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利用一种新颖的特征识别催化残基,该特征综合了残基的微环境和几何位置特性。

Identification of catalytic residues using a novel feature that integrates the microenvironment and geometrical location properties of residues.

机构信息

State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, People's Republic of China.

出版信息

PLoS One. 2012;7(7):e41370. doi: 10.1371/journal.pone.0041370. Epub 2012 Jul 19.

Abstract

Enzymes play a fundamental role in almost all biological processes and identification of catalytic residues is a crucial step for deciphering the biological functions and understanding the underlying catalytic mechanisms. In this work, we developed a novel structural feature called MEDscore to identify catalytic residues, which integrated the microenvironment (ME) and geometrical properties of amino acid residues. Firstly, we converted a residue's ME into a series of spatially neighboring residue pairs, whose likelihood of being located in a catalytic ME was deduced from a benchmark enzyme dataset. We then calculated an ME-based score, termed as MEscore, by summing up the likelihood of all residue pairs. Secondly, we defined a parameter called Dscore to measure the relative distance of a residue to the center of the protein, provided that catalytic residues are typically located in the center of the protein structure. Finally, we defined the MEDscore feature based on an effective nonlinear integration of MEscore and Dscore. When evaluated on a well-prepared benchmark dataset using five-fold cross-validation tests, MEDscore achieved a robust performance in identifying catalytic residues with an AUC1.0 of 0.889. At a ≤ 10% false positive rate control, MEDscore correctly identified approximately 70% of the catalytic residues. Remarkably, MEDscore achieved a competitive performance compared with the residue conservation score (e.g. CONscore), the most informative singular feature predominantly employed to identify catalytic residues. To the best of our knowledge, MEDscore is the first singular structural feature exhibiting such an advantage. More importantly, we found that MEDscore is complementary with CONscore and a significantly improved performance can be achieved by combining CONscore with MEDscore in a linear manner. As an implementation of this work, MEDscore has been made freely accessible at http://protein.cau.edu.cn/mepi/.

摘要

酶在几乎所有的生物过程中都起着至关重要的作用,而鉴定催化残基是破译生物功能和理解潜在催化机制的关键步骤。在这项工作中,我们开发了一种新的结构特征,称为 MEDscore,用于识别催化残基,该特征整合了氨基酸残基的微环境(ME)和几何特性。首先,我们将残基的 ME 转化为一系列空间相邻的残基对,其位于催化 ME 的可能性是从基准酶数据集推断出来的。然后,我们通过将所有残基对的可能性相加来计算基于 ME 的得分,称为 MEscore。其次,我们定义了一个称为 Dscore 的参数,用于测量残基到蛋白质中心的相对距离,因为催化残基通常位于蛋白质结构的中心。最后,我们基于 MEscore 和 Dscore 的有效非线性整合定义了 MEDscore 特征。在使用五重交叉验证测试对精心准备的基准数据集进行评估时,MEDscore 在识别催化残基方面表现出稳健的性能,AUC1.0 为 0.889。在 ≤ 10%假阳性率控制下,MEDscore 正确识别了约 70%的催化残基。值得注意的是,与主要用于识别催化残基的信息最丰富的单一特征残基保守得分(如 CONscore)相比,MEDscore 具有竞争力。据我们所知,MEDscore 是第一个具有这种优势的单一结构特征。更重要的是,我们发现 MEDscore 与 CONscore 互补,通过以线性方式将 CONscore 与 MEDscore 结合,可以获得显著提高的性能。作为这项工作的实现,MEDscore 已在 http://protein.cau.edu.cn/mepi/ 上免费提供。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6918/3400608/aed2320867be/pone.0041370.g001.jpg

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