Department of Computational and Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, PA.
Mol Biol Evol. 2019 Sep 1;36(9):2053-2068. doi: 10.1093/molbev/msz102.
Recent studies have drawn attention to the evolution of protein dynamics, in addition to sequence and structure, based on the premise structure-encodes-dynamics-encodes-function. Of interest is to understand how functional differentiation is accomplished while maintaining the fold, or how intrinsic dynamics plays out in the evolution of structural variations and functional specificity. We performed a systematic computational analysis of 26,899 proteins belonging to 116 CATH superfamilies. Characterizing cooperative mechanisms and convergent/divergent features that underlie the shared/differentiated dynamics of family members required a methodology that lends itself to efficient analyses of large ensembles of proteins. We therefore introduced, SignDy, an integrated pipeline for evaluating the signature dynamics of families based on elastic network models. Our analysis confirmed that family members share conserved, highly cooperative (global) modes of motion. Importantly, our analysis discloses a subset of motions that sharply distinguishes subfamilies, which lie in a low-to-intermediate frequency regime of the mode spectrum. This regime has maximal impact on functional differentiation of families into subfamilies, while being evolutionarily conserved among subfamily members. Notably, the high-frequency end of the spectrum also reveals evolutionary conserved features across and within subfamilies; but in sharp contrast to global motions, high-frequency modes are minimally collective. Modulation of robust/conserved global dynamics by low-to-intermediate frequency fluctuations thus emerges as a versatile mechanism ensuring the adaptability of selected folds and the specificity of their subfamilies. SignDy further allows for dynamics-based categorization as a new layer of information relevant to distinctive mechanisms of action of subfamilies, beyond sequence or structural classifications.
最近的研究引起了人们对蛋白质动力学进化的关注,除了序列和结构之外,这是基于结构编码动力学-编码功能的前提。有趣的是,要了解如何在保持折叠的情况下完成功能分化,或者内在动力学如何在结构变异和功能特异性的进化中发挥作用。我们对属于 116 个 CATH 超家族的 26899 个蛋白质进行了系统的计算分析。为了刻画合作机制和内在的趋同/分歧特征,这些机制和特征是成员之间共享/分化动力学的基础,我们需要一种方法来有效地分析大量的蛋白质集合。因此,我们引入了 SignDy,这是一种基于弹性网络模型评估家族特征动力学的综合分析方法。我们的分析证实,家族成员共享保守的、高度协作的(全局)运动模式。重要的是,我们的分析揭示了一组运动,这些运动可以清晰地区分亚家族,这些运动位于模式谱的低到中频范围。该范围对家族分为亚家族的功能分化有最大的影响,同时在亚家族成员之间具有进化保守性。值得注意的是,该范围的高频端也揭示了亚家族之间和内部的进化保守特征;但与全局运动形成鲜明对比的是,高频模式的集体性最小。通过低到中频波动对稳健/保守的全局动力学的调制,因此成为一种通用机制,确保了所选折叠的适应性及其亚家族的特异性。SignDy 还允许基于动力学的分类作为一个新的信息层,与亚家族的作用机制相关,超越了序列或结构分类。