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MBE Advance Access originally published online on May 23, 2007
Molecular Biology and Evolution 2007 24(8):1769-1782; doi:10.1093/molbev/msm097
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© The Author 2007. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org

Research Articles

Quantifying the Impact of Protein Tertiary Structure on Molecular Evolution

Sang Chul Choi*, Asger Hobolth*, Douglas M. Robinson*,{dagger}, Hirohisa Kishino{ddagger} and Jeffrey L. Thorne*,§

* Bioinformatics Research Center, North Carolina State University
{dagger} Statistical Genetics and Biomarkers Group, Bristol-Myers Squibb Co., Pennington, New Jersey
{ddagger} Laboratory of Biometrics, Graduate School of Agriculture and Life Sciences, University of Tokyo, Tokyo, Japan
§ Wissenschaftskolleg zu Berlin, Berlin, Germany

E-mail: thorne{at}statgen.ncsu.edu.

Accepted for publication May 11, 2007.

To investigate the evolutionary impact of protein structure, the experimentally determined tertiary structure and the protein-coding DNA sequence were collected for each of 1,195 genes. These genes were studied via a model of sequence change that explicitly incorporates effects on evolutionary rates due to protein tertiary structure. In the model, these effects act via the solvent accessibility environments and pairwise amino acid interactions that are induced by tertiary structure. To compare the hypotheses that structure does and does not have a strong influence on evolution, Bayes factors were estimated for each of the 1,195 sequences. Most of the Bayes factors strongly support the hypothesis that protein structure affects protein evolution. Furthermore, both solvent accessibility and pairwise interactions among amino acids are inferred to have important roles in protein evolution. Our results also indicate that the strength of the relationship between tertiary structure and evolution has a weak but real correlation to the annotation information in the Gene Ontology database. Although their influences on rates of evolution vary among protein families, we find that the mean impacts of solvent accessibility and pairwise interactions are about the same.

Key Words: molecular evolution • protein structure impact • Gene Ontology • MCMC • Bayes factor

Arndt von Haeseler, Associate Editor


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