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Derivation and Testing Residue-Residue Mean-Force Potentials for Use in Protein Structure Prediction

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Protein Structure Prediction

Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 143))

Abstract

In protein-structure prediction, simplified energy functions are necessarily used to allow fast sorting over many conformations. As a rule, these functions are derived from residue-residue approximation, which attributes all atomic interactions between residues to a single point within each residue. Physically, the simplified energies should result from averaging of the atomic interactions over various positions and conformations of the interacting amino acid residues, as well as the surrounding solvent molecules. Unfortunately, direct calculation of such mean-force potentials is not possible today both because of methodological difficulties and the lack of reliable atom-based energy functions.

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References

  1. Sippl, M. (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.

    Article  PubMed  CAS  Google Scholar 

  2. Vajda, S., Sippl, M., and Novotny, J. (1997) Empirical potentials and functions for protein folding and binding. Curr. Opin. Struct. Biol. 7(2), 222–228.

    Article  PubMed  CAS  Google Scholar 

  3. Thomas, P. D. and Dill, K. A. (1996) Statistical potentials extracted from protein structures: how accurate are they? J. Mol. Biol. 257, 457–469.

    Article  PubMed  CAS  Google Scholar 

  4. Godzik, A., Kolinski, A., and Skolnick, J. (1995) Are proteins ideal mixtures of amino acids? Analysis of energy parameter sets. Prot. Sci. 4, 2107–2117.

    Article  CAS  Google Scholar 

  5. Jernigan, R. and Bahar, I. (1996) Structure-derived potentials and protein simulations. Curr. Opin. Struct. Biol. 6, 195–209.

    Article  PubMed  CAS  Google Scholar 

  6. Rooman, J. and Wodak, S. (1995) Are database-derived potentials valid for scoring both forward and inverted protein folding? Protein Eng. 8, 849–858.

    Article  PubMed  CAS  Google Scholar 

  7. Skolnick, J., Jaroszewski, L., Kolinski, A., and Godzik, A. (1997) Derivation and testing of pair potentials for protein folding. When is the quasichemical approximation correct? Prot. Sci. 6(3), 676–688.

    Article  CAS  Google Scholar 

  8. Kocher, J. P., Rooman M. J., and Wodak S. J. (1994) Factors influencing the ability of knowledge-based potentials to identify native sequence-structure matches. J. Mol. Biol. 235(5), 1598–1613.

    Article  PubMed  CAS  Google Scholar 

  9. Pohl, F. M. (1971) Empirical protein energy maps. Nat. New Biol. 234, 277–279.

    PubMed  CAS  Google Scholar 

  10. Finkelstein, A., Badretdinov, A., and Gutin, A. (1995) Why do protein architectures have Boltzmann-like statistics? Proteins 23, 142–150.

    Article  PubMed  CAS  Google Scholar 

  11. Reva, B. A., Finkelstein, A. V., Sanner, M. F., and Olson, A. J. (1997) Accurate mean-force pairwise-residue potentials for discrimination of protein folds, in Proceedings of Pacific Symposium on Biomolecular Computations, 373–384.

    Google Scholar 

  12. Reva, B. A., Finkelstein, A. V., Sanner, M. F., and Olson, A. J. (1997) Residueresidue mean-force potentials for protein structure recognition. Protein Eng. 10(5), 865–876.

    Article  PubMed  CAS  Google Scholar 

  13. Hobohm, U., Scharf, M., Schneider, R., and Sander, C. (1992) Selection of representative protein data sets. Prot. Sci. 1, 409–417.

    Article  CAS  Google Scholar 

  14. Smith, T. and Waterman, M. (1981) Identification of common molecular subsequences. J. Mol. Biol. 147, 195–197.

    Article  PubMed  CAS  Google Scholar 

  15. Murzin, A., Brenner, S., Hubbard, T., and Chothia, C. (1995) SCOP: a structural classification of proteins database for the investigation of sequences and structures. J. Mol. Biol. 247, 536–540.

    PubMed  CAS  Google Scholar 

  16. Ben-Naim, A. (1997) Statistical potentials extracted from protein structures: are these meaningful potentials? J. Chem. Phys. 107(9), 3698–3706.

    Article  CAS  Google Scholar 

  17. Hendlich, M., Lackner, P., Weitckus, S., Floeckner, H., Froschauer, R., Gottsbacher, K., Casari, G., and Sippl, M. (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.

    Article  PubMed  CAS  Google Scholar 

  18. Shakhnovich, E. I. and Gutin, A. M. (1989) Formation of unique structure in polypeptide chain. Theoretical investigation with the aid of a replica approach. Biophys. Chem. 34, 187–199.

    Article  PubMed  CAS  Google Scholar 

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© 2000 Humana Press Inc.

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Reva, B.A., Finkelstein, A.V., Skolnick, J. (2000). Derivation and Testing Residue-Residue Mean-Force Potentials for Use in Protein Structure Prediction. In: Webster, D.M. (eds) Protein Structure Prediction. Methods in Molecular Biology™, vol 143. Humana Press. https://doi.org/10.1385/1-59259-368-2:155

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  • DOI: https://doi.org/10.1385/1-59259-368-2:155

  • Publisher Name: Humana Press

  • Print ISBN: 978-0-89603-637-6

  • Online ISBN: 978-1-59259-368-2

  • eBook Packages: Springer Protocols

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