The Victor/FRST function for model quality estimation

Journal of Computational Biology

Volumn 12, Issue 10, 2005, Pages 1316-1327

  Tosatto, Silvio C E ^a  

^a UNIVERSITY OF PADOVA   (Italy)

Author keywords

Decoy sets; Fold assessment; Fold recognition; Homology modeling; Knowledge based potential; Model evaluation; Statistical potential

Indexed keywords

ARTICLE; COMPARATIVE STUDY; COMPUTER PROGRAM; CORRELATION ANALYSIS; HYDROGEN BOND; MATHEMATICAL MODEL; PREDICTION; PRIORITY JOURNAL; PROBABILITY; PROTEIN ANALYSIS; PROTEIN STRUCTURE; QUALITY CONTROL; SCORING SYSTEM; SOLVATION; STATISTICAL ANALYSIS; TORSION; VICTOR FUNCTION OF RAPDF SOLVATION AND TORSION POTENTIAL FUNCTION; BIOLOGY; CHEMICAL STRUCTURE; CHEMISTRY; KNOWLEDGE BASE; PROTEIN DATABASE; THERMODYNAMICS;

PROTEIN;

COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; HYDROGEN BONDING; KNOWLEDGE BASES; MODELS, MOLECULAR; MOLECULAR STRUCTURE; PROTEINS; THERMODYNAMICS;

EID: 28144448406     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.2005.12.1316     Document Type: Article

References (40)

1. Albrecht, M., Tosatto, S.C.E., Lengauer, T., and Valle, G. 2003. Simple consensus procedures are effective and sufficient in secondary structure prediction. Protein Eng. 16, 459-462.
2. Berman, H.M., Battistuz, T., Bhat, T.N., et al. 2002. The Protein Data Bank. Acta Crystallogr. D Biol. Crystallogr. 58, 899-907.
3. Berrera, M., Molinari, H., and Fogolari, F. 2003. Amino acid empirical contact energy definitions for fold recognition in the space of contact maps. BMC Bioinformatics 4, 8.
4. Bindewald, E., Cestaro, A., Hesser, J., Heiler, M., and Tosatto, S.C.E. 2003. MANIFOLD: Protein fold recognition based on secondary structure, sequence similarity and enzyme classification. Protein Eng. 16, 785-789.
5. Colovos, C., and Yeates, T.O. 1993. Verification of protein structures: Patterns of nonbonded atomic interactions. Protein Sci. 2, 1511-1519.
6. Eisenberg, D., Luthy, R., and Bowie, J.U. 1997. VERIFY3D: Assessment of protein models with three-dimensional profiles. Methods Enzymol. 277, 396-404.
7. Fischer, D., Barret, C., Bryson, K., et al., 1999. CAFASP-1: Critical assessment of fully automated structure prediction methods. Proteins Suppl. 3, 209-217.
8. Fischer, D., Elofsson, A., Rychlewski, L., Pazos, F., Valencia, A., Rost, B., Ortiz, A.R., and Dunbrack, R.L., Jr. 2001. CAFASP2: The second critical assessment of fully automated structure prediction methods. Proteins Suppl. 5, 171-183.
9. Fischer, D., Rychlewski, L., Dunbrack, R.L., Jr., Ortiz, A.R., and Elofsson, A. 2003. CAFASP3: The third critical assessment of fully automated structure prediction methods. Proteins 53, Suppl. 6, 503-516.
10. Fogolari, F., and Tosatto, S.C.E. 2005. Application of MM/PBSA colony free energy to loop decoy discrimination: Towards correlation between energy and root mean square deviation. Protein Sci. In press.
11. Hao, M.H., and Scheraga, H.A. 1998. Molecular mechanisms for cooperative folding of proteins. J. Mol. Biol. 277, 973-983.
12. Jones, D.T. 1999. GenTHREADER: An efficient and reliable protein fold recognition method for genomic sequences. J. Mol. Biol. 287, 797-815.
13. 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.
14. Krishnamoorthy, B., and Tropsha, A. 2003. Development of a four-body statistical pseudo-potential to discriminate native from non-native protein conformations. Bioinformatics 19, 1540-1548.
15. Laskowski, R., MacArthur, M.W., Moss, D., and Thornton, J. 1993. Procheck: A program to check the stereochemical quality of protein structures. J. Appl. Cryst. 26, 283-291.
16. Lazaridis, T., and Karplus, M. 1999. Discrimination of the native from misfolded protein models with an energy function including implicit solvution. J. Mol. Biol. 288, 477-487.
17. Lovell, S.C., Davis, I.W., Arendall, W.B.R., de Bakker, P.I., Word, J.M., Prisant, M.G., Richardson, J.S., and Richardson, D.C. 2003. Structure validation by Calpha geometry: phi,psi and Cbeta deviation. Proteins 50, 437-450.
18. Lu, H., and Skolnick, J. 2001. A distance-dependent atomic knowledge-based potential for improved protein structure selection. Protein 44, 223-232.
19. Luthy, R., Bowie, J.U., and Eisenberg, D. 1992. Assessment of protein models with three-dimensional profiles. Nature 356, 83-85.
20. Melo, F., Sanchez, R., and Sali, A. 2002. Statistical potentials for fold assessment. Protein Sci. 11, 430-448.
21. Miyazawa, S., and Jernigan, R.L. 2003. Long- and short-range interactions in native protein structures are consistent/minimally frustrated in sequence space. Proteins 50, 35-43.
22. Moult, J., Fidelis, K., Zemla, A., and Hubbard, T. 2001. Critical assessment of methods of protein structure prediction (CASP): Round IV. Proteins Suppl. 5, 2-7.
23. 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.
24. Ptrey, D., and Honig, B. 2000. Free energy determinants of tertiary structure and the evaluation of protein models. Protein Sci. 9. 2181-2191.
25. Ramachandran, G.N., Ramakrishnan, C., and Sasisekharan, V. 1963. Stereochemistry of polypeptide chain configurations. J. Mol. Biol., 7, 95-99.
26. Samudrala, R., and Levitt, M. 2000. Decoys 'R' Us: A database of incorrect conformations to improve protein structure prediction. Protein Sci. 9, 1399-1401.
27. 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.
28. Shortle, D. 2002. Composites of local structure propensities: Evidence for local encoding of long-range structure. Protein Sci. 11, 18-26.
29. Shortle, D. 2003. Propensities, probabilities, and the Boltzmann hypothesis. Protein Sci. 12, 1298-1302.
30. Siew, N., Elofsson, A., Rychlewski, L., and Fischer, D. 2000. MaxSub: An automated measure for the assessment of protein structure prediction quality. Bioinformatics 16, 776-785.
31. Sippl, M.J. 1993a. Boltzmann's principle, knowledge-based mean fields and protein folding. An approach to the computational determination of protein structures. J. Comput. Aided Mol. Des. 7, 473-501.
32. Sippl, M.J. 1993b. Recognition of errors in three-dimensional structures of proteins. Proteins 17, 355-362.
33. Tosatto, S.C.E., Bindewald, E., Hesser, J., and Männer, R. 2002. A divide and conquer approach to fast loop modeling. Protein Eng. 15, 279-286.
34. Valencia, A. 2005. Protein refinement: A new challenge for casp in its 10th anniversary, Bioinformatics 21, 277.
35. Wallner, B., and Elofsson, A. 2003. Can correct protein models be identified? Protein Sci. 12, 1073-1086.
36. Wang, K., Fain, B., Levitt, M., and Samudrala, R. 2004. Improved protein structure selection using decoy-dependent discriminatory functions. BMC Struct. Biol. 4, 8.
37. 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.
38. Zemla, A. 2003. LGA: A method for finding 3D similarities in protein structures. Nucl. Acids Res. 31, 3370-3374.
39. 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.
40. 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.