Bioinformatics Advance Access originally published online on November 8, 2005
Bioinformatics 2006 22(2):164-171; doi:10.1093/bioinformatics/bti766
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Prediction of functional specificity determinants from protein sequences using log-likelihood ratios
1Howard Hughes Medical Institute, University of Texas Southwestern Medical Center 5323 Harry Hines Boulevard, Dallas, TX 75390-9050, USA
2Department of Biochemistry, University of Texas Southwestern Medical Center 5323 Harry Hines Boulevard, Dallas, TX 75390-9050, USA
*To whom correspondence should be addressed.
Motivation: A number of methods have been developed to predict functional specificity determinants in protein families based on sequence information. Most of these methods rely on pre-defined functional subgroups. Manual subgroup definition is difficult because of the limited number of experimentally characterized subfamilies with differing specificity, while automatic subgroup partitioning using computational tools is a non-trivial task and does not always yield ideal results.
Results: We propose a new approach SPEL (specificity positions by evolutionary likelihood) to detect positions that are likely to be functional specificity determinants. SPEL, which does not require subgroup definition, takes a multiple sequence alignment of a protein family as the only input, and assigns a P-value to every position in the alignment. Positions with low P-values are likely to be important for functional specificity. An evolutionary tree is reconstructed during the calculation, and P-value estimation is based on a random model that involves evolutionary simulations. Evolutionary log-likelihood is chosen as a measure of amino acid distribution at a position. To illustrate the performance of the method, we carried out a detailed analysis of two protein families (LacI/PurR and G protein 
subunit), and compared our method with two existing methods (evolutionary trace and mutual information based). All three methods were also compared on a set of protein families with known ligand-bound structures.
Availability: SPEL is freely available for non-commercial use. Its pre-compiled versions for several platforms and alignments used in this work are available at ftp://iole.swmed.edu/pub/SPEL/
Contact: grishin{at}chop.swmed.edu.
Supplementary information: Supplementary materials are available at ftp:/iole.swmed.edu/pub/SPEL/
Received on August 9, 2005; revised on November 3, 2005; accepted on November 3, 2005
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