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Homology modeling

Dinesh GuptaICGEB, 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 E

str = ½k

s,ij(r

ij -r

o)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 E

bend = ½k

b,ij(

ij –

o)2

where where kb,ij is the bending force constant, ij is the instantaneousbond 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 betweenatoms i and j with thebend between atomsi, 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 units constant (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 anglearound the bond, and ktor,1, ktor,2

and ktor,3 are constants for one-,two- and three-fold barriers.

energy of 3-fold torsionalbarrier 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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