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

Author:

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

Abstract

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.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computational Theory and Mathematics,Molecular Biology,Structural Biology

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