MBE Advance Access originally published online on June 16, 2006
Molecular Biology and Evolution 2006 23(9):1751-1761; doi:10.1093/molbev/msl040
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Research Article |
Structural Determinants of the Rate of Protein Evolution in Yeast


* Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California;
Program in Computation and Neural Systems, California Institute of Technology, Pasadena, California; and
Section of Integrative Biology and Center for Computational Biology and Bioinformatics, University of Texas at Austin
E-mail: cwilke{at}mail.utexas.edu.
We investigate how a protein's structure influences the rate at which its sequence evolves. Our basic hypothesis is that proteins with highly designable structures (structures that are encoded by many sequences) will evolve more rapidly. Recent theoretical advances argue that structures with a higher density of interresidue contacts are more designable, and we show that high contact density is correlated with an increased rate of sequence evolution in yeast. In addition, we investigate the correlations between the rate of sequence evolution and several other structural descriptors, carefully controlling for the strong effect of expression level on evolutionary rate. Overall, we find that the structural descriptors that we consider appear to explain roughly 10% of the variation in rates of protein evolution in yeast. We also show that despite the well-known trend for buried residues to be more conserved, proteins with a higher fraction of buried residues, nonetheless, tend to evolve their sequences more rapidly. We suggest that this effect is due to the increased designability of structures with more buried residues. Our results provide evidence that protein structure plays an important role in shaping the rate of sequence evolution and provide evidence to support recent theoretical advances linking structural designability to contact density.
Key Words: designability protein structure evolutionary rate protein evolution principal component regression yeast
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