InterProSurf: A web server for predicting interacting sites on protein surfaces

Surendra S. Negi, Catherine H. Schein, Numan Oezguen, Trevor D. Power, Werner Braun

Research output: Contribution to journalArticle

89 Citations (Scopus)

Abstract

A new web server, InterProSurf, predicts interacting amino acid residues in proteins that are most likely to interact with other proteins, given the 3D structures of subunits of a protein complex. The prediction method is based on solvent accessible surface area of residues in the isolated subunits, a propensity scale for interface residues and a clustering algorithm to identify surface regions with residues of high interface propensities. Here we illustrate the application of InterProSurf to determine which areas of Bacillus anthracis toxins and measles virus hemagglutinin protein interact with their respective cell surface receptors. The computationally predicted regions overlap with those regions previously identified as interface regions by sequence analysis and mutagenesis experiments.

Original languageEnglish (US)
Pages (from-to)3397-3399
Number of pages3
JournalBioinformatics
Volume23
Issue number24
DOIs
StatePublished - Dec 2007

Fingerprint

Web Server
Membrane Proteins
Servers
Proteins
Protein
Bacillus anthracis
Measles virus
Protein Subunits
Hemagglutinins
Cell Surface Receptors
Mutagenesis
Sequence Analysis
Cluster Analysis
Bacilli
Surface area
Viruses
Clustering algorithms
Receptor
Virus
Clustering Algorithm

ASJC Scopus subject areas

  • Clinical Biochemistry
  • Computer Science Applications
  • Computational Theory and Mathematics

Cite this

InterProSurf : A web server for predicting interacting sites on protein surfaces. / Negi, Surendra S.; Schein, Catherine H.; Oezguen, Numan; Power, Trevor D.; Braun, Werner.

In: Bioinformatics, Vol. 23, No. 24, 12.2007, p. 3397-3399.

Research output: Contribution to journalArticle

Negi, Surendra S. ; Schein, Catherine H. ; Oezguen, Numan ; Power, Trevor D. ; Braun, Werner. / InterProSurf : A web server for predicting interacting sites on protein surfaces. In: Bioinformatics. 2007 ; Vol. 23, No. 24. pp. 3397-3399.
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