protease, COX)

Performance: Several minutes for large protein molecules and seconds for small drug molecules on standard PC computer.

Dataset and Testing ResultsDataset and Testing Results

Endonuclease I-PpoI (1EVX) with DNA (1A73). RMSD 0.87Å, rank 2

DNAendonucleasedocking solution

Estrogen receptor

Estradiol molecule from complex

docking solution

Estrogen receptor with estradiol (1A52). RMSD 0.9Å, rank 1, running time: 11 seconds

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Results Enzyme-Inhibitor Results Enzyme-Inhibitor dockingdockingComplex Description

pen. res.1

geom score time with ACE score

PDB receptor/ligand rmsd rank min. rmsd rank

1ACB α-chymotrypsin/Eglin C 0,2 2.0 41 9:37 1.8 55

1AVW Trypsin/Sotbean Trypsin inhibitor 3,4 1.9 913 11:27 1.9 319

1BRC Trypsin/APPI 0,2 5.0 528 5:20 5.6 66

1BRS Barnase/Barstar 1,3 3.5 115 5:18 2.7 7

1CGI α-chymotrypsinogen/trypsin inhibitor 4,2 2.4 114 6:26 3.0 10

1CHO α-chymotrypsin/ovomucoid 3rd Domain 0,3 3.4 148 5:35 1.2 26

1CSE Subtilisin Carlsberg/Eglin C 0,2 3.8 166 6:58 2.3 540

1DFJ Ribonuclease inhibitor/Ribonuclease A 12,8 3.9 1446 11:58 11.9 612

1FSS Acetylcholinesterase/Fasciculin II 8,3 2.5 296 11:42 2.3 46

1MAH Mouse Acetylcholinesterase/inhibitor 2,5 2.5 436 14:39 2.3 57

1PPE* Trypsin/CMT-1 0,0 2.0 1 2:34 2.0 1

1STF* Papain/Stefin B 0,0 2.2 4 8:15 2.1 13

1TAB* Trypsin/BBI 0,1 1.4 96 3:41 7.2* 104

1TGS Trypsinogen/trypsin inhibitor 5,4 2.2 345 5:19 3.6 101

1UDI* Virus Uracil-DNA glycosylase/inhibitor 4,2 2.6 3 7:40 2.4 1

1UGH Human Uracil-DNA glycosylase/inhibitor 8,3 2.1 12 5:45 3.8 5

2KAI Kallikrein A/Trypsin inhibitor 10,7 4.2 126 7:15 4.7 42

2PTC β-trypsin/ Pancreatic trypsin inhibitor 2,4 4.4 66 5:13 3.4 12

2SIC Subtilisin BPN/Subtilisin inhibitor 5,3 2.5 129 9:41 4.7 21

2SNI Subtilisin Novo/Chymotrypsin inhibitor 2 6,7 8.3 1241 5:08 7.3 450

2TEC* Thermitase/Eglin C 0,1 3.0 66 7:58 1.4 29

4HTC* α-Thrombin/Hirudin 2,2 3.3 2 3:36 2.8 21 Number of highly penetrating residues in unbound structures superimposed to complex

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Results Antibody-Antigen dockingResults Antibody-Antigen docking

Complex Description pen. res. 1

geom score time ACE score

PDB receptor/ligand rmsd rank min. rmsd rank

1AHW Antibody Fab 5G9/Tissue factor 3,3 2.5 29 10:12 2.5 10

1BQL* Hyhel - 5 Fab/Lysozyme 0,0 2.5 13 6:21 1.4 7

1BVK Antibody Hulys11 Fv/Lysozyme 0,0 3.8 1301 6:25 3.5 809

1DQJ Hyhel - 63 Fab/Lysozyme 18,7 4.3 773 5:30 5.1 953

1EO8* Bh151 Fab/Hemagglutinin 3,1 1.8 567 9:45 1.6 292

1FBI* IgG1 Fab fragment/Lysozyme 2,5 5.0 536 10:13 5.0 2416

1IAI* IgG1 Idiotypic Fab/Igg2A Anti-Idiotypic Fab 5,6 4.8 1302 9:13 3.4 1304

1JHL* IgG1 Fv Fragment/Lysozyme 0,0 1.6 282 13:15 1.3 143

1MEL* Vh Single-Domain Antibody/Lysozyme 0,1 1.8 3 2:40 2.0 2

1MLC IgG1 D44.1 Fab fragment/Lysozyme 8,3 4.0 136 5:29 2.6 123

1NCA* Fab NC41/Neuraminidase 0,0 2.6 114 17:50 2.8 66

1NMB* Fab NC10/Neuraminidase 0,0 2.7 2593 28:10 2.4 1734

1QFU* Igg1-k Fab/Hemagglutinin 0,0 2.7 44 5:42 2.7 23

1WEJ IgG1 E8 Fab fragment/Cytochrome C 0,0 4.3 232 7:44 2.6 87

2JEL* Jel42 Fab Fragment/A06 Phosphotransferase 0,2 4.7 114 5:02 4.7 50

2VIR* Igg1-lamda Fab/Hemagglutinin 0,0 3.1 258 7:34 3.5 306

1 Number of highly penetrating residues in unbound structures superimposed to complex

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Quality of INVDOCK AlgorithmQuality of INVDOCK Algorithm Proteins. 1999; 36:1Proteins. 1999; 36:1

Molecule Docked Protein PDB Id

RMSDDescription of Docking Quality Energy

(kcal/mol)

Indinavir HIV-1 Protease 1hsg 1.38 Match -70.25

Xk263 Of Dupont Merck

HIV-1 Protease 1hvr 2.05 Match -58.07

Vac HIV-1 Protease 4phv 0.80 Match -88.46

Folate 

Dihydrofolate Reductase 1dhf 6.55 One end match, the other in different orientation -46.02

5-Deazafolate Dihydrofolate Reductase 2dhf 1.48 Match -65.49

Estrogen Estrogen Receptor 1a52 1.30 Match -45.86

4-Hydroxytamoxifen Estrogen Receptor

 3ert 

5.45 

Complete overlap, flipped along short axis -55.15

Guanosine-5'-[B,G-Methylene] Triphosphate

H-Ras P21 

121p 

0.94 Match-80.20

Glycyl-*L-Tyrosine 

Carboxypeptidase A 3cpa 3.56 Overlap, flipped along short axis-40.63

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Identification of the N-terminal Identification of the N-terminal peptide binding site of GRP94peptide binding site of GRP94

GRP94 - Glucose regulated protein 94

VSV8 peptide - derived from vesicular stomatitis virus

Gidalevitz T, Biswas C, Ding H, Schneidman-Duhovny D, Wolfson HJ, Stevens F, Radford S, Argon Y. J Biol Chem. 2004

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Biological motivationBiological motivation

The complex between the two molecules highly stimulates the response of the T-cells of the immune system. The grp94 protein alone does not have this property. The activity that stimulates the immune response is due to the ability of grp94 to bind different peptides. Characterization of peptide binding site is highly important.

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GRP94 moleculeGRP94 molecule

There was no structure of grp94 protein. Homology modeling was used to predict a structure using another protein with 52% identity.

Recently the structure of grp94 was published. The RMSD between the crystal structure and the model is 1.3A.

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DockingDocking

PatchDock was applied to dock the two molecules, without any binding site constraints. Docking results were clustered in the two cavities:

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GRP94 moleculeGRP94 molecule There is a binding site for inhibitors between the helices. There is another cavity produced by beta sheet on the opposite side.