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dc.contributor.authorYeh, So-Weien_US
dc.contributor.authorHuang, Tsun-Tsaoen_US
dc.contributor.authorLiu, Jen-Weien_US
dc.contributor.authorYu, Sung-Huanen_US
dc.contributor.authorShih, Chien-Huaen_US
dc.contributor.authorHwang, Jenn-Kangen_US
dc.contributor.authorEchave, Julianen_US
dc.date.accessioned2014-12-08T15:36:38Z-
dc.date.available2014-12-08T15:36:38Z-
dc.date.issued2014en_US
dc.identifier.issn2314-6133en_US
dc.identifier.urihttp://hdl.handle.net/11536/24970-
dc.identifier.urihttp://dx.doi.org/10.1155/2014/572409en_US
dc.description.abstractFunctional and biophysical constraints result in site-dependent patterns of protein sequence variability. It is commonly assumed that the key structural determinant of site-specific rates of evolution is the Relative Solvent Accessibility (RSA). However, a recent study found that amino acid substitution rates correlate better with two Local Packing Density (LPD) measures, the Weighted Contact Number (WCN) and the Contact Number (CN), than with RSA. This work aims at a more thorough assessment. To this end, in addition to substitution rates, we considered four other sequence variability scores, four measures of solvent accessibility (SA), and other CN measures. We compared all properties for each protein of a structurally and functionally diverse representative dataset of monomeric enzymes. We show that the best sequence variability measures take into account phylogenetic tree topology. More importantly, we show that both LPD measures (WCN and CN) correlate better than all of the SA measures, regardless of the sequence variability score used. Moreover, the independent contribution of the best LPD measure is approximately four times larger than that of the best SA measure. This study strongly supports the conclusion that a site\'s packing density rather than its solvent accessibility is the main structural determinant of its rate of evolution.en_US
dc.language.isoen_USen_US
dc.titleLocal Packing Density Is the Main Structural Determinant of the Rate of Protein Sequence Evolution at Site Levelen_US
dc.typeArticleen_US
dc.identifier.doi10.1155/2014/572409en_US
dc.identifier.journalBIOMED RESEARCH INTERNATIONALen_US
dc.contributor.department生物資訊及系統生物研究所zh_TW
dc.contributor.departmentInstitude of Bioinformatics and Systems Biologyen_US
dc.identifier.wosnumberWOS:000339186900001-
dc.citation.woscount1-
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