Inferred Biomolecular Interaction Server (IBIS)—a web server to analyze and predict protein interacting partners and binding sites

National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.
Nucleic Acids Research (Impact Factor: 9.11). 10/2009; 38(Database issue):D518-24. DOI: 10.1093/nar/gkp842
Source: PubMed


IBIS is the NCBI Inferred Biomolecular Interaction Server. This server organizes, analyzes and predicts interaction partners and locations of binding sites in proteins. IBIS provides annotations for different types of binding partners (protein, chemical, nucleic acid and peptides), and facilitates the mapping of a comprehensive biomolecular interaction network for a given protein query. IBIS reports interactions observed in experimentally determined structural complexes of a given protein, and at the same time IBIS infers binding sites/interacting partners by inspecting protein complexes formed by homologous proteins. Similar binding sites are clustered together based on their sequence and structure conservation. To emphasize biologically relevant binding sites, several algorithms are used for verification in terms of evolutionary conservation, biological importance of binding partners, size and stability of interfaces, as well as evidence from the published literature. IBIS is updated regularly and is freely accessible via

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    • "PredUS is a structural homology-based method. Given a query protein structure, PredUS uses a structural alignment method to identify structural neighbors, maps the interface of the structural neighbors onto the query protein, calculates the frequency of mapped contacts for each query residue and uses a logistic function to normalize contact frequencies and generate the final residue-based interfacial score IBIS [67] Structure http://www.ncbi.nlm. "
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    ABSTRACT: Reliably pinpointing which specific amino acid residues form the interface(s) between a protein and its binding partner(s) is critical for understanding the structural and physicochemical determinants of protein recognition and binding affinity, and has wide applications in modeling and validating protein interactions predicted by high-throughput methods, in engineering proteins, and in prioritizing drug targets. Here, we review the basic concepts, principles and recent advances in computational approaches to the analysis and prediction of protein-protein interfaces. We point out caveats for objectively evaluating interface predictors, and discuss various applications of data-driven interface predictors for improving energy model-driven protein-protein docking. Finally, we stress the importance of exploiting binding partner information in reliably predicting interfaces and highlight recent advances in this emerging direction.
    Full-text · Article · Oct 2015 · FEBS letters
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    • "Then we collected domain footprint regions which were mapped to the same CDD domain superfamily, structurally superimposed them and ensured that the sufficient fraction of domain footprints was structurally aligned. Subsequently, we clustered their corresponding binding sites based on sequence and structural similarity between the sites and sequence conservation profile of binding site residues (Shoemaker et al., 2010). Binding sites were clustered by a hierarchical complete linkage clustering procedure. "
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    ABSTRACT: Protein interactions have evolved into highly precise and regulated networks adding an immense layer of complexity to cellular systems. The most accurate atomistic description of protein binding sites can be obtained directly from structures of protein complexes. The availability of structurally characterized protein interfaces significantly improves our understanding of interactomes, and the progress in structural characterization of protein-protein interactions (PPIs) can be measured by calculating the structural coverage of protein domain families. We analyze the coverage of protein domain families (defined according to CDD and Pfam databases) by structures, structural protein-protein complexes and unique protein binding sites. Structural PPI coverage of currently available protein families is about 30% without any signs of saturation in coverage growth dynamics. Given the current growth rates of domain databases and structural PPI deposition, complete domain coverage with PPIs is not expected in the near future. As a result of this study we identify families without any protein-protein interaction evidence (listed on a supporting website and propose them as potential targets for structural studies with a focus on protein interactions.
    Full-text · Article · Jun 2014 · Progress in Biophysics and Molecular Biology
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    • "Unlike PeptiSite, other databases such as DOMINO [64], MPID 87 [65], PCIDB [55], MOAD [56], IBIS [57] [66] or ReliBase [58] mainly 88 collect, enrich, and make inferences from individual PDB struc- 89 tures of protein complexes with small chemicals or peptides. "
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    ABSTRACT: We developedPeptiSite, a comprehensive and reliable database of biologically and structurally characterized peptide-binding sites, in which each site is represented by an ensemble of its complexes with protein, peptide and small molecule partners. The unique features of the database include (1) the ensemble site representation that provides a fourth dimension to the otherwise three dimensional data, (2) comprehensive characterization of the binding site architecture that may consist of a multimeric protein assembly with cofactors and metal ions (3) analysis of consensus interaction motifs within the ensembles and identification of conserved determinants of these interactions. Currently the database contains 585 proteins with 650peptide-binding sites.∼chayan/PeptiSite link allows searching for the sites of interestand interactive visualization of the ensembles using the ActiveICM web-browser plugin.This structural database for protein-peptide interactions enables understanding of structural principles of these interactions and may assist the development of an efficient peptide docking benchmark.
    Full-text · Article · Jan 2014 · Biochemical and Biophysical Research Communications
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