TY - JOUR
T1 - Causes of evolutionary rate variation among protein sites
AU - Echave, Julian
AU - Spielman, Stephanie J.
AU - Wilke, Claus O.
N1 - Funding Information:
J.E. is Principal Investigator of CONICET. This work was also supported in part by US National Institutes of Health (NIH) grant F31 GM113622-01 to S.J.S. and by NIH grant R01 GM088344, NSF Cooperative agreement DBI-0939454 (BEACON Center), and ARO grant W911NF-12-1-0390 to C.O.W.
Publisher Copyright:
© 2016 Macmillan Publishers Limited.
PY - 2016/2/1
Y1 - 2016/2/1
N2 - It has long been recognized that certain sites within a protein, such as sites in the protein core or catalytic residues in enzymes, are evolutionarily more conserved than other sites. However, our understanding of rate variation among sites remains surprisingly limited. Recent progress to address this includes the development of a wide array of reliable methods to estimate site-specific substitution rates from sequence alignments. In addition, several molecular traits have been identified that correlate with site-specific mutation rates, and novel mechanistic biophysical models have been proposed to explain the observed correlations. Nonetheless, current models explain, at best, approximately 60% of the observed variance, highlighting the limitations of current methods and models and the need for new research directions.
AB - It has long been recognized that certain sites within a protein, such as sites in the protein core or catalytic residues in enzymes, are evolutionarily more conserved than other sites. However, our understanding of rate variation among sites remains surprisingly limited. Recent progress to address this includes the development of a wide array of reliable methods to estimate site-specific substitution rates from sequence alignments. In addition, several molecular traits have been identified that correlate with site-specific mutation rates, and novel mechanistic biophysical models have been proposed to explain the observed correlations. Nonetheless, current models explain, at best, approximately 60% of the observed variance, highlighting the limitations of current methods and models and the need for new research directions.
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U2 - 10.1038/nrg.2015.18
DO - 10.1038/nrg.2015.18
M3 - Review article
C2 - 26781812
AN - SCOPUS:84955379926
VL - 17
SP - 109
EP - 121
JO - Nature Reviews Genetics
JF - Nature Reviews Genetics
SN - 1471-0056
IS - 2
ER -