Literature DB >> 15657096

PIBASE: a comprehensive database of structurally defined protein interfaces.

Fred P Davis1, Andrej Sali.   

Abstract

MOTIVATION: In recent years, the Protein Data Bank (PDB) has experienced rapid growth. To maximize the utility of the high resolution protein-protein interaction data stored in the PDB, we have developed PIBASE, a comprehensive relational database of structurally defined interfaces between pairs of protein domains. It is composed of binary interfaces extracted from structures in the PDB and the Probable Quaternary Structure server using domain assignments from the Structural Classification of Proteins and CATH fold classification systems.
RESULTS: PIBASE currently contains 158,915 interacting domain pairs between 105,061 domains from 2125 SCOP families. A diverse set of geometric, physiochemical and topologic properties are calculated for each complex, its domains, interfaces and binding sites. A subset of the interface properties are used to remove interface redundancy within PDB entries, resulting in 20,912 distinct domain-domain interfaces. The complexes are grouped into 989 topological classes based on their patterns of domain-domain contacts. The binary interfaces and their corresponding binding sites are categorized into 18,755 and 30,975 topological classes, respectively, based on the topology of secondary structure elements. The utility of the database is illustrated by outlining several current applications. AVAILABILITY: The database is accessible via the world wide web at http://salilab.org/pibase SUPPLEMENTARY INFORMATION: http://salilab.org/pibase/suppinfo.html.

Mesh:

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Year:  2005        PMID: 15657096     DOI: 10.1093/bioinformatics/bti277

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  69 in total

1.  Integrative structure modeling of macromolecular assemblies from proteomics data.

Authors:  Keren Lasker; Jeremy L Phillips; Daniel Russel; Javier Velázquez-Muriel; Dina Schneidman-Duhovny; Elina Tjioe; Ben Webb; Avner Schlessinger; Andrej Sali
Journal:  Mol Cell Proteomics       Date:  2010-05-27       Impact factor: 5.911

2.  Finding biologically relevant protein domain interactions: conserved binding mode analysis.

Authors:  Benjamin A Shoemaker; Anna R Panchenko; Stephen H Bryant
Journal:  Protein Sci       Date:  2005-12-29       Impact factor: 6.725

3.  Localization of protein-binding sites within families of proteins.

Authors:  Dmitry Korkin; Fred P Davis; Andrej Sali
Journal:  Protein Sci       Date:  2005-08-04       Impact factor: 6.725

4.  In silico modeling of pH-optimum of protein-protein binding.

Authors:  Rooplekha C Mitra; Zhe Zhang; Emil Alexov
Journal:  Proteins       Date:  2010-12-22

5.  LTHREADER: prediction of extracellular ligand-receptor interactions in cytokines using localized threading.

Authors:  Vinay Pulim; Jadwiga Bienkowska; Bonnie Berger
Journal:  Protein Sci       Date:  2007-12-20       Impact factor: 6.725

Review 6.  Computational prediction of protein-protein interactions.

Authors:  Lucy Skrabanek; Harpreet K Saini; Gary D Bader; Anton J Enright
Journal:  Mol Biotechnol       Date:  2007-08-14       Impact factor: 2.695

7.  Host pathogen protein interactions predicted by comparative modeling.

Authors:  Fred P Davis; David T Barkan; Narayanan Eswar; James H McKerrow; Andrej Sali
Journal:  Protein Sci       Date:  2007-10-26       Impact factor: 6.725

8.  Optimization of electrostatic interactions in protein-protein complexes.

Authors:  Kelly Brock; Kemper Talley; Kacey Coley; Petras Kundrotas; Emil Alexov
Journal:  Biophys J       Date:  2007-08-10       Impact factor: 4.033

9.  A survey of available tools and web servers for analysis of protein-protein interactions and interfaces.

Authors:  Nurcan Tuncbag; Gozde Kar; Ozlem Keskin; Attila Gursoy; Ruth Nussinov
Journal:  Brief Bioinform       Date:  2009-02-24       Impact factor: 11.622

Review 10.  Coverage of protein domain families with structural protein-protein interactions: current progress and future trends.

Authors:  Alexander Goncearenco; Benjamin A Shoemaker; Dachuan Zhang; Alexey Sarychev; Anna R Panchenko
Journal:  Prog Biophys Mol Biol       Date:  2014-06-13       Impact factor: 3.667

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