OPUS-Ca: A knowledge-based potential function requiring only Cα positions

Protein Science

Volumn 16, Issue 7, 2007, Pages 1449-1463

  Wu, Yinghao ^a   Lu, Mingyang ^b   Chen, Mingzhi ^b   Li, Jialin ^b   Ma, Jianpeng ^a,b  

^a Rice University   (United States)

^b BAYLOR COLLEGE OF MEDICINE   (United States)

Author keywords

Decoy recognition; Knowledge based potential function; Protein folding; Structure prediction

Indexed keywords

HYDROGEN; PEPTIDE; PROTEIN;

ARTICLE; HYDROGEN BOND; KNOWLEDGE BASE; MOLECULAR INTERACTION; OPUS-CA POTENTIAL; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN INTERACTION; PROTEIN STRUCTURE; SOLVATION;

ALGORITHMS; HYDROGEN BONDING; KNOWLEDGE BASES; MODELS, CHEMICAL; PROTEIN CONFORMATION; PROTEINS; THERMODYNAMICS;

EID: 34250829219     PISSN: 09618368     EISSN: 1469896X     Source Type: Journal    
DOI: 10.1110/ps.072796107     Document Type: Article

References (71)

1. Adamian, L. and Liang, J. 2001. Helix-helix packing and interfacial pairwise interactions of residues in membrane proteins. J. Mol. Biol. 311: 891-907.
2. Andrew, C.D., Penel, S., Jones, G.R., and Doig, A.J. 2001. Stabilizing nonpolar/polar side-chain interactions in the α-helix. Proteins 45: 449-455.
3. Bahar, I. and Jernigan, R.L. 1997. Inter-residue potentials in globular proteins and the dominance of highly specific hydrophilic interactions at close separation. J. Mol. Biol. 266: 195-214.
4. Betancourt, M.R. and Thirumalai, D. 1999. Pair potentials for protein folding: Choice of reference states and sensitivity of predicted native states to variations in the interaction schemes. Protein Sci. 8: 361-369.
5. Buchete, N.V., Straub, J.E., and Thirumalai, D. 2004a. Development of novel statistical potentials for protein fold recognition. Curr. Opin. Struct. Biol. 14: 225-232.
6. Buchete, N.V., Straub, J.E., and Thirumalai, D. 2004b. Orientational potentials extracted from protein structures improve native fold recognition. Protein Sci. 13: 862-874.
7. Bystroff, C. 2002. MASKER: Improved solvent-excluded molecular surface area estimations using Boolean masks. Protein Eng. 15: 959-965.
8. Colubri, A., Jha, A.K., Shen, M.Y., Sali, A., Berry, R.S., Sosnick, T.R., and Freed, K.F. 2006. Minimalist representations and the importance of nearest neighbor effects in protein folding simulations. J. Mol. Biol. 363: 835-857.
9. DeBolt, S.E. and Skolnick, J. 1996. Evaluation of atomic level mean force potentials via inverse folding and inverse refinement of protein structures: Atomic burial position and pairwise non-bonded interactions. Protein Eng. 9: 637-655.
10. Dehouck, Y., Gilis, D., and Rooman, M. 2006. A new generation of statistical potentials for proteins. Biophys. J. 90: 4010-4017.
11. Dobson, C.M. and Karplus, M. 1999. The fundamentals of protein folding: Bringing together theory and experiment. Curr. Opin. Struct. Biol. 9: 92-101.
12. Dong, Q., Wang, X., and Lin, L. 2006. Novel knowledge-based mean force potential at the profile level. BMC Bioinformatics 7: 324.
13. Eisenberg, D., Luthy, R., and Bowie, J.U. 1997. VERIFY3D: Assessment of protein models with three-dimensional profiles. Methods Enzymol. 277: 396-404.
14. Fabiola, F., Bertram, R., Korostelev, A., and Chapman, M.S. 2002. An improved hydrogen bond potential: Impact on medium resolution protein structures. Protein Sci. 11: 1415-1423.
15. Feng, Y., Kloczkowski, A., and Jernigan, R.L. 2007. Four-body contact potentials derived from two protein datasets to discriminate native structures from decoys. Proteins doi: 10.1002/prot.21362.
16. Fidelis, K., Stern, P.S., Bacon, D., and Moult, J. 1994. Comparison of systematic search and database methods for constructing segments of protein structure. Protein Eng. 7: 953-960.
17. Gatchell, D.W., Dennis, S., and Vajda, S. 2000. Discrimination of near-native protein structures from misfolded models by empirical free energy functions. Proteins 41: 518-534.
18. Godzik, A., Kolinski, A., and Skolnick, J. 1995. Are proteins ideal mixtures of amino acids? Analysis of energy parameter sets. Protein Sci. 4: 2107-2117.
19. Gohlke, H. and Klebe, G. 2001. Statistical potentials and scoring functions applied to protein-ligand binding. Curr. Opin. Struct. Biol. 11: 231-235.
20. Hendlich, M., Lackner, P., Weitckus, S., Floeckner, H., Froschauer, R., Gottsbacher, K., Casari, G., and Sippl, M.J. 1990. Identification of native protein folds amongst a large number of incorrect models. The calculation of low energy conformations from potentials of mean force. J. Mol. Biol. 216: 167-180.
21. Hinds, D.A. and Levitt, M. 1992. A lattice model for protein structure prediction at low resolution. Proc. Natl. Acad. Sci. 89: 2536-2540.
22. Hubner, I.A., Deeds, E.J., and Shakhnovich, E.I. 2005. High-resolution protein folding with a transferable potential. Proc. Natl. Acad. Sci. 102: 18914-18919.
23. Hutchinson, E.G., Sessions, R.B., Thornton, J.M., and Woolfson, D.N. 1998. Determinants of strand register in antiparallel β-sheets of proteins. Protein Sci. 7: 2287-2300.
24. Jernigan, R.L. and Bahar, I. 1996. Structure-derived potentials and protein simulations. Curr. Opin. Struct. Biol. 6: 195-209.
25. Jones, D.T., Taylor, W.R., and Thornton, J.M. 1992. A new approach to protein fold recognition. Nature 358: 86-89.
26. Kabsch, W. and Sander, C. 1983. Dictionary of protein secondary structure - Pattern-recognition of hydrogen-bonded and geometrical features. Biopolymers 22: 2577-2637.
27. Keasar, C. and Levitt, M. 2003. A novel approach to decoy set generation: Designing a physical energy function having local minima with native structure characteristics. J. Mol. Biol. 329: 159-174.
28. Lazaridis, T. and Karplus, M. 2000. Effective energy functions for protein structure prediction. Curr. Opin. Struct. Biol. 10: 139-145.
29. Liwo, A., Lee, J., Ripoll, D.R., Pillardy, J., and Scheraga, H.A. 1999. Protein structure prediction by global optimization of a potential energy function. Proc. Natl. Acad. Sci. 96: 5482-5485.
30. Loose, C., Klepeis, J.L., and Floudas, C.A. 2004. A new pairwise folding potential based on improved decoy generation and side-chain packing. Proteins 54: 303-314.
31. Lu, H. and Skolnick, J. 2001. A distance-dependent atomic knowledge-based potential for improved protein structure selection. Proteins 44: 223-232.
32. MacKerell, A.D., Bashford Jr., D., Bellott, M., Dunbrack Jr., R.L., Evanseck, J.D., Field, M.J., Fischer, S., Gao, J., Guo, H., Ha, S., et al. 1998. All-atom empirical potential for molecular modeling and dynamics studies of proteins. J. Phys. Chem. B102: 3586-3616.
33. McConkey, B.J., Sobolev, V., and Edelman, M. 2003. Discrimination of native protein structures using atom-atom contact scoring. Proc. Natl. Acad. Sci. 100: 3215-3220.
34. Meller, J. and Elber, R. 2002. Protein recognition by sequence-to-structure fitness: Bridging efficiency and capacity of threading models. Adv. Chem. Phys. 120: 77-130.
35. Melo, F. and Feytmans, E. 1998. Assessing protein structures with a non-local atomic interaction energy. J. Mol. Biol. 277: 1141-1152.
36. Melo, F., Sanchez, R., and Sali, A. 2002. Statistical potentials for fold assessment. Protein Sci. 11: 430-448.
37. Milik, M., Kolinski, A., and Skolnick, J. 1997. Algorithm for rapid reconstruction of protein backbone from a carbon coordinates. J. Comput. Chem. 18: 80-85.
38. Miyazawa, S. and Jernigan, R.L. 1985. Estimation of effective interresidue contact energies from protein crystal-structures - Quasi-chemical approximation. Macromolecules 18: 534-552.
39. Miyazawa, S. and Jernigan, R.L. 1996. Residue-residue potentials with a favorable contact pair term and an unfavorable high packing density term, for simulation and threading. J. Mol. Biol. 256: 623-644.
40. Miyazawa, S. and Jernigan, R.L. 2005. How effective for fold recognition is a potential of mean force that includes relative orientations between contacting residues in proteins? J. Chem. Phys. doi: 10.1063/1.1824012.
41. Moult, J. 1997. Comparison of database potentials and molecular mechanics force fields. Curr. Opin. Struct. Biol. 7: 194-199.
42. Park, B. and Levitt, M. 1996. Energy functions that discriminate X-ray and near native folds from well-constructed decoys. J. Mol. Biol. 258: 367-392.
43. Poole, A.M. and Ranganathan, R. 2006. Knowledge-based potentials in protein design. Curr. Opin. Struct. Biol. 16: 508-513.
44. Qiu, J. and Elber, R. 2005. Atomically detailed potentials to recognize native and approximate protein structures. Proteins 61: 44-55.
45. Rajgaria, R., McAllister, S.R., and Floudas, C.A. 2006. A novel high resolution Ca-Ca distance dependent force field based on a high quality decoy set. Proteins 65: 726-741.
46. Russ, W.P. and Ranganathan, R. 2002. Knowledge-based potential functions in protein design. Curr. Opin. Struct. Biol. 12: 447-452.
47. Samudrala, R. and Moult, J. 1998. An all-atom distance-dependent conditional probability discriminatory function for protein structure prediction. J. Mol. Biol. 275: 895-916.
48. Samudrala, R., Xia, Y., Levitt, M., and Huang, E.S. 1999. A combined approach for ab initio construction of low resolution protein tertiary structures from sequence. Pacific Symposium on Biocomputing 4: 505-516.
49. Shen, M.Y. and Sali, A. 2006. Statistical potential for assessment and prediction of protein structures. Protein Sci. 15: 2507-2524.
50. Shi, Z., Olson, C.A., and Kallenbach, N.R. 2002. Cation-π interaction in model α-helical peptides. J. Am. Chem. Soc. 124: 3284-3291.
51. Simons, K.T., Kooperberg, C., Huang, E., and Baker, D. 1997. Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. J. Mol. Biol. 268: 209-225.
52. Simons, K.T., Ruczinski, I., Kooperberg, C., Fox, B.A., Bystroff, C., and Baker, D. 1999. Improved recognition of native-like protein structures using a combination of sequence-dependent and sequence-independent features of proteins. Proteins 34: 82-95.
53. Sippl, M.J. 1990. Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins. J. Mol. Biol. 213: 859-883.
54. Sippl, M.J. 1995. Knowledge-based potentials for proteins. Curr. Opin. Struct. Biol. 5: 229-235.
55. Skolnick, J. 2006. In quest of an empirical potential for protein structure prediction. Curr. Opin. Struct. Biol. 16: 166-171.
56. Stapley, B.J. and Doig, A.J. 1997. Hydrogen bonding interactions between glutamine and asparagine in α-helical peptides. J. Mol. Biol. 272: 465-473.
57. Steward, R.E. and Thornton, J.M. 2002. Prediction of strand pairing in antiparallel and parallel β-sheets using information theory. Proteins 48: 178-191.
58. Tanaka, S. and Scheraga, H.A. 1976. Medium- and long-range interaction parameters between amino acids for predicting three-dimensional structures of proteins. Macromolecules 9: 945-950.
59. Thomas, P.D. and Dill, K.A. 1996. Statistical potentials extracted from protein structures: How accurate are they? J. Mol. Biol. 257: 457-469.
60. Tobi, D. and Elber, R. 2000. Distance-dependent, pair potential for protein folding: Results from linear optimization. Proteins 41: 40-46.
61. Wang, G. and Dunbrack Jr., R.L. 2003. PISCES: A protein sequence culling server. Bioinformatics 19: 1589-1591.
62. Wodak, S.J. and Janin, J. 1980. Analytical approximation to the accessible surface-area of proteins. Proc. Natl. Acad. Sci. USA 77: 1736-1740.
63. Wu, Y., Chen, M., Lu, M., Wang, Q., and Ma, J. 2005a. Determining protein topology from skeletons of secondary structures. J. Mol. Biol. 350: 571-586.
64. Wu, Y., Tian, X., Lu, M., Chen, M., Wang, Q., and Ma, J. 2005b. Folding of small helical proteins assisted by small-angle X-ray scattering profiles. Structure 13: 1587-1597.
65. Xia, Y., Huang, E.S., Levitt, M., and Samudrala, R. 2000. Ab initio construction of protein tertiary structures using a hierarchical approach. J. Mol. Biol. 300: 171-185.
66. Zhang, C., Vasmatzis, G., Cornette, J.L., and DeLisi, C. 1997. Determination of atomic desolvation energies from the structures of crystallized proteins. J. Mol. Biol. 267: 707-726.
67. Zhang, Y., Kolinski, A., and Skolnick, J. 2003. TOUCHSTONE II: A new approach to ab initio protein structure prediction. Biophys. J. 85: 1145-1164.
68. Zhang, C., Liu, S., Zhou, H., and Zhou, Y. 2004. An accurate, residue-level, pair potential of mean force for folding and binding based on the distance-scaled, ideal-gas reference state. Protein Sci. 13: 400-411.
69. Zhang, J., Chen, R., and Liang, J. 2006. Empirical potential function for simplified protein models: Combining contact and local sequence-structure descriptors. Proteins 63: 949-960.
70. Zhou, H. and Zhou, Y. 2002. Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction. Protein Sci. 11: 2714-2726.
71. Zhou, Y., Zhou, H., Zhang, C., and Liu, S. 2006. What is a desirable statistical energy function for proteins and how can it be obtained? Cell Biochem. Biophys. 46: 165-174.