Protein Structure Prediction

Transcription

1 Protein Structure Prediction Michael Feig MMTSB/CTBP 2006 Summer Workshop

2 From Sequence to Structure SEALGDTIVKNA

3 Ab initio Structure Prediction Protocol Amino Acid Sequence Conformational Sampling to generate native-like structures Scoring & Clustering to identify most native-like structures 3D Structure

4 Folding with All-Atom Models AAQAAAAQAAAAQAA CHARMM force field Implicit solvent replica exchange simulations 8 replicas, 10 ns/replica

5 Folding with Low-Resolution Model EQQNAFYEILHLPNLNEEQRNGFIQSLKDDPSQSANLLAEAKKLNDAQA SICHO model, MONSSTER simulated annealing run

6 SICHO Lattice Model Monte Carlo simulations: Thr Leu > Attempt move > Compute ΔE Phe > Accept with probability p: Asp %1 "E # 0 p =& 'exp($"e / k BT ) "E > 0 Simulated annealing! MMTSB/CTBP Summer Workshop Constant Temperature Replica Exchange Sampling Kolinski & Skolnick: Proteins 32, 475 (1998) Michael Feig, 2006.

7 Excluded volume SICHO Energy Function Knowledge-Based Terms Side chain burial propensity follows Kyte-Doolittle scale Centrosymmetric bias r g = 2.2 N 0.38 res Ala Arg Asp Ile

8 SICHO Energy Function Statistical Terms Potential of mean force (PMF): p " #E ij i kbt = e p j energy "E = #kt ln(p) extended GLU-GLU r(i,i+4) in Å helix

9 Conformational Sampling with SICHO All-Atom Energy in kcal/mol Protein A RMSD from native in Å MMTSB/CTBP Summer Workshop Michael Feig, 2006.

10 Ab initio Structure Prediction Protocol Amino Acid Sequence Secondary Structure Prediction PSIPRED et al. Efficient Sampling e.g. MONSSTER/SICHO All-Atom Reconstruction Scoring & Clustering e.g. MMGB/SA, DFIRE 3D Structure

11 Secondary Structure Prediction GDPIVKNAKLDSRLANKEALRLL?

12 Secondary Structure Propensities α-helix β-sheet turn Chou & Fasman (1974)

13 Secondary Structure Prediction Methods SABLE PSIPRED PSSP SAM-T99-sec PHD C+F 77.6% 76.2% 75.1% 76.1% 72.3% 50-60% C+F: Chou & Fasman GOR: Garnier, Osguthorpe, Robson

14 Secondary structure prediction Per-Residue Accuracy

15 Realistic ab initio Structure Prediction CHARMM22/GBMV C! RMSD in Å (62 residues)

16 Sampling, Scoring, Clustering CHARMM22/GBMV C! RMSD in Å (62 residues)

17 Ab initio Predictions DNase fragmentation factor NMR structure 1KOY Best-scoring prediction 7.4 Å RMSD

18 Scoring Functions Knowledge-based/statistical derived from known protein structures limited by training data usually fast e.g. DFIRE, RAPDF, prosaii Force field based model physical energy landscape more robust and transferable often expensive (require minimization) e.g. MMPB(GB)/SA, UNRES

19 -3500 Scoring Function Comparison MMGB/SA vs. DFIRE MMGB/SA score DFIRE score C! RMSD in Å radius of gyration C! RMSD in Å C! RMSD in Å

20 Sampling with Restraints Secondary structure bias Secondary structure prediction NMR shift data Distance restraints Experimental restraints (disulfides, NMR, EPR) Side chain contacts from analogous structures Shape restraints cryoem data, small-angle X-ray scattering

21 but the solution may lie elsewhere.

22 Sequence Homology Human thioredoxin (1AUC) SDKIIHLTDDSFDTDVLKADGAILVDFWAEWCGPCKMIAPILDEIADEYQGKLTV A : :....:..::: : :::::::: :.....:.... MVKQIESKTAFQEALDAAGDKLVVVDFSATWCGPCKMIKPFFHSLSEKYSNVIFL - KLNIDQNPGTAPKYGIRGIPTLLLFKNGEVAATKVGALSKGQLKEFLDAN---LA...:..:....::..::.:. :::.: : :: :.:. :. EVDVDDCQDVASECEVKCMPTFQFFKKGQ----KVGEFS-GANKEKLEATINELV E. Coli thioredoxin (1THO)

23 Comparative Modeling Assumption: Proteins with similar sequence have similar structure Human thioredoxin (1AUC) E. Coli thioredoxin (1THO)

24 Structural Templates from Homology Challenges: Correct alignment Loop modeling Side chain rebuilding PGTAPKYGIRGIPTLLLFKNGEVAATKVGALSKGQLKEFLDAN---LA.:....::..::.:. :::.: : :: :.:. :. QDVASECEVKCMPTFQFFKKGQ----KVGEFS-GANKEKLEATINELV

25 Accuracy of Predictions by Homology 100 % predictions % sequence identity <2Å RMSD <5Å RMSD

26 Prediction through Fold Recognition Assumption: Proteins with similar secondary structure share fold 1N91 1JRM

27 Templates through Fold Recognition Challenges: Wrong templates Alignment uncertain Fragment modeling Refinement needed

28 Ab initio Sampling in Template-based Structure Prediction Template provides known protein structure Ab initio sampling of unknown fragments in the context of template

29 Template Restraints Near Flexible Part Restraint potential: U = f " k (r # r 0 ) 2

30 Loop Sampling Methods # Residues Sampling All-Atom Reconstruction Exhaustive Search Torsional Space MC/MD Multi-Scale Fragment-based Program MMTSB Tool Set Modeller (Sali) MMTSB Tool Set Rosetta (Baker)

31 Structural Genomics Efforts

32 Structure Refinement? predicted native (NMR)