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序列和结构连续性对于进化重要性的提高有助于蛋白质功能位点的发现和注释。

Sequence and structure continuity of evolutionary importance improves protein functional site discovery and annotation.

机构信息

Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030, USA.

出版信息

Protein Sci. 2010 Jul;19(7):1296-311. doi: 10.1002/pro.406.

Abstract

Protein functional sites control most biological processes and are important targets for drug design and protein engineering. To characterize them, the evolutionary trace (ET) ranks the relative importance of residues according to their evolutionary variations. Generally, top-ranked residues cluster spatially to define evolutionary hotspots that predict functional sites in structures. Here, various functions that measure the physical continuity of ET ranks among neighboring residues in the structure, or in the sequence, are shown to inform sequence selection and to improve functional site resolution. This is shown first, in 110 proteins, for which the overlap between top-ranked residues and actual functional sites rose by 8% in significance. Then, on a structural proteomic scale, optimized ET led to better 3D structure-function motifs (3D templates) and, in turn, to enzyme function prediction by the Evolutionary Trace Annotation (ETA) method with better sensitivity of (40% to 53%) and positive predictive value (93% to 94%). This suggests that the similarity of evolutionary importance among neighboring residues in the sequence and in the structure is a universal feature of protein evolution. In practice, this yields a tool for optimizing sequence selections for comparative analysis and, via ET, for better predictions of functional site and function. This should prove useful for the efficient mutational redesign of protein function and for pharmaceutical targeting.

摘要

蛋白质功能位点控制着大多数生物过程,是药物设计和蛋白质工程的重要靶点。为了描述它们,进化轨迹(Evolutionary Trace,ET)根据残基的进化变化对其相对重要性进行排序。通常,排名靠前的残基在空间上聚集,形成进化热点,从而预测结构中的功能位点。在这里,展示了各种衡量结构或序列中相邻残基之间 ET 排名物理连续性的功能,这些功能可用于指导序列选择并提高功能位点的分辨率。首先在 110 种蛋白质中进行了验证,结果表明,前几位残基与实际功能位点之间的重叠在统计学上显著提高了 8%。然后,在结构蛋白质组学的规模上,优化后的 ET 产生了更好的 3D 结构-功能基序(3D 模板),进而通过 Evolutionary Trace Annotation(ETA)方法提高了酶功能预测的敏感性(40%至 53%)和阳性预测值(93%至 94%)。这表明,序列和结构中相邻残基的进化重要性相似是蛋白质进化的普遍特征。实际上,这为比较分析中的序列选择优化提供了一种工具,并且通过 ET 还可以更好地预测功能位点和功能。这对于蛋白质功能的高效突变设计和药物靶向应该是有用的。

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