文献类型：期刊文献

英文题名：Mechanism-Guided Computational Design of ω-Transaminase by Reprograming of High-Energy-Barrier Steps

作者：Yang, Lin[1];Zhang, Kaiyue[1];Xu, Meng[1];Xie, Youyu[1];Meng, Xiangqi[1];Wang, Hualei[1];Wei, Dongzhi[1]

机构：[1]East China Univ Sci & Technol, New World Inst Biotechnol, State Key Lab Bioreactor Engn, Shanghai, Peoples R China

年份：2022

卷号：61

期号：12

外文期刊名：ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

收录：;EI(收录号：20224913213712);WOS:【SCI-EXPANDED(收录号:WOS:000889086200001)】；

基金：Acknowledgements This research was supported by the National Natural Science Foundation of China (No. 22078097) and the National Key Research and Development Program of China (No. 2021YFC2100300). We are grateful for access to beamline BL19U1 at the Shanghai Synchrotron Radiation Facility (SSRF) and thank the beamline staff for their technical help.

语种：英文

外文关键词：Chiral Amines; Protein Engineering; QM Calculation; Rosetta Design; omega-Transaminase

摘要：omega-Transaminases (omega-TAs) show considerable potential for the synthesis of chiral amines. However, their low catalytic efficiency towards bulky substrates limits their application, and complicated catalytic mechanisms prevent precise enzyme design. Herein, we address this challenge using a mechanism-guided computational enzyme design strategy by reprograming the transition and ground states in key reaction steps. The common features among the three high-energy-barrier steps responsible for the low catalytic efficiency were revealed using quantum mechanics (QM). Five key residues were simultaneously tailored to stabilize the rate-limiting transition state with the aid of the Rosetta design. The 14 top-ranked variants showed 16.9-143-fold improved catalytic activity. The catalytic efficiency of the best variant, M9 (Q25F/M60W/W64F/I266A), was significantly increased, with a 1660-fold increase in k(cat)/K-m and a 1.5-26.8-fold increase in turnover number (TON) towards various indanone derivatives.