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长程构象动力学导致多种催化酶特性的普遍协同突变效应出现。

Pervasive cooperative mutational effects on multiple catalytic enzyme traits emerge via long-range conformational dynamics.

机构信息

Biosyntia ApS, Copenhagen, Denmark.

State Key Laboratory of Biocatalysis and Enzyme Engineering, Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, Hubei Key Laboratory of Industrial Biotechnology, School of Life Sciences, Hubei University, Wuhan, P. R. China.

出版信息

Nat Commun. 2021 Mar 12;12(1):1621. doi: 10.1038/s41467-021-21833-w.

DOI:10.1038/s41467-021-21833-w
PMID:33712579
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7955134/
Abstract

Multidimensional fitness landscapes provide insights into the molecular basis of laboratory and natural evolution. To date, such efforts usually focus on limited protein families and a single enzyme trait, with little concern about the relationship between protein epistasis and conformational dynamics. Here, we report a multiparametric fitness landscape for a cytochrome P450 monooxygenase that was engineered for the regio- and stereoselective hydroxylation of a steroid. We develop a computational program to automatically quantify non-additive effects among all possible mutational pathways, finding pervasive cooperative signs and magnitude epistasis on multiple catalytic traits. By using quantum mechanics and molecular dynamics simulations, we show that these effects are modulated by long-range interactions in loops, helices and β-strands that gate the substrate access channel allowing for optimal catalysis. Our work highlights the importance of conformational dynamics on epistasis in an enzyme involved in secondary metabolism and offers insights for engineering P450s.

摘要

多维适应度景观为实验室和自然进化的分子基础提供了深入的了解。迄今为止,此类研究通常集中于有限的蛋白质家族和单个酶特性,很少关注蛋白质上位性与构象动力学之间的关系。在这里,我们报告了一种细胞色素 P450 单加氧酶的多参数适应度景观,该酶经过工程设计可实现甾体的区域和立体选择性羟化。我们开发了一个计算程序来自动量化所有可能突变途径之间的非加性效应,发现多个催化特性上普遍存在协同符号和幅度上位性。通过使用量子力学和分子动力学模拟,我们表明这些效应受到环、螺旋和β-链中远程相互作用的调节,这些相互作用控制着底物进入通道,从而实现最佳催化。我们的工作强调了构象动力学对涉及次生代谢的酶中上位性的重要性,并为 P450 的工程设计提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/9a2614406d37/41467_2021_21833_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/50d6e583a092/41467_2021_21833_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/5f1406417be4/41467_2021_21833_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/7a6345df5cc3/41467_2021_21833_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/bfdb62d52e98/41467_2021_21833_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/b8b3ad3d37ba/41467_2021_21833_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/9218a1ada6d5/41467_2021_21833_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/9a2614406d37/41467_2021_21833_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/50d6e583a092/41467_2021_21833_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/5f1406417be4/41467_2021_21833_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/7a6345df5cc3/41467_2021_21833_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/bfdb62d52e98/41467_2021_21833_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/b8b3ad3d37ba/41467_2021_21833_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/9218a1ada6d5/41467_2021_21833_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d46/7955134/9a2614406d37/41467_2021_21833_Fig7_HTML.jpg

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