Computational method for prediction of protein functional sites using specificity determinants

O. V. Kalinina, R. B. Rassel, A. B. Rakhmaninova, M. S. Gel'fand

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


The current available data on protein sequences largely exceeds the experimental capabilities to annotate their function. So annotation in silico, i.e. using computational methods becomes increasingly important. This annotation is inevitably a prediction, but it can be an important starting point for further experimental studies. Here we present a method for prediction of protein functional sites, SDPsite, based on the identification of protein specificity determinants. Taking as an input a protein sequence alignment and a phylogenetic tree, the algorithm predicts conserved positions and specificity determinants, maps them onto the protein's 3D structure, and searches for clusters of the predicted positions. Comparison of the obtained predictions with experimental data and data on performance of several other methods for prediction of functional sites reveals that SDPsite agrees well with the experiment and outperforms most of the previously available methods. SDPsite is publicly available under

Original languageEnglish
Pages (from-to)151-162
Number of pages12
JournalMolekulyarnaya Biologiya
Issue number1
Publication statusPublished - Jan 2007
Externally publishedYes


Dive into the research topics of 'Computational method for prediction of protein functional sites using specificity determinants'. Together they form a unique fingerprint.

Cite this