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VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials

机译:VASP-E:具有静电等电位体积分析的特异性注释

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Algorithms for comparing protein structure are frequently used for function annotation. By searching for subtle similarities among very different proteins, these algorithms can identify remote homologs with similar biological functions. In contrast, few comparison algorithms focus on specificity annotation, where the identification of subtle differences among very similar proteins can assist in finding small structural variations that create differences in binding specificity. Few specificity annotation methods consider electrostatic fields, which play a critical role in molecular recognition. To fill this gap, this paper describes VASP-E (Volumetric Analysis of Surface Properties with Electrostatics), a novel volumetric comparison tool based on the electrostatic comparison of protein-ligand and protein-protein binding sites. VASP-E exploits the central observation that three dimensional solids can be used to fully represent and compare both electrostatic isopotentials and molecular surfaces. With this integrated representation, VASP-E is able to dissect the electrostatic environments of protein-ligand and protein-protein binding interfaces, identifying individual amino acids that have an electrostatic influence on binding specificity. VASP-E was used to examine a nonredundant subset of the serine and cysteine proteases as well as the barnase-barstar and Rap1a-raf complexes. Based on amino acids established by various experimental studies to have an electrostatic influence on binding specificity, VASP-E identified electrostatically influential amino acids with 100% precision and 83.3% recall. We also show that VASP-E can accurately classify closely related ligand binding cavities into groups with different binding preferences. These results suggest that VASP-E should prove a useful tool for the characterization of specific binding and the engineering of binding preferences in proteins.
机译:比较蛋白质结构的算法通常用于功能注释。通过搜索非常不同的蛋白质之间的细微相似性,这些算法可以识别具有相似生物学功能的远程同源物。相反,很少有比较算法专注于特异性注释,在这种注释中,非常相似的蛋白质之间的细微差别的识别可以帮助发现在结合特异性上产生差异的微小结构变异。很少有特异性注释方法考虑静电场,而静电场在分子识别中起关键作用。为了填补这一空白,本文介绍了VASP-E(带静电的表面特性的体积分析),这是一种基于蛋白质-配体和蛋白质-蛋白质结合位点的静电比较的新型体积比较工具。 VASP-E利用集中观测到的三维固体可以完全代表和比较静电等电势和分子表面。通过这种综合表示,VASP-E能够剖析蛋白质-配体和蛋白质-蛋白质结合界面的静电环境,从而识别对结合特异性产生静电影响的单个氨基酸。 VASP-E用于检查丝氨酸和半胱氨酸蛋白酶以及barnase-barstar和Rap1a-raf复合物的非冗余子集。基于各种实验研究确定的对结合特异性产生静电影响的氨基酸,VASP-E以100%的准确度和83.3%的回收率鉴定出对静电有影响的氨基酸。我们还表明,VASP-E可以将紧密相关的配体结合腔精确地分为具有不同结合偏好的组。这些结果表明,VASP-E应该被证明是用于表征特异性结合和蛋白质结合偏好工程的有用工具。

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