Homology modeling. Dinesh Gupta ICGEB, New Delhi 1/27/2010 5:59 PM

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1 Homology modeling Dinesh Gupta ICGEB, New Delhi

2 Protein structure prediction Methods: Homology (comparative) modelling Threading Ab-initio

3 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

4 The accuracy of modeling is proportional to the similarity in primary sequences

5 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

6 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 ( MODEL.html) CPH model server ( SDSC1 server (

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10 Protein structure prediction Methods: Homology (comparative) modelling Threading Ab-initio

11 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.

12 2 kinds of threading Three dimensional threading Distance Based Method (DBM) Two dimensional threading Prediction Based Methods (PBM)

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14 Threading software EVA: SAMt99: o/hmm-apps/t99-model-librarysearch.html 3DPSSM: FUGUE: Metaservers:

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19 Protein structure prediction Methods: Homology (comparative) modelling Threading Ab-initio

20 Ab initio structure prediction Still experimental ROSETTA (David Baker)

21 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.

22 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).

23 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.

24 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.

25 Bond length Spring-like term for energy based on distance E str = ½k s,ij (r ij -r o ) 2 where k s,ij is the stretching force constant for the bond between i and j, r ij is the length, and r o is the equilibrium bond length

26 Bond bend Same basic idea for bending E bend = ½k b,ij ( ij o ) 2 where where k b,ij is the bending force constant, ij is the instantaneous bond angle, and o is the equilibrium bond angle

27 Stretch-bend When a bond is bent, the two associated bond lengths increase, with interaction term: E str-bend =½k sb,ijk (r ij -r o )( ik - o ) where k sb,ijk is the stretch-bend force constant for the bond between atoms i and j with the bend between atoms i, j, and k.

28 Van der Waals 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=70.4kCÅ 6 and B=6286kCÅ 12

29 Electrostatics If bonds in the molecule are polar, some atoms will have partial electrostatic charges, which attract if opposite and repel otherwise. where Q i and Q j are the partial atomic charges for i and j separated by distance r ij, is the dielectric constant of the solute, and k is a units constant (k=2086 kcal/mol)

30 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 E tor = ½k tor,1 (1 - cos ) + ½k tor,2 (1-2cos ) + ½k tor,3 (1-3cos ) where is the dihedral angle around the bond, and k tor,1, k tor,2 and k tor,3 are constants for one-, two- and three-fold barriers. energy of 3-fold torsional barrier in ethane

31 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)

32 Time steps Need time steps of roughly 1/10 the period of the smallest time scale of interest, or about a femtosecond (10-15 s). A million computational steps per nanosecond of simulation...

33 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)

34 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)

35 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

36 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

37 Docking example Benzamidine binding to beta-trypsin 3ptb,

38 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

39 Docking Resources AutoDock FlexX and commercially at Dock 3D-Dock which uses an unusual Fourier correlation method and is aimed at protein-protein 1/27/2010 interactions 5:59 PM

40 Lab Exercise-1 Install: MDL chime RasMol SwissPDBviewer Cn3D Explore few protein/dna structures

41 Lab exercise-2 Download sequence file for S. cerevisiae endoplasmic reticulum mannosidase Generate a homology model using SWISS-model server Download the template structure from Compare the model and template structures Repeat the exercise for other protein sequences of your choice

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