Rate-Perturbing Single Amino Acid Mutation for Hydrolases: A Statistical Profiling
Rate-Perturbing Single Amino Acid Mutation for Hydrolases: A Statistical Profiling
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DOI：
10.1021/acs.jpcb.1c05901
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发表时间：
2021-09-15
影响因子：
3.3
通讯作者：
Yang, Zhongyue J.
中科院分区：
文献类型：
--
作者：
Yan, Bailu;Ran, Xinchun;Yang, Zhongyue J.
水解酶是现代化学、制药和环境科学的重要组成部分。识别提高催化效率的突变是设计和发现广泛的学术和工业用途的新水解酶的障碍。在这里，我们报告了具有单一氨基酸取代的速率干扰突变水解酶的统计分析。我们构建了一个完整的水解酶结构动力学数据库IntEnzyDB，其中包含3907个k(cat)s， 4175个k(M)s和2715个蛋白质数据库id。IntEnzyDB采用关系型架构，数据结构扁平化，可以方便高效地访问干净的表格数据，用于机器学习。我们对单个氨基酸突变如何影响周转率（即k(cat)）和效率（即k(cat)/ k - m）进行了统计分析，并特别强调了速率增强突变的特征。结果表明，与其他类型的残基相比，具有烃链的大块非极性残基突变具有更高的速率加速可能性。线性回归模型揭示了底物和突变残基的几何描述符，这些描述符介导了具有大量非极性突变的水解酶的速率扰动结果。在结构-动力学关系分析的基础上，我们观察到速率增强倾向与蛋白质大小无关。此外，我们观察到水解酶的远端突变（即距离活性位点100 ~ 10埃）更容易诱导效率中性和避免效率缺失，但也有类似的速率增强倾向。这些研究揭示了识别水解酶中速率增强突变的统计特征，这将潜在地指导水解酶在生物催化中的发现。
Hydrolases are a critical component for modern chemical, pharmaceutical, and environmental sciences. Identifying mutations that enhance catalytic efficiency presents a roadblock to design and to discover new hydrolases for broad academic and industrial uses. Here, we report the statistical profiling for rate- perturbing mutant hydrolases with a single amino acid substitution. We constructed an integrated structure-kinetics database for hydrolases, IntEnzyDB, which contains 3907 k(cat)s, 4175 K(M)s, and 2715 Protein Data Bank IDs. IntEnzyDB adopts a relational architecture with a flattened data structure, enabling facile and efficient access to clean and tabulated data for machine learning uses. We conducted statistical analyses on how single amino acids mutations influence the turnover number (i.e., k(cat)) and efficiency (i.e.,k(cat)/K-M), with a particular emphasis on profiling the features for rate-enhancing mutations. The results show that mutation to bulky nonpolar residues with a hydrocarbon chain involves a higher likelihood for rate acceleration than to other types of residues. Linear regression models reveal geometric descriptors of substrate and mutation residues that mediate rate-perturbing outcomes for hydrolases with bulky nonpolar mutations. On the basis of the analyses of the structure-kinetics relationship, we observe that the propensity for rate enhancement is independent of protein sizes. In addition, we observe that distal mutations (i.e., >10 angstrom from the active site) in hydrolases are significantly more prone to induce efficiency neutrality and avoid efficiency deletion but involve similar propensity for rate enhancement. The studies reveal the statistical features for identifying rate-enhancing mutations in hydrolases, which will potentially guide hydrolase discovery in biocatalysis.