iWRAP: An Interface Threading Approach with Application to Prediction of Cancer-Related Protein–Protein Interactions
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Author(s)
Hosur, Raghavendra
Xu, Jinbo
Berger, Bonnie
Bienkowska, Jadwiga R.
Date Issued
December 2010
Journal
Journal of Molecular Biology
Publisher
Elsevier
Citation
Hosur, Raghavendra, Jinbo Xu, Jadwiga Bienkowska, and Bonnie Berger. “iWRAP: An Interface Threading Approach with Application to Prediction of Cancer-Related Protein–Protein Interactions.” Journal of Molecular Biology 405, no. 5 (February 2011): 1295–1310.
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Author's final manuscript
Abstract
Current homology modeling methods for predicting protein–protein interactions (PPIs) have difficulty in the “twilight zone” (< 40%) of sequence identities. Threading methods extend coverage further into the twilight zone by aligning primary sequences for a pair of proteins to a best-fit template complex to predict an entire three-dimensional structure. We introduce a threading approach, iWRAP, which focuses only on the protein interface. Our approach combines a novel linear programming formulation for interface alignment with a boosting classifier for interaction prediction. We demonstrate its efficacy on SCOPPI, a classification of PPIs in the Protein Databank, and on the entire yeast genome. iWRAP provides significantly improved prediction of PPIs and their interfaces in stringent cross-validation on SCOPPI. Furthermore, by combining our predictions with a full-complex threader, we achieve a coverage of 13% for the yeast PPIs, which is close to a 50% increase over previous methods at a higher sensitivity. As an application, we effectively combine iWRAP with genomic data to identify novel cancer-related genes involved in chromatin remodeling, nucleosome organization, and ribonuclear complex assembly. iWRAP is available at http://iwrap.csail.mit.edu.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Materials Science and Engineering
Massachusetts Institute of Technology. Department of Mathematics
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DOI of Published Version
https://doi.org/10.1016/j.jmb.2010.11.025
