Advertisement

Protein Design pp 207-234 | Cite as

Prediction of Protein–Protein Interaction Based on Structure

  • Gregorio Fernandez-Ballester
  • Luis Serrano
Part of the Methods in Molecular Biology book series (MIMB, volume 340)

Abstract

A great challenge in the proteomics and structural genomics era is to predict protein structure and function from sequence, including the identification of biological partners. The development of a procedure to construct position-specific scoring matrices for the prediction and identification of sequences with putative significant affinity faces this challenge. The local and web applications used for sequence and structure search, sequence alignment, protein modeling, molecule edition and modification, and scoring matrices construction are described in detail. The methodology is based on the information contained in structural databases and takes into account the subtle conformational and sequence details that characterize different structures within a family. Using the matrices, the protein sequence databases can be easily scanned to locate putative partners of biological significance. The success of this methodology opens the way for the prediction of protein-protein interaction at genome scale.

Key Words

Bioinformatics protein–protein interaction protein modeling protein prediction positional scoring matrix pattern search 

References

  1. 1.
    Lo, C. L., Chothia, C., and Janin, J. (1999) The atomic structure of protein-protein recognition sites. J. Mol. Biol. 285, 2177–2198.CrossRefGoogle Scholar
  2. 2.
    Valdar, W. S. and Thornton, J. M. (2001) Protein-protein interfaces: analysis of amino acid conservation in homodimers. Proteins 42, 108–124.PubMedCrossRefGoogle Scholar
  3. 3.
    Jones, S. and Thornton, J. M. (1997) Analysis of protein-protein interaction sites using surface patches. J. Mol. Biol. 272, 121–132.PubMedCrossRefGoogle Scholar
  4. 4.
    Jones, S. and Thornton, J. M. (1997) Prediction of protein-protein interaction sites using patch analysis. J. Mol. Biol. 272, 133–143.PubMedCrossRefGoogle Scholar
  5. 5.
    Aloy, P., Querol, E., Aviles, F. X., and Sternberg, M. J. (2001) Automated structure-based prediction of functional sites in proteins: applications to assessing the validity of inheriting protein function from homology in genome annotation and to protein docking. J. Mol. Biol. 311, 395–408.PubMedCrossRefGoogle Scholar
  6. 6.
    Stein, A., Russell, R. B., and Aloy, P. (2005) 3did: interacting protein domains of known three-dimensional structure. Nucleic Acids Res. 33, D413–D417.PubMedCrossRefGoogle Scholar
  7. 7.
    Aloy, P., Bottcher, B., Ceulemans, H., Leutwein, C., Mellwig, C., Fischer, S., et al. (2004) Structure-based assembly of protein complexes in yeast. Science 303, 2026–2029.PubMedCrossRefGoogle Scholar
  8. 8.
    Brannetti, B., Via, A., Cestra, G., Cesareni, G., and Helmer-Citterich, M. (2000)SH3-SPOT: an algorithm to predict preferred ligands to different members of the SH3 gene family. J. Mol. Biol. 298, 313–328.PubMedCrossRefGoogle Scholar
  9. 9.
    Wollacott, A. M. and Desjarlais, J. R. (2001) Virtual interaction profiles of proteins. J. Mol. Biol. 313, 317–342.PubMedCrossRefGoogle Scholar
  10. 10.
    Meng, E. C., Gschwend, D. A., Blaney, J. M., and Kuntz, I. D. (1993) Orientational sampling and rigid-body minimization in molecular docking. Proteins 17, 266–278.PubMedCrossRefGoogle Scholar
  11. 11.
    Lichtarge, O. and Sowa, M. E. (2002) Evolutionary predictions of binding surfaces and interactions. Curr. Opin. Struct. Biol. 12, 21–27.PubMedCrossRefGoogle Scholar
  12. 12.
    Bogan, A. A. and Thorn, K. S. (1998) Anatomy of hot spots in protein interfaces. J. Mol. Biol. 280, 1–9.PubMedCrossRefGoogle Scholar
  13. 13.
    Schreiber, G. and Fersht, A. R. (1995) Energetics of protein-protein interactions:analysis of the barnase-barstar interface by single mutations and double mutant cycles. J. Mol. Biol. 248, 478–486.PubMedGoogle Scholar
  14. 14.
    Janin, J. and Chothia, C. (1990) The structure of protein-protein recognition sites. J. Biol. Chem. 265, 16027–16030.PubMedGoogle Scholar
  15. 15.
    Janin, J. (1995) Principles of protein-protein recognition from structure to thermodynamics. Biochimie 77, 497–505.PubMedCrossRefGoogle Scholar
  16. 16.
    Jones, S. and Thornton, J. M. (1996) Principles of protein-protein interactions. Proc. Natl. Acad. Sci. USA 93, 13–20.PubMedCrossRefGoogle Scholar
  17. 17.
    Tsai, C. J., Lin, S. L., Wolfson, H. J., and Nussinov, R. (1996) A dataset of protein-protein interfaces generated with a sequence-order-independent comparison technique. J. Mol. Biol. 260, 604–620.PubMedCrossRefGoogle Scholar
  18. 18.
    Tsai, C. S. (2002) Molecular modelling: protein modelling, in An Introduction to Computational Biochemistry (Han L., ed.), John Wiley & Sons, Inc., New York, pp. 315–342.CrossRefGoogle Scholar
  19. 19.
    Letunic, I., Copley, R. R., Schmidt, S., Ciccarelli, F. D., Doerks, T., Schultz, J., et al. (2004) SMART 4.0: towards genomic data integration. Nucleic Acids Res. 32,D142–D144.PubMedCrossRefGoogle Scholar
  20. 20.
    Guex, N. and Peitsch, M. C. (1997) SWISS-MODEL and the Swiss-PdbViewer:an environment for comparative protein modeling. Electrophoresis 18, 2714–2723.PubMedCrossRefGoogle Scholar
  21. 21.
    van Gunsteren, W. F. and Mark, A. E. (1992) Prediction of the activity and stability effects of site-directed mutagenesis on a protein core. J. Mol. Biol. 227, 389–395.PubMedCrossRefGoogle Scholar
  22. 22.
    Northey, J. G., Di Nardo, A. A., and Davidson, A. R. (2002) Hydrophobic core packing in the SH3 domain folding transition state. Nat. Struct. Biol. 9, 126–130.PubMedCrossRefGoogle Scholar
  23. 23.
    Larson, S. M. and Davidson, A. R. (2000) The identification of conserved interactions within the SH3 domain by alignment of sequences and structures. Protein Sci. 9, 2170–2180.PubMedCrossRefGoogle Scholar
  24. 24.
    Fernandez-Ballester, G., Blanes-Mira, C., and Serrano, L. (2004) The tryptophan switch: changing ligand-binding specificity from type I to type II in SH3 domains. J. Mol. Biol. 335, 619–629.PubMedCrossRefGoogle Scholar
  25. 25.
    Cesareni, G., Panni, S., Nardelli, G., and Castagnoli, L. (2002) Can we infer peptide recognition specificity mediated by SH3 domains? FEBS Lett. 513, 38–44.PubMedCrossRefGoogle Scholar
  26. 26.
    Hilbert, M., Bohm, G., and Jaenicke, R. (1993) Structural relationships of homologous proteins as a fundamental principle in homology modeling. Proteins 17,138–151.PubMedCrossRefGoogle Scholar
  27. 27.
    Chinea, G., Padron, G., Hooft, R. W., Sander, C., and Vriend, G. (1995) The use of position-specific rotamers in model building by homology. Proteins 23, 415–421.PubMedCrossRefGoogle Scholar
  28. 28.
    Bonneau, R. and Baker, D. (2001) Ab initio protein structure prediction: progress and prospects. Annu. Rev. Biophys. Biomol. Struct. 30, 173–189.PubMedCrossRefGoogle Scholar
  29. 29.
    Bryant, S. H. and Altschul, S. F. (1995) Statistics of sequence-structure threading. Curr. Opin. Struct. Biol. 5, 236–244.PubMedCrossRefGoogle Scholar
  30. 30.
    Murphy, K. P. and Freire, E. (1992) Thermodynamics of structural stability and cooperative folding behavior in proteins. Adv. Protein Chem. 43, 313–361.PubMedCrossRefGoogle Scholar
  31. 31.
    Pace, C. N., Shirley, B. A., McNutt, M., and Gajiwala, K. (1996) Forces contributing to the conformational stability of proteins. FASEB J. 10, 75–83.PubMedGoogle Scholar
  32. 32.
    Sippl, M. J. (1995) Knowledge-based potentials for proteins. Curr. Opin. Struct.Biol. 5, 229–235.PubMedCrossRefGoogle Scholar
  33. 33.
    Topham, C. M., Srinivasan, N., and Blundell, T. L. (1997) Prediction of the stability of protein mutants based on structural environment-dependent amino acid substitution and propensity tables. Protein Eng. 10, 7–21.PubMedCrossRefGoogle Scholar
  34. 34.
    Bordo, D. and Argos, P. (1991) Suggestions for &quote;safe&quote; residue substitutions in site-directed mutagenesis. J. Mol. Biol. 217, 721–729.PubMedCrossRefGoogle Scholar
  35. 35.
    Prevost, M., Wodak, S. J., Tidor, B., and Karplus, M. (1991) Contribution of the hydrophobic effect to protein stability: analysis based on simulations of the Ile-96–Ala mutation in barnase. Proc. Natl. Acad. Sci. USA 88, 10880–10884.PubMedCrossRefGoogle Scholar
  36. 36.
    Pitera, J. W. and Kollman, P. A. (2000) Exhaustive mutagenesis in silico:multicoordinate free energy calculations on proteins and peptides. Proteins 41,385–397.PubMedCrossRefGoogle Scholar
  37. 37.
    Guerois, R., Nielsen, J. E., and Serrano, L. (2002) Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. J. Mol.Biol. 320, 369–387.PubMedCrossRefGoogle Scholar
  38. 38.
    Kiel, C., Serrano, L., and Herrmann, C. (2004) A detailed thermodynamic analysis of ras/effector complex interfaces. J. Mol. Biol. 340, 1039–1058.PubMedCrossRefGoogle Scholar
  39. 39.
    Vijayakumar, M., Wong, K. Y., Schreiber, G., Fersht, A. R., Szabo, A., and Zhou, H. X. (1998) Electrostatic enhancement of diffusion-controlled protein-protein association: comparison of theory and experiment on barnase and barstar. J. Mol.Biol. 278, 1015–1024.PubMedCrossRefGoogle Scholar
  40. 40.
    Kuntz, I. D., Blaney, J. M., Oatley, S. J., Langridge, R., and Ferrin, T. E. (1982) A geometric approach to macromolecule-ligand interactions. J. Mol. Biol. 161,269–288.PubMedCrossRefGoogle Scholar
  41. 41.
    Morris, G. M., Goodsell, D. S., Huey, R., and Olson, A. J. (1996) Distributed automated docking of flexible ligands to proteins: parallel applications of AutoDock 2.4. J. Comput. Aided Mol. Des. 10, 293–304.PubMedCrossRefGoogle Scholar
  42. 42.
    Jones, G., Willett, P., Glen, R. C., Leach, A. R., and Taylor, R. (1997) Development and validation of a genetic algorithm for flexible docking. J. Mol. Biol. 267, 727–748.PubMedCrossRefGoogle Scholar
  43. 43.
    Ewing, T. J., Makino, S., Skillman, A. G., and Kuntz, I. D. (2001) DOCK 4.0:search strategies for automated molecular docking of flexible molecule databases. J. Comput. Aided Mol. Des. 15, 411–428.PubMedCrossRefGoogle Scholar
  44. 44.
    Rarey, M., Kramer, B., Lengauer, T., and Klebe, G. (1996) A fast flexible docking method using an incremental construction algorithm. J. Mol. Biol. 261, 470–489.PubMedCrossRefGoogle Scholar
  45. 45.
    Bohm, H. J. (1992) The computer program LUDI: a new method for the de novo design of enzyme inhibitors. J. Comput. Aided Mol. Des. 6, 61–78.PubMedCrossRefGoogle Scholar
  46. 46.
    Bohacek, R. S. and McMartin, C. (1997) Modern computational chemistry and drug discovery: structure generating programs. Curr. Opin. Chem. Biol. 1, 157–161.PubMedCrossRefGoogle Scholar
  47. 47.
    Jones, D. and Thornton, J. (1993) Protein fold recognition. J. Comput. Aided Mol.Des. 7, 439–456.PubMedCrossRefGoogle Scholar
  48. 48.
    Gattiker, A., Gasteiger, E., and Bairoch, A. (2002) ScanProsite: a reference implementation of a PROSITE scanning tool. Appl. Bioinformatics 1, 107–108.PubMedGoogle Scholar
  49. 49.
    Tong A. H., Drees B., Nardelli G., Bader G. D., Brannetti B., Castagnoli L., et al. (2002) A combined experimental and computational strategy to define protein interaction networks for peptide recognition modules. Science 295, 321–324.PubMedCrossRefGoogle Scholar
  50. 50.
    Beltrao, P. and Serrano, L. (2005) Comparative genomics and disorder prediction identity biologically relevant SH3 protein interactions. PLoS Comput. Biol. 1, e26.PubMedCrossRefGoogle Scholar

Copyright information

© Humana Press Inc. 2006

Authors and Affiliations

  • Gregorio Fernandez-Ballester
    • 1
  • Luis Serrano
    • 2
  1. 1.IBMC-Universidad Miguel HernándezElche (Alicante)Spain
  2. 2.Structural Biology and BiocomputingEuropean Molecular Biology LaboratoryHeidelbergGermany

Personalised recommendations