iSPOT: a web tool for the analysis and recognition of protein domain specificity

Methods that aim at predicting interaction partners are very likely to play an important role in the interpretation of genomic information. iSPOT (iSpecificity Prediction Of Target) is a web tool (accessible at http://cbm.bio.uniroma2.it/iSPOT) developed for the prediction of protein-protein interaction mediated by families of peptide recognition modules. iSPOT accesses a database of position specific residue-residue interaction frequencies for members of the SH3 and PDZ protein domain families. The software utilises this database to provide a score for any potential domain peptide interaction.

iSPOT: 1. evaluates the likelihood of the interaction between any of the peptides contained in an input protein and a list of domains of the two different families; 2. searches in the SWISS-PROT database for potential partners of a query domain; and 3. has access to a repository of all the domain/target peptide interaction data.

The IntAct molecular interaction database in 2010

IntAct is an open-source, open data molecular interaction database and toolkit. Data is abstracted from the literature or from direct data depositions by expert curators following a deep annotation model providing a high level of detail. As of September 2009, IntAct contains over 200.000 curated binary interaction evidences. In response to the growing data volume and user requests, IntAct now provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows 'zooming in' on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.

IntAct--open source resource for molecular interaction data

IntAct is an open source database and software suite for modeling, storing and analyzing molecular interaction data. The data available in the database originates entirely from published literature and is manually annotated by expert biologists to a high level of detail, including experimental methods, conditions and interacting domains. The database features over 126 000 binary interactions extracted from over 2100 scientific publications and makes extensive use of controlled vocabularies. The web site provides tools allowing users to search, visualize and download data from the repository. IntAct supports and encourages local installations as well as direct data submission and curation collaborations. IntAct source code and data are freely available from .

Distinct binding specificity of the multiple PDZ domains of INADL, a human protein with homology to INAD from Drosophila melanogaster

PDZ domains are protein-protein interaction modules that typically bind to short peptide sequences at the carboxyl terminus of target proteins. Proteins containing multiple PDZ domains often bind to different trans-membrane and intracellular proteins, playing a central role as organizers of multimeric complexes. To characterize the rules underlying the binding specificity of different PDZ domains, we have assembled a novel repertoire of random peptides that are displayed at high density at the carboxyl terminus of the capsid D protein of bacteriophage lambda. We have exploited this combinatorial library to determine the peptide binding preference of the seven PDZ domains of human INADL, a multi-PDZ protein that is homologous to the INAD protein of Drosophila melanogaster. This approach has permitted the determination of the consensus ligand for each PDZ domain and the assignment to class I, class II, and to a new specificity class, class IV, characterized by the presence of an acidic residue at the carboxyl-terminal position. Homology modeling and site-directed mutagenesis experiments confirmed the involvement of specific residues at contact positions in determining the domain binding preference. However, these experiments failed to reveal simple rules that would permit the association of the chemical characteristics of any given residue in the peptide binding pocket to the preference for specific amino acid sequences in the ligand peptide. Rather, they suggested that to infer the binding preference of any PDZ domain, it is necessary to simultaneously take into account all contact positions by using computational procedures. For this purpose we extended the SPOT algorithm, originally developed for SH3 domains, to evaluate the probability that any peptide would bind to any given PDZ domain.