Abstract
Most of the cellular functions are the result of the concerted action of protein complexes forming pathways and networks. For this reason, efforts were devoted to the study of protein-protein interactions. Large-scale experiments on whole genomes allowed the identification of interacting protein pairs. However residues involved in the interaction are generally not known and the majority of the interactions still lack a structural characterization. A crucial step towards the deciphering of the interaction mechanism of proteins is the recognition of their interacting surfaces, particularly in those structures for which also the most recent interaction network resources do not contain information. To this purpose, we developed a neural network-based method that is able to characterize protein complexes, by predicting amino acid residues that mediate the interactions. All the Protein Data Bank (PDB) chains, both in the unbound and in the complexed form, are predicted and the results are stored in a database of interaction surfaces (http://gpcr.biocomp.unibo.it/zenpatches). Finally, we performed a survey on the different computational methods for protein-protein interaction prediction and on their training/testing sets in order to highlight the most informative properties of protein interfaces.
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References
Chothia, C., Janin, J.: Principles of protein-protein recognition. Nature 256, 705–708 (1975)
Jones, S., Thornton, J.M.: Prediction of protein-protein interaction sites using patch analysis. J. Mol. Biol. 272, 133–143 (1997)
Zhou, H., Qin, S.: Interaction site prediction for protein complexes: a critical assessment. Bioinformatics 21, 2469–2501 (2007)
De Vries, S.J., Bonvin, A.M.: How proteins get in touch: interface prediction in the study of biomolecular complexes. Curr. Protein Pept. Sci. 9, 394–406 (2008)
Ezkurdia, I., Bartoli, L., Fariselli, P., Casadio, R., Valencia, A., Tress, M.L.: Progress and challenges in predicting protein-protein interaction sites. Briefings in Bioinformatics 10(3), 233–246 (2009)
Fu, H.: Protein-Protein Interactions: Methods and Applications (Methods in Molecular Biology). Humana Press Inc., New York
Katchalski-Katzir, E., Shariv, I., Eisenstein, M., Friesem, A.A., Aflalo, C., Vakser, I.A.: Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques. Proc. Natl. Acad. Sci. USA 89, 2195–2199 (1992)
Berezin, C., Glaser, F., Rosenberg, J., Paz, I., Pupko, T., Fariselli, P., Casadio, R., Ben-Tal, N.: ConSeq: the identification of functionally and structurally important residues in protein sequence. Bioinformatics 20, 1322–1324 (2004)
Nooren, I., Thornton, J.M.: Structural characterization and functional significance of transient protein-protein interactions. J. Mol. Biol. 325, 991–1018 (2003)
Fariselli, P., Pazos, F., Valencia, A., Casadio, R.: Prediction of protein-protein interaction sites in heterocomplexes with neural networks. Eur. J. Biochem. 269, 1356–1361 (2002)
Fariselli, P., Zauli, A., Rossi, I., Finelli, M., Martelli, P.L., Casadio, R.: A neural network method to improve prediction of protein-protein interaction sites in heterocomplexes. In: IEEE International Workshop on Neural Network on Signal Processing 2003, Toulouse, France, pp. 33–41. IEEE Press, Los Alamitos (2003)
Ofran, Y., Rost, B.: ISIS: interaction sites identified from sequence. Bioinformatics 23, 13–16 (2007)
Rost, B.: Prediction in 1D: Secondary structure, membrane helices, and accessibility. In: Bourne, P., Weissig, H. (eds.) Structural bioinformatics. Wiley-Liss, Hoboken (2002)
Porollo, A., Meller, J.: Prediction-based fingerprints of protein-protein interactions. Proteins 66, 630–645 (2007)
Dong, Q., Wang, X., Lin, L., Guan, Y.: Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins. BMC Bioinform. 8, 147 (2007)
Chung, J., Wang, W., Bourne, P.E.: Exploiting sequence and structure homologs to identify protein-protein binding sites. Proteins 62, 630–640 (2006)
Li, J.J., Huang, D., Wang, B., Chen, P.: Identifying protein-protein interfacial residues in heterocomplexes using residue conservation scores. Int. J. Biol. Macromol. 38, 241–247 (2006)
Wang, B., Chen, P., Huang, D., Li, J.J., Lok, T.M., Lyu, M.R.: Predicting protein interaction sites from residue spatial sequence profile and evolution rate. FEBS Lett. 580, 380–384 (2006)
Bordner, A.J., Abagyan, R.: Statistical analysis and prediction of protein-protein interfaces. Proteins 60, 353–366 (2005)
Li, M., Lin, L., Wang, X.L., Liu, T.: Protein-protein interaction site prediction based on conditional random fields. Bioinformatics 23, 597–604 (2007)
Zhou, H.X., Shan, Y.: Prediction of protein interaction sites from sequence profile and residue neighbor list. Proteins 44, 336–343 (2001)
Chen, H., Zhou, H.: Prediction of interface residues in protein-protein complexes by a consensus neural network method: test against NMR data. Proteins 61, 21–35 (2005)
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Bartoli, L., Martelli, P.L., Rossi, I., Fariselli, P., Casadio, R. (2009). Prediction of Protein-Protein Interacting Sites: How to Bridge Molecular Events to Large Scale Protein Interaction Networks. In: Degano, P., Gorrieri, R. (eds) Computational Methods in Systems Biology. CMSB 2009. Lecture Notes in Computer Science(), vol 5688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03845-7_1
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DOI: https://doi.org/10.1007/978-3-642-03845-7_1
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