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结构分歧与进化信息有何关系?

How is structural divergence related to evolutionary information?

机构信息

Structural Bioinformatics Unit, Fundación Instituto Leloir, CONICET, C1405BWE, Ciudad Autónoma de Buenos Aires, Buenos Aires, Argentina.

Departamento de Ciencia y Tecnología, CONICET, Universidad Nacional de Quilmes, Bernal, Argentina.

出版信息

Mol Phylogenet Evol. 2018 Oct;127:859-866. doi: 10.1016/j.ympev.2018.06.033. Epub 2018 Jun 25.

Abstract

The analysis of evolutionary information in a protein family, such as conservation and covariation, is often linked to its structural information. Multiple sequence alignments of distant homologous sequences are used to measure evolutionary variables. Although high structural differences between proteins can be expected in such divergent alignments, most works linking evolutionary and structural information use a single structure ignoring the structural variability within protein families. The goal of this work is to elucidate the relevance of structural divergence when sequence-based measures are integrated with structural information. We found that inter-residue contacts and solvent accessibility undergo large variations in protein families. Our results show that high covariation scores tend to reveal residue contacts that are conserved in the family, instead of protein or conformer specific contacts. We also found that residue accessible surface area shows a high variability between structures of the same family. As a consequence, the mean relative solvent accessibility of multiple structures correlates better with the conservation pattern than the relative solvent accessibility of a single structure. We conclude that the use of comprehensive structural information allows a more accurate interpretation of the information computed from sequence alignments. Therefore, considering structural divergence would lead to a better understanding of protein function, dynamics, and evolution.

摘要

对蛋白质家族的进化信息(如保守性和共变性)的分析通常与结构信息相关联。使用远距离同源序列的多重序列比对来测量进化变量。尽管在如此发散的比对中可以预期蛋白质之间存在很高的结构差异,但大多数将进化和结构信息联系起来的工作都使用单个结构,而忽略了蛋白质家族内的结构可变性。这项工作的目标是阐明在将基于序列的度量与结构信息整合时,结构发散的相关性。我们发现,在蛋白质家族中,残基间的接触和溶剂可及性会发生很大的变化。我们的结果表明,高共变得分往往揭示了家族中保守的残基接触,而不是蛋白质或构象特异性的接触。我们还发现,同一家族中不同结构的残基可及表面积具有很高的可变性。因此,多个结构的平均相对溶剂可及性与保守模式的相关性优于单个结构的相对溶剂可及性。我们的结论是,使用全面的结构信息可以更准确地解释从序列比对计算得出的信息。因此,考虑结构发散将有助于更好地理解蛋白质的功能、动力学和进化。

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