title: SH3-SPOT: an algorithm to predict preferred ligands to different members of the SH3 gene family.
abstract: We have developed a procedure to predict the peptide binding specificity of an SH3 domain from its sequence. The procedure utilizes information extracted from position-specific contacts derived from six SH3/peptide or SH3/protein complexes of known structure. The framework of SH3/peptide contacts defined on the structure of the complexes is used to build a residue-residue interaction database derived from ligands obtained by panning peptide libraries displayed on filamentous phage. The SH3-specific interaction database is a multidimensional array containing frequencies of position-specific contacts. As input, SH3-SPOT requires the sequence of an SH3 domain and of a query decapeptide ligand. The array, that we call the SH3-specific matrix, is then used to evaluate the probability that the peptide would bind the given SH3 domain. This procedure is fast enough to be applied to the entire protein sequence database. Panning experiments were performed to search putative specific ligands of different SH3 domains in a database of decapeptides, or in a database of protein sequences. The procedure ranked some of the natural partners of interaction of a number of SH3 domains among the best ligands of the approximately 5. 6x10(9) different decapeptides in the SWISSPROT database. We expect the predictive power of the method to increase with the enrichment of the SH3-specific matrix by interaction data derived from new complex structures or from the characterization of new ligands. The procedure was developed using the SH3 domain family as test case but its application can easily be extended to other families of protein domains (such as, SH2, MHC, EH, PDZ, etc.).
authors.affiliation: Department of Biology, Centro di Bioinformatica Molecolare, University of Rome, Tor Vergata, Rome, 00133, Italy.
authors.forename: B
authors.initials: B
authors.lastname: Brannetti
authors.forename: A
authors.initials: A
authors.lastname: Via
authors.forename: G
authors.initials: G
authors.lastname: Cestra
authors.forename: G
authors.initials: G
authors.lastname: Cesareni
authors.forename: M
authors.initials: M
authors.lastname: Helmer-Citterich
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D008969:Molecular Sequence Data; D005810:Multigene Family / Q000235:genetics; D010446:Peptide Fragments / Q000737:chemistry / Q000235:genetics / Q000378:metabolism; D019151:Peptide Library; D011336:Probability; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism*; D016415:Sequence Alignment; D013379:Substrate Specificity; D018909:src Homology Domains
chemical_list: D008024:Ligands; D010446:Peptide Fragments; D019151:Peptide Library; D011506:Proteins