An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies

Pavel Mazin, Mikhail S. Gelfand, Andrey A. Mironov, A. B. Rakhmaninova, Anatoly R. Rubinov, Robert B. Russell, Olga V. Kalinina

Algorithms for Molecular Biology · 2010 · 59 citations · 28 references

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Abstract

BACKGROUND: Recent progress in sequencing and 3 D structure determination techniques stimulated development of approaches aimed at more precise annotation of proteins, that is, prediction of exact specificity to a ligand or, more broadly, to a binding partner of any kind. RESULTS: We present a method, SDPclust, for identification of protein functional subfamilies coupled with prediction of specificity-determining positions (SDPs). SDPclust predicts specificity in a phylogeny-independent stochastic manner, which allows for the correct identification of the specificity for proteins that are separated on a phylogenetic tree, but still bind the same ligand. SDPclust is implemented as a Web-server http://bioinf.fbb.msu.ru/SDPfoxWeb/ and a stand-alone Java application available from the website. CONCLUSIONS: SDPclust performs a simultaneous identification of specificity determinants and specificity groups in a statistically robust and phylogeny-independent manner.

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