Struct2Net: a web service to predict protein–protein interactions using a structure-based approach
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Berger_Struct2Net a.pdf
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Author(s)
Singh, Rohit
Park, Daniel Kyu
Xu, Jinbo
Hosur, Raghavendra
Berger, Bonnie
Date Issued
May 2010
Journal
Nucleic Acids Research
Publisher
Oxford University Press
Citation
Singh, R. et al. “Struct2Net: a Web Service to Predict Protein-protein Interactions Using a Structure-based Approach.” Nucleic Acids Research 38.Web Server (2010): W508–W515. Web.
Version
Final published version
Abstract
Struct2Net is a web server for predicting interactions between arbitrary protein pairs using a structure-based approach. Prediction of protein–protein interactions (PPIs) is a central area of interest and successful prediction would provide leads for experiments and drug design; however, the experimental coverage of the PPI interactome remains inadequate. We believe that Struct2Net is the first community-wide resource to provide structure-based PPI predictions that go beyond homology modeling. Also, most web-resources for predicting PPIs currently rely on functional genomic data (e.g. GO annotation, gene expression, cellular localization, etc.). Our structure-based approach is independent of such methods and only requires the sequence information of the proteins being queried. The web service allows multiple querying options, aimed at maximizing flexibility. For the most commonly studied organisms (fly, human and yeast), predictions have been pre-computed and can be retrieved almost instantaneously. For proteins from other species, users have the option of getting a quick-but-approximate result (using orthology over pre-computed results) or having a full-blown computation performed. The web service is freely available at http://struct2net.csail.mit.edu.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Department of Mathematics
Terms of Use
Creative Commons Attribution Non-Commercial
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1093/nar/gkq481
