Detecting protein dissimilarities in multiple alignments using Bayesian variable selection.

Sinae Kim; Jerry Tsai; Ioannis Kagiampakis; Patricia LiWang; Marina Vannucci

doi:10.1093/bioinformatics/btl566

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Detecting protein dissimilarities in multiple alignments using Bayesian variable selection.

Sinae Kim·Jerry Tsai·Ioannis Kagiampakis·Patricia LiWang·Marina Vannucci

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Abstract

MOTIVATION: We present an application of Bayesian variable selection to the novel detection of sequence elements that confer negative design to protein structure and function. As an illustration, we analyze the different dimer interfaces between the CXCL8 chemokine family with the CCL4 and CCL2 chemokine families to discover the changes that disfavor CXCL8 of quaternary structure. RESULTS: In comparison with known experimental results, our method identifies evolutionarily conserved sequence changes in the CC families that inhibit CXCL8 quaternary structure. Therefore, we find positive selection of negative design elements. Furthermore, our approach predicts that a two-residue deletion conserved in the CCL4 chemokine family disfavors CXCL8 dimerization. AVAILABILITY: The Matlab code for the Bayesian variable selection is freely available at http://stat.tamu.edu/~mvannucci/webpages/codes.html

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Algorithms Amino Acid Sequence Bayes Theorem Conserved Sequence Molecular Sequence Data Pattern Recognition, Automated Proteins Sequence Alignment Sequence Analysis, Protein Sequence Homology, Amino Acid Software Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

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Sinae Kim, Jerry Tsai, Ioannis Kagiampakis, Patricia LiWang, Marina Vannucci. 2006-11-14. Detecting protein dissimilarities in multiple alignments using Bayesian variable selection.. https://doi.org/10.1093/bioinformatics%2Fbtl566

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