Ab-initio protein structure prediction

1. Ab-initio protein structure prediction Chen Keasar BGU ? Any educational usage of these slides is welcomed. Please acknowledge. keasar@cs.bgu.ac.il

2. The problem: Predict the three dimensional structure of a protein based on its sequence. ? ? ? ? ? ? ……TVFAIYDYDFK….. ……TEDDAGSFHEK …… ……TLUNSGDGDWW …… ……TGYVGSSYV …… Chen Keasar BGU

3. Are we lucky? no yes a bit A C C W K A C V K G + homology C A K C W A ab initio C G fold recognition K V C A K C W A C G K V How can we predict protein structures? Chen Keasar BGU

4. Why is ab-initio prediction hard? Chen Keasar BGU

5. Ab-initio is hard, why do it? Wait until enough proteins are solved and use homology modeling/fold-recognition Chen Keasar BGU

6. Because it’s there Chen Keasar BGU

7. Because homology modeling tells us nothing about the physical nature of the protein folding and stability. • Because ab-initio methods can augment fold-recognition and homology (refinement, large loops, side chains). • Because of ORFans (orphan ORFs). • Because it can ease experimental structure determination. • Because prediction is the basis of design. Chen Keasar BGU

8. Simulation of the actual folding process • Build an accurate initial model (including energy and forces). • Accurately simulate the dynamics of the system. • The native structure will emerge. •  • Optimization problem • Define some initial model. • Define a function mapping structures to numerical values (the lower the better). • Solve the computational problem of finding the global minimum. •  ab-initio protein structure prediction Chen Keasar BGU

9. Simulating the actual folding process Model I – quantum description of the system dimera CHOOH Chen Keasar BGU

10. Model II • Semi-empirical energy functions – forcefields • Classic world no quantum effects (that is no chemistry). • Parameterized to reproduce experimental results for small molecules. Their use for proteins is an extrapolation. • The basic element is an atom: • Unbreakable. • Represented by the X,Y,Z coordinates of its center. • Its attributes (volume, charge, mass etc.) are the basic parameters of the energy function. Chen Keasar BGU

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15. The good news The model is rather accurate and correctly describe many natural phenomena.  • The bad news • Each time step is hard to compute. • An order of 1012 steps are needed to simulate protein folding.  Chen Keasar BGU

16. Ab-initio protein structure prediction as an optimization problem energy conformation • Define a function that map protein structures to some quality measure. • Solve the computational problem of finding an optimal structure. •  Chen Keasar BGU

17. A dream function Has a clear minimum in the native structure.  Has a clear path towards the minimum.  Global optimization algorithm should find the native structure. Chen Keasar BGU

18. An approximate function  Easier to design and compute.  Native structure not always the global minimum.  Global optimization methods do not converge. Many alternative models (decoys) should be generated. Chen Keasar BGU

19. An approximate function  Easier to design and compute.  Native structure not always the global minimum.  Global optimization methods do not converge. Many alternative models (decoys) should be generated. No clear way of choosing among them. Decoy set Chen Keasar BGU

20. Energy functions: • Typically include terms for hydrophobicity, hydrogen bonds etc. • Typically based on the distribution of structural features (say contacts between alanine residues and arginine residues) in the PDB. The more frequent is the feature the lower is the energy associated with it. Assumptions: • These features are independent. • The proteins in the PDB are a representative sample of conformation space. A small problems – these assumptions are wrong. A brilliant solution – ignore it. Chen Keasar BGU

21. Basic element Not really Ab-initio electrons & protons AMBR ECEP CHARM OPLS ENCAD GROMOS atom heavy atom Levitt & Keasar Baker (Rosetta) Levitt 1976 Scheraga 1998 half a residue Jones Skolnik 1998 Park & Levitt Osguthorpe residue Skolnik 2000 Some residues Hinds & Levitt diamond lattice torsion angle lattice fine square lattice fragments continuous Chen Keasar BGU

22. Basic element electrons & protons atom extended atom half a residue residue Some residues Hinds & Levitt diamond lattice torsion angle lattice fine square lattice fragments continuous Chen Keasar BGU

23. Basic element electrons & protons atom extended atom half a residue Park & Levitt residue Some residues diamond lattice torsion angle lattice fine square lattice fragments continuous Chen Keasar BGU

24. Basic element electrons & protons atom extended atom half a residue residue Skolnik 2000 Some residues diamond lattice torsion angle lattice fine square lattice fragments continuous Chen Keasar BGU

25. Basic element electrons & protons atom extended atom Scheraga 1998 half a residue residue Some residues diamond lattice torsion angle lattice fine square lattice fragments continuous Chen Keasar BGU

26. Basic element electrons & protons Apparently the best current method AMBR ECEP CHARM OPLS ENCAD GROMOS atom extended atom Levitt, Keasar Baker (Rosetta) Levitt 1976 Scheraga 1998 half a residue Jones Skolnik 1998 Park & Levitt Osguthorpe residue Skolnik 2000 Some residues Hinds & Levitt diamond lattice torsion angle lattice fine square lattice fragments continuous Chen Keasar BGU