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按酶的国际分类编号(EC编号)分类的酶及其活性位点的序列和结构特征

Sequence and structural features of enzymes and their active sites by EC class.

作者信息

Bray Tracey, Doig Andrew J, Warwicker Jim

机构信息

Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT, UK.

出版信息

J Mol Biol. 2009 Mar 13;386(5):1423-36. doi: 10.1016/j.jmb.2008.11.057. Epub 2008 Dec 10.

Abstract

We have analysed a non-redundant set of 294 enzymes for differences in sequence and structural features between the six main Enzyme Commission (EC) classification groups. This systematic study of enzymes, and their active sites in particular, aims to increase understanding of how the structure of an enzyme relates to its functional role. Many features showed significant differences between the EC classes, including active-site polarity, enzyme size and active-site amino acid propensities. Many attributes correlate with each other to form clusters of related features from which we chose representative features for further analysis. Oxidoreductases have more non-polar active sites, which can be attributed to cofactor binding and a preference for Glu over Asp in active sites in comparison to the other classes. Lyases form a significantly higher proportion of oligomers than any other class, whilst the hydrolases form the largest proportion of monomers. These features were then used in a prediction model that classified each enzyme into its top EC class with an accuracy of 33.1%, which is an increase of 16.4% over random classification. Understanding the link between structure and function is critical to improving enzyme design and the prediction of protein function from structure without transfer of annotation from alignments.

摘要

我们分析了一组294种非冗余酶,以研究六大主要酶委员会(EC)分类组之间在序列和结构特征上的差异。这项对酶,尤其是其活性位点的系统研究,旨在增进对酶的结构与其功能作用之间关系的理解。许多特征在EC分类之间表现出显著差异,包括活性位点极性、酶大小和活性位点氨基酸倾向。许多属性相互关联,形成相关特征簇,我们从中选择代表性特征进行进一步分析。氧化还原酶具有更多的非极性活性位点,这可归因于辅因子结合以及与其他类别相比,活性位点中对谷氨酸的偏好超过天冬氨酸。裂合酶形成寡聚体的比例明显高于任何其他类别,而水解酶形成单体的比例最大。然后,这些特征被用于一个预测模型,该模型将每种酶分类到其最高的EC类别,准确率为33.1%,比随机分类提高了16.4%。理解结构与功能之间的联系对于改进酶设计以及从结构预测蛋白质功能而不通过比对转移注释至关重要。

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