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Algorithms Mol Biol. 2010 Jul 15;5:29. doi: 10.1186/1748-7188-5-29.

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

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Cellnetworks, University of Heidelberg, Heidelberg, Germany.



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.


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 and a stand-alone Java application available from the website.


SDPclust performs a simultaneous identification of specificity determinants and specificity groups in a statistically robust and phylogeny-independent manner.

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