文献类型：期刊文献

英文题名：Engineering of Halide Methyltransferase BxHMT through Dynamic Cross-Correlation Network Analysis

作者：Gao, Chun-Yu[1,2];Yang, Gui-Ying[1,2];Ding, Xu-Wei[1,2];Xu, Jian-He[1,2];Cheng, Xiaolin[3];Zheng, Gao-Wei[1,2];Chen, Qi[1,2]

机构：[1]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Shanghai Collaborat Innovat Ctr Biomfg, Shanghai 200237, Peoples R China;[3]Ohio State Univ, Coll Pharm, Div Med Chem & Pharmacognosy, Columbus, OH 43210 USA

年份：2024

卷号：63

期号：25

外文期刊名：ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

收录：;EI(收录号：20242016089814);WOS:【SCI-EXPANDED(收录号:WOS:001222257300001)】；

基金：This work was financially supported by the National Key Research and Development Program of China (2021YFC2102300 and 2019YFA0905000), the National Natural Science Foundation of China (31971380), the Shanghai Commossion of Science and Technology (23HC1400200).

语种：英文

外文关键词：biocatalysis; halide methyltransferase; protein engineering; dynamic cross-correlation; network analysis

摘要：Halide methyltransferases (HMTs) provide an effective way to regenerate S-adenosyl methionine (SAM) from S-adenosyl homocysteine and reactive electrophiles, such as methyl iodide (MeI) and methyl toluene sulfonate (MeOTs). As compared with MeI, the cost-effective unnatural substrate MeOTs can be accessed directly from cheap and abundant alcohols, but shows only limited reactivity in SAM production. In this study, we developed a dynamic cross-correlation network analysis (DCCNA) strategy for quickly identifying hot spots influencing the catalytic efficiency of the enzyme, and applied it to the evolution of HMT from Paraburkholderia xenovorans. Finally, the optimal mutant, M4 (V55T/C125S/L127T/L129P), exhibited remarkable improvement, with a specific activity of 4.08 U/mg towards MeOTs, representing an 82-fold increase as compared to the wild-type (WT) enzyme. Notably, M4 also demonstrated a positive impact on the catalytic ability with other methyl donors. The structural mechanism behind the enhanced enzyme activity was uncovered by molecular dynamics simulations. Our work not only contributes a promising biocatalyst for the regeneration of SAM, but also offers a strategy for efficient enzyme engineering.