title: InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale.
abstract: We propose InSite, a computational method that integrates high-throughput protein and sequence data to infer the specific binding regions of interacting protein pairs. We compared our predictions with binding sites in Protein Data Bank and found significantly more binding events occur at sites we predicted. Several regions containing disease-causing mutations or cancer polymorphisms in human are predicted to be binding for protein pairs related to the disease, which suggests novel mechanistic hypotheses for several diseases.
authors.affiliation: Computer Science Department, Stanford University, Serra Mall, Stanford, CA 94305, USA. haidong@cs.stanford.edu
authors.forename: Haidong
authors.initials: H
authors.lastname: Wang
authors.forename: Eran
authors.initials: E
authors.lastname: Segal
authors.forename: Asa
authors.initials: A
authors.lastname: Ben-Hur
authors.forename: Qian-Ru
authors.initials: QR
authors.lastname: Li
authors.forename: Marc
authors.initials: M
authors.lastname: Vidal
authors.forename: Daphne
authors.initials: D
authors.lastname: Koller
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D030562:Databases, Protein; D001330:Electronic Data Processing; D020869:Gene Expression Profiling; D006801:Humans; D011110:Polymorphism, Genetic; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D020543:Proteome; D040901:Proteomics; D012441:Saccharomyces cerevisiae / Q000378:metabolism; D012984:Software; D020798:Two-Hybrid System Techniques
chemical_list: D020543:Proteome