A family of evolution-entropy hybrid methods for ranking protein residues by importance.
In order to identify the amino acids that determine protein structure and function it is useful to rank them by their relative importance. Previous approaches belong to two groups; those that rely on statistical inference, and those that focus on phylogenetic analysis. Here, we introduce a class of hybrid methods that combine evolutionary and entropic information from multiple sequence alignments. A detailed analysis in insulin receptor kinase domain and tests on proteins that are well-characterized experimentally show the hybrids' greater robustness with respect to the input choice of sequences, as well as improved sensitivity and specificity of prediction. This is a further step toward proteome scale analysis of protein structure and function.
Mihalek
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Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza T921, Houston, TX 77030, USA.
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Lichtarge
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D000595:Amino Acid Sequence; D000596:Amino Acids; D000818:Animals; D019277:Entropy; D019143:Evolution, Molecular; D006801:Humans; D008957:Models, Genetic; D008958:Models, Molecular; D011506:Proteins / Q000737:chemistry / Q000235:genetics; D011972:Receptor, Insulin / Q000737:chemistry* / Q000235:genetics; D016415:Sequence Alignment
D000596:Amino Acids; D011506:Proteins; D011972:Receptor, Insulin