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Homology modeling

Dinesh Gupta

ICGEB, New Delhi

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Protein structure prediction

• Methods:

– Homology (comparative) modelling

– Threading

– Ab-initio

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Protein Homology modeling

• Homology modeling is an extrapolation of protein structure for a target sequence using the known 3D structure of similar sequence as a template.

• Basis: proteins with similar sequences are likely to assume same folding

• Certain proteins with as low as 25% similarity have been observed to assume same 3D structure

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The accuracy of modeling is proportional

to the similarity in primary sequences

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Steps…

• Given:

– A query sequence Q

– A database of known protein structures

• Find protein P such that P has high

sequence similarity to Q

• Return P’s structure as an approximation

to Q’s structure

• Energy minimization

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Sofware for homology molecular

modelling

• Freeware: available for all OS

– Downloadable

• Modeller (Sali, 1998)

• DeepView (SwissPDB viewer)

• WHATIF (Krieger et al. 2003)

– Web based:

• SWISS MODEL server (www.expasy.org/swissmod/SWISS-

MODEL.html)

• CPH model server

(http://www.cbs.dtu.dk/services/CPHmodels)

• SDSC1 server (http://cl.sdsc.edu/hm.html)

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Protein structure prediction

• Methods:

– Homology (comparative) modelling

– Threading

– Ab-initio

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Threading

• Structure prediction that picks up where homology modelling leaves off.

• Recognize folds in proteins having no similarity to known proteins structures

• Very approximate models

• Check by forcing a sequence of structure into known folds checking the packing of aa residues, including sides chains, in each fold.

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2 kinds of threading

• Three dimensional threading

– Distance Based Method (DBM)

• Two dimensional threading

– Prediction Based Methods (PBM)

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Threading software

• EVA: http://cubic.bioc.columbia.edu/eva/

• SAMt99: http://www.cse.ucsc.edu/research/compbio/HMM-apps/T99-model-library-search.html

• 3DPSSM: http://www.sbg.bio.ic.ac.uk/3dpssm

• FUGUE: http://tardis.nibio.go.jp/fugue/

• Metaservers:

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Protein structure prediction

• Methods:

– Homology (comparative) modelling

– Threading

– Ab-initio

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Ab initio structure prediction

• Still experimental

• ROSETTA (David Baker)

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Energy minimization (Molecular

Mechanics, MM)

• Energy minimization is an important part of both empirical and predicted structures

• MM could be used to calculate large scale conformational changes over long periods of time, but currently computationally infeasible.

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How does MM work?

• Three aspects:– Functions that describe the forces acting on the

atoms

– Numerical integration methods, to calculate the motion of the atoms due to the forces acting on them

– Long time propagation of the equations of motion

• Computational demands are intense– Accuracy (small errors propagate!)

– Stability

– Lots of techniques for approximation (e.g. rigid bodies) and handling artifacts (resonance).

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The Force Fields

• How do atoms stretch, vibrate, rotate, etc.?

• Must represent the constraints on atomic motion

(e.g. van der Waals, electrostatic, bonds, etc.)

• Must also represent solvation effects etc.

• Quantum solutions exist, but are too complex to

calculate for such large systems

• Empirical (approximate) energy functions must

be used. No single best function exists.

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Real energetics

• Steric (conformational) energy. Additive

combination of

– Bonded: stretching, bending, stretching and bending

– Non-bonded: Van der Waals, electrostatic and

“torsional”

• Minimum energy conformation minimizes these

energies

• Rosetta energy function is an empirical attempt

to capture most of this energy function without

having to calculate it fully.

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Bond length

• Spring-like term for energy based on

distance Estr

= ½ks,ij

(rij

-ro)2

where ks,ij is the stretching force constant

for the bond between i and j, rij is the

length, and ro is the equilibrium bond

length

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Bond bend

• Same basic idea for bending

Ebend

= ½kb,ij

(ij–

o)2

where where kb,ij is the bending force constant,

ij is the instantaneous

bond angle, and o is

the equilibrium

bond angle

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Stretch-bend

• When a bond is bent, the two associated bond

lengths increase, with interaction term:

Estr-bend

=½ksb,ijk

(rij-r

o)(

ik-

o)

where ksb,ijk is the stretch-bend force constant for

the bond between

atoms i and j with the

bend between atoms

i, j, and k.

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• A non-bonded interaction capturing the preferred distance between atoms

where A and B are constants depending on the atoms. For two hydrogen atoms, A=70.4kCÅ6 and B=6286kCÅ12

Van der Waals

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Electrostatics

• If bonds in the molecule are polar, some atoms will have partial electrostatic charges, which attract if opposite and repel otherwise.

where Qi and Qj are the partial atomic charges for i and j

separated by distance rij , is the dielectric constant of the solute, and k is a unitsconstant (k=2086 kcal/mol)

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Torsional energy

• Torsion is the energy needed to rotate about

bonds. Only relevant to single bonds, since

others are too stiff to rotate at all

Etor = ½ktor,1 (1 - cos ) + ½ktor,2 (1 - 2cos )

+ ½ktor,3 (1 - 3cos )

where is the dihedral angle

around the bond, and ktor,1, ktor,2

and ktor,3 are constants for one-,

two- and three-fold barriers.

energy of 3-fold torsional

barrier in ethane

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Energy minimization

• Given some energy function and initial conditions, we want to find the minimum energy conformation.

• Optimization problem, various methods:

– Steepest descent

– Conjugate gradient descent

– Newton-Raphson

• Various programs: Charmm, Amber are two most widely used (and packaged)

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Time steps

Need time steps of roughly 1/10 the period of the smallest time

scale of interest, or about a femtosecond (10-15s). A million

computational steps per nanosecond of simulation...

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Issues in Molecular Mechanics

• Solvation models: water & salt are very important to molecular behaviour. Must model as many water atoms as protein atoms.

• Initial conditions: velocity & position

• Equilibration: simulated heating and cooling

• Chaos: sensitivity to initial conditions, and statistical characterization of states

• Computational issues (e.g. parallelization)

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Molecular Dynamics

• Molecules, especially proteins, are not static.

– Dynamics can be important to function

• Trajectories, not just minimum energy state.

– MM ignores kinetic energy, does only potential energy

– MD takes same force model, but calculates F=ma and

calculates velocities of all atoms (as well as positions)

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Docking

• Computation to assess binding affinity

• Looks for conformational and electrostatic "fit"

between proteins and other molecules e.g.

inhibitors

• Optimization again: what position and

orientation of the two molecules minimizes

energy?

• Large computations, since there are many

possible positions to check, and the energy for

each position may involve many atoms

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Virtual Screening

• Docking small ligands to proteins is a way to find

potential drugs. Industrially important

• A small region of interest (pharmacophore) can

be identified, reducing computation

• Empirical scoring functions are not universal

• Various search methods:

– Rigid provides score for whole ligand (accurate)

– Flexible breaks ligands into pieces and docks them

individually

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Docking example

Benzamidine binding to beta-Trypsin 3ptb,

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Macromolecular docking• Docking of proteins to proteins or to DNA

• Important to understanding

macromolecular recognition, genetic

regulation, etc.

• Conceptually similar to small molecule

docking, but practically much more difficult

– Score function can't realistically compute

energies

– Use either shape complementarities alone or

some kind of mean field approximation

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Docking Resources

• AutoDock http://www.scripps.edu/pub/olson-

web/doc/autodock/

• FlexX http://www.biosolveit.de/FlexX/ and

commercially at http://www.tripos.com

• Dock

http://www.cmpharm.ucsf.edu/kuntz/dock.html

• 3D-Dock http://www.bmm.icnet.uk/docking/

which uses an unusual “Fourier correlation”

method and is aimed at protein-protein

interactions

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Lab Exercise-1

Install:

• MDL chime

• RasMol

• SwissPDBviewer

• Cn3D

Explore few protein/DNA structures

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Lab exercise-2

• Download sequence file for S. cerevisiae endoplasmic reticulum mannosidase

• Generate a homology model using SWISS-model server http://www.expasy.ch/swissmod/

• Download the template structure from www.rcsb.org

• Compare the model and template structures

• Repeat the exercise for other protein sequences of your choice

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