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酶选择性的计算机辅助理解与工程设计

Computer-aided understanding and engineering of enzymatic selectivity.

作者信息

Wu Lunjie, Qin Lei, Nie Yao, Xu Yan, Zhao Yi-Lei

机构信息

School of Biotechnology and Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China.

School of Biotechnology and Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; Suqian Industrial Technology Research Institute of Jiangnan University, Suqian 223814, China.

出版信息

Biotechnol Adv. 2022 Jan-Feb;54:107793. doi: 10.1016/j.biotechadv.2021.107793. Epub 2021 Jul 2.

DOI:10.1016/j.biotechadv.2021.107793
PMID:34217814
Abstract

Enzymes offering chemo-, regio-, and stereoselectivity enable the asymmetric synthesis of high-value chiral molecules. Unfortunately, the drawback that naturally occurring enzymes are often inefficient or have undesired selectivity toward non-native substrates hinders the broadening of biocatalytic applications. To match the demands of specific selectivity in asymmetric synthesis, biochemists have implemented various computer-aided strategies in understanding and engineering enzymatic selectivity, diversifying the available repository of artificial enzymes. Here, given that the entire asymmetric catalytic cycle, involving precise interactions within the active pocket and substrate transport in the enzyme channel, could affect the enzymatic efficiency and selectivity, we presented a comprehensive overview of the computer-aided workflow for enzymatic selectivity. This review includes a mechanistic understanding of enzymatic selectivity based on quantum mechanical calculations, rational design of enzymatic selectivity guided by enzyme-substrate interactions, and enzymatic selectivity regulation via enzyme channel engineering. Finally, we discussed the computational paradigm for designing enzyme selectivity in silico to facilitate the advancement of asymmetric biosynthesis.

摘要

具有化学、区域和立体选择性的酶能够实现高价值手性分子的不对称合成。不幸的是,天然存在的酶往往效率低下或对非天然底物具有不理想的选择性,这一缺点阻碍了生物催化应用的拓展。为了满足不对称合成中特定选择性的需求,生物化学家们采用了各种计算机辅助策略来理解和设计酶的选择性,从而丰富了人工酶的库。在此,鉴于整个不对称催化循环,包括活性口袋内的精确相互作用以及酶通道中的底物转运,都会影响酶的效率和选择性,我们对酶选择性的计算机辅助工作流程进行了全面概述。本综述包括基于量子力学计算对酶选择性的机理理解、由酶 - 底物相互作用指导的酶选择性合理设计以及通过酶通道工程对酶选择性的调控。最后,我们讨论了在计算机上设计酶选择性的计算范式,以促进不对称生物合成的发展。

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