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Identification of direct residue contacts in protein-protein interaction by message passing.

TitleIdentification of direct residue contacts in protein-protein interaction by message passing.
Publication TypeJournal Article
Year of Publication2009
AuthorsWeigt, M, White, RA, Szurmant, H, Hoch, JA, Hwa, T
JournalProc Natl Acad Sci U S A
Date Published2009 Jan 6
KeywordsBacterial Proteins, Computational Biology, Databases, Protein, Protein Interaction Mapping, Signal Transduction

Understanding the molecular determinants of specificity in protein-protein interaction is an outstanding challenge of postgenome biology. The availability of large protein databases generated from sequences of hundreds of bacterial genomes enables various statistical approaches to this problem. In this context covariance-based methods have been used to identify correlation between amino acid positions in interacting proteins. However, these methods have an important shortcoming, in that they cannot distinguish between directly and indirectly correlated residues. We developed a method that combines covariance analysis with global inference analysis, adopted from use in statistical physics. Applied to a set of >2,500 representatives of the bacterial two-component signal transduction system, the combination of covariance with global inference successfully and robustly identified residue pairs that are proximal in space without resorting to ad hoc tuning parameters, both for heterointeractions between sensor kinase (SK) and response regulator (RR) proteins and for homointeractions between RR proteins. The spectacular success of this approach illustrates the effectiveness of the global inference approach in identifying direct interaction based on sequence information alone. We expect this method to be applicable soon to interaction surfaces between proteins present in only 1 copy per genome as the number of sequenced genomes continues to expand. Use of this method could significantly increase the potential targets for therapeutic intervention, shed light on the mechanism of protein-protein interaction, and establish the foundation for the accurate prediction of interacting protein partners.

Alternate JournalProc. Natl. Acad. Sci. U.S.A.
PubMed ID19116270
PubMed Central IDPMC2629192
Grant ListGM019416 / GM / NIGMS NIH HHS / United States

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