All-Atom Ab Initio Folding of a Diverse Set of Proteins

Structure

Volumn 15, Issue 1, 2007, Pages 53-63

  Yang, Jae Shick ^a   Chen, William W ^a,b   Skolnick, Jeffrey ^c   Shakhnovich, Eugene I ^a  

^a HARVARD UNIVERSITY   (United States)

^b HARVARD UNIVERSITY   (United States)

^c UNIVERSITY AT BUFFALO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AB INITIO CALCULATION; ARTICLE; HYDROGEN BOND; MOLECULAR INTERACTION; MOLECULAR MODEL; MONTE CARLO METHOD; PRIORITY JOURNAL; PROTEIN FOLDING; PROTEIN STRUCTURE; STRUCTURE ANALYSIS; THERMODYNAMICS;

MODELS, MOLECULAR; MONTE CARLO METHOD; PROTEIN FOLDING; PROTEIN STRUCTURE, SECONDARY;

EID: 33846104376     PISSN: 09692126     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.str.2006.11.010     Document Type: Article

References (40)

1. Behe M.J., Lattman E.E., and Rose G.D. The protein-folding problem: the native fold determines packing, but does packing determine the native fold?. Proc. Natl. Acad. Sci. USA 88 (1991) 4195-4199
2. Bradley P., Misura K.M., and Baker D. Toward high-resolution de novo structure prediction for small proteins. Science 309 (2005) 1868-1871
3. Brooks B.R., Bruccoleri R.E., Olafson B.D., States D.J., Swaminathan S., and Karplus M. CHARMM: a program for macromolecular energy, minimization, and dynamics calculations. J. Comput. Chem. 4 (1983) 187-217
4. Chen W.W., and Shakhnovich E.I. Lessons from the design of a novel atomic potential for protein folding. Protein Sci. 14 (2005) 1741-1752
5. Chen W.W., Yang J.S., and Shakhnovich E.I. A knowledge-based move set for protein folding. Proteins (2006) in print
6. Coutsias E.A., Seok C., Jacobson M.P., and Dill K.A. A kinematic view of loop closure. J. Comput. Chem. 25 (2004) 510-528
7. Dill K.A. Dominant forces in protein folding. Biochemistry 29 (1990) 7133-7155
8. Duan Y., and Kollman P.A. Pathways to a protein folding intermediate observed in a 1-microsecond simulation in aqueous solution. Science 282 (1998) 740-744
9. Fersht A.R., and Daggett V. Protein folding and unfolding at atomic resolution. Cell 108 (2002) 573-582
10. Frishman D., and Argos P. Knowledge-based protein secondary structure assignment. Proteins 23 (1995) 566-579
11. Gront D., Kolinski A., and Skolnick J. Comparison of three Monte Carlo conformational search strategies for a proteinlike homopolymer model: folding thermodynamics and identification of low-energy structures. J. Chem. Phys. 113 (2000) 5065-5071
12. Guex N., and Peitsch M.C. SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis 18 (1997) 2714-2723
13. Gutin A.M., Abkevich V.V., and Shakhnovich E.I. Chain length scaling of protein folding time. Phys. Rev. Lett. 77 (1996) 5433-5436
14. Hubner I.A., Deeds E.J., and Shakhnovich E.I. High-resolution protein folding with a transferable potential. Proc. Natl. Acad. Sci. USA 102 (2005) 18914-18919
15. Hubner I.A., Deeds E.J., and Shakhnovich E.I. Understanding ensemble protein folding at atomic detail. Proc. Natl. Acad. Sci. USA 103 (2006) 17747-17752
16. Humphrey W., Dalke A., and Schulten K. VMD: visual molecular dynamics. J. Mol. Graph. 14 (1996) 33-38
17. Jain A.K., and Dubes R.C. Algorithms for Clustering Data (1988), Prentice Hall, Englewood Cliffs, NJ
18. Klimov D.K., and Thirumalai D. Mechanisms and kinetics of beta-hairpin formation. Proc. Natl. Acad. Sci. USA 97 (2000) 2544-2549
19. Kussell E., Shimada J., and Shakhnovich E.I. A structure-based method for derivation of all-atom potentials for protein folding. Proc. Natl. Acad. Sci. USA 99 (2002) 5343-5348
20. Lazaridis T., and Karplus M. "New view" of protein folding reconciled with the old through multiple unfolding simulations. Science 278 (1997) 1928-1931
21. Liwo A., Khalili M., and Scheraga H.A. Ab initio simulations of protein-folding pathways by molecular dynamics with the united-residue model of polypeptide chains. Proc. Natl. Acad. Sci. USA 102 (2005) 2362-2367
22. McGuffin L.J., Bryson K., and Jones D.T. The PSIPRED protein structure prediction server. Bioinformatics 16 (2000) 404-405
23. Meisner W.K., and Sosnick T.R. Fast folding of a helical protein initiated by the collision of unstructured chains. Proc. Natl. Acad. Sci. USA 101 (2004) 13478-13482
24. Mirny L.A., and Shakhnovich E.I. How to derive a protein folding potential? A new approach to an old problem. J. Mol. Biol. 264 (1996) 1164-1179
25. Richards F.M., and Lim W.A. An analysis of packing in the protein folding problem. Q. Rev. Biophys. 26 (1993) 423-498
26. Shakhnovich E.I. Proteins with selected sequences fold into unique native conformation. Phys. Rev. Lett. 72 (1994) 3907-3910
27. Shakhnovich E.I. Protein design: a perspective from simple tractable models. Fold. Des. 3 (1998) R45-R58
28. Shakhnovich E.I. Protein folding thermodynamics and dynamics: where physics, chemistry, and biology meet. Chem. Rev. 106 (2006) 1559-1588
29. Shimada J., Kussell E.L., and Shakhnovich E.I. The folding thermodynamics and kinetics of crambin using an all-atom Monte Carlo simulation. J. Mol. Biol. 308 (2001) 79-95
30. Shortle D. Propensities, probabilities, and the Boltzmann hypothesis. Protein Sci. 12 (2003) 1298-1302
31. Siew N., Elofsson A., Rychlewski L., and Fischer D. MaxSub: an automated measure for the assessment of protein structure prediction quality. Bioinformatics 16 (2000) 776-785
32. Simons K.T., Strauss C., and Baker D. Prospects for ab initio protein structural genomics. J. Mol. Biol. 306 (2001) 1191-1199
33. Snow C.D., Nguyen H., Pande V.S., and Gruebele M. Absolute comparison of simulated and experimental protein-folding dynamics. Nature 420 (2002) 102-106
34. Srinivasan R., Fleming P.J., and Rose G.D. Ab initio protein folding using LINUS. Methods Enzymol. 383 (2004) 48-66
35. Swendsen R.H., and Wang J.S. Replica Monte Carlo simulation of spin glasses. Phys. Rev. Lett. 57 (1986) 2607-2609
36. Wang G., and Dunbrack Jr. R.L. PISCES: a protein sequence culling server. Bioinformatics 19 (2003) 1589-1591
37. Zhang Y., and Skolnick J. Automated structure prediction of weakly homologous proteins on a genomic scale. Proc. Natl. Acad. Sci. USA 101 (2004) 7594-7599
38. Zhang Y., and Skolnick J. The protein structure prediction problem could be solved using the current PDB library. Proc. Natl. Acad. Sci. USA 102 (2005) 1029-1034
39. Zhang Y., Arakaki A.K., and Skolnick J. TASSER: an automated method for the prediction of protein tertiary structures in CASP6. Proteins 61 Suppl 7 (2005) 91-98
40. Zhou H., and Zhou Y. Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction. Protein Sci. 11 (2002) 2714-2726