Computational method for predicting protein functional sites with the use of specificity determinants

O. V. Kalinina, R. B. Russell, A. B. Rakhmaninova, M. S. Gelfand

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The currently available body of decoded amino acid sequences of various proteins exceeds manifold the experimental capabilities of their functional annotation. Therefore, in silico annotation using bioinformatics methods becomes increasingly important. Such annotation is actually a prediction; however, this can be an important starting point for further laboratory research. This work describes a new method for predicting functionally important protein sites, SDPsite, on the basis of identification of specificity determinants. The algorithm proposed utilizes a protein family aglinment and a phylogenetic tree to predict the conserved positions and specificity determinants, map them onto the protein structure, and search for clusters of the predicted positions. Comparison of the resulting predictions with experimental data and published predictions of functional sites by other methods demonstrates that the results of SDPsite agree well with experimental data and exceed the results obtained with the majority of previous methods. SDPsite is publicly available at http://bioinf.fbb.msu.ru/SDPsite .

Original languageEnglish
Pages (from-to)137-147
Number of pages11
JournalMolecular Biology
Volume41
Issue number1
DOIs
Publication statusPublished - Feb 2007
Externally publishedYes

Keywords

  • Comparative sequence analysis
  • Functional site
  • Prediction
  • Specificity determinants
  • Specificity-determining positions
  • Structural genomics

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