Shahmoradi Amir, Sydykova Dariya K, Spielman Stephanie J, Jackson Eleisha L, Dawson Eric T, Meyer Austin G, Wilke Claus O
Department of Physics, The University of Texas at Austin, Austin, TX, 78712, USA.
J Mol Evol. 2014 Oct;79(3-4):130-42. doi: 10.1007/s00239-014-9644-x. Epub 2014 Sep 13.
Several recent works have shown that protein structure can predict site-specific evolutionary sequence variation. In particular, sites that are buried and/or have many contacts with other sites in a structure have been shown to evolve more slowly, on average, than surface sites with few contacts. Here, we present a comprehensive study of the extent to which numerous structural properties can predict sequence variation. The quantities we considered include buriedness (as measured by relative solvent accessibility), packing density (as measured by contact number), structural flexibility (as measured by B factors, root-mean-square fluctuations, and variation in dihedral angles), and variability in designed structures. We obtained structural flexibility measures both from molecular dynamics simulations performed on nine non-homologous viral protein structures and from variation in homologous variants of those proteins, where they were available. We obtained measures of variability in designed structures from flexible-backbone design in the Rosetta software. We found that most of the structural properties correlate with site variation in the majority of structures, though the correlations are generally weak (correlation coefficients of 0.1-0.4). Moreover, we found that buriedness and packing density were better predictors of evolutionary variation than structural flexibility. Finally, variability in designed structures was a weaker predictor of evolutionary variability than buriedness or packing density, but it was comparable in its predictive power to the best structural flexibility measures. We conclude that simple measures of buriedness and packing density are better predictors of evolutionary variation than the more complicated predictors obtained from dynamic simulations, ensembles of homologous structures, or computational protein design.
最近的几项研究表明,蛋白质结构能够预测位点特异性的进化序列变异。特别是,在一个结构中被掩埋和/或与其他位点有许多接触的位点,平均而言,其进化速度比接触少的表面位点要慢。在此,我们对众多结构特性能够预测序列变异的程度进行了全面研究。我们考虑的量包括掩埋程度(通过相对溶剂可及性测量)、堆积密度(通过接触数测量)、结构灵活性(通过B因子、均方根波动和二面角变化测量)以及设计结构中的变异性。我们从对九个非同源病毒蛋白结构进行的分子动力学模拟以及这些蛋白同源变体的变异中(若有可用数据)获得了结构灵活性测量值。我们从Rosetta软件中的柔性骨架设计获得了设计结构中的变异性测量值。我们发现,大多数结构特性与大多数结构中的位点变异相关,尽管相关性通常较弱(相关系数为0.1 - 0.4)。此外,我们发现掩埋程度和堆积密度比结构灵活性更能预测进化变异。最后,设计结构中的变异性比掩埋程度或堆积密度更难以预测进化变异性,但其预测能力与最佳的结构灵活性测量值相当。我们得出结论,与从动态模拟、同源结构集合或计算蛋白质设计中获得的更复杂的预测指标相比,掩埋程度和堆积密度的简单测量指标更能预测进化变异。