ISIS: Interaction sites identified from sequence

Yanay Ofran, Burkhard Rost

Research output: Contribution to journalArticlepeer-review

232 Scopus citations

Abstract

Motivation: Large-scale experiments reveal pairs of interacting proteins but leave the residues involved in the interactions unknown. These interface residues are essential for understanding the mechanism of interaction and are often desired drug targets. Reliable identification of residues that reside in protein-protein interface typically requires analysis of protein structure. Therefore, for the vast majority of proteins, for which there is no high-resolution structure, there is no effective way of identifying interface residues. Results: Here we present a machine learning-based method that identifies interacting residues from sequence alone. Although the method is developed using transient protein-protein interfaces from complexes of experimentally known 3D structures, it never explicitly uses 3D information. Instead, we combine predicted structural features with evolutionary information. The strongest predictions of the method reached over 90% accuracy in a cross-validation experiment. Our results suggest that despite the significant diversity in the nature of protein-protein interactions, they all share common basic principles and that these principles are identifiable from sequence alone.

Original languageEnglish
Pages (from-to)e13-e16
JournalBioinformatics
Volume23
Issue number2
DOIs
StatePublished - 15 Jan 2007
Externally publishedYes

Bibliographical note

Funding Information:
Thanks to Jinfeng Liu (Columbia) for computer assistance and to Guy Yachdav (Columbia) for setting up the ISIS Internet server. Special thanks also to Lawrence Shapiro, Wayne Hendrickson, Barry Honig, David Hirsh and Oliver Hobert (all Columbia) for helpful discussions. The work of Y.O. and B.R. was supported by the grants RO1-GM63029-01 and R01-GM64633-01 from the National Institutes of Health (NIH). Last, not least, thanks to all those who maintain excellent databases and to all experimentalists who enabled this work by making their data publicly available.

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