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AI-driven engineering of EgtD enabling high-efficiency ergothioneine synthesis with a multi-enzyme cascade

文献类型：期刊论文

作者Li, Yamiao1,2; Rao, Jingxin3,6; Jiang, Zhentao1,2; Zhang, Xinyi1,2; Zhu, Qiang1,2; Zhu, Caokai1,2; Yu, Wenli1,2; Dong, Xin1,2; Gao, Shanshan1,2; Zhang, Wenchi4
刊名INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
出版日期2025-10-01
卷号327页码:13
关键词Methyltransferase Molecular dynamics Ergothioneine
ISSN号0141-8130
DOI10.1016/j.ijbiomac.2025.147266
英文摘要Ergothioneine (ERG), a sulfur-containing natural antioxidant with significant biomedical potentials, has long been limited by low productivity in microbial fermentation. Here, we report the first high-efficiency in vitro reconstruction of a multi-enzyme cascade for ERG biosynthesis. To address the rate-limiting histidine methylation step, we employed a synergistic strategy integrating machine learning-based kinetic prediction (CataPro, DLkcat), molecular dynamics simulations, and conformational dynamics analysis to guide site-directed mutagenesis of Mycolicibacrterium smegmatis EgtD. This yielded a triple mutant M3 (L53A/T59S/E282S) with 3.4- and 2.8-fold enhancements in catalytic efficiency (kcat/Km) toward histidine and S-adenosyl-L-methionine (SAM), respectively. Mechanistically, M3 enhances catalysis by reducing the SAM-histine distance, optimizing the catalytic angle, eliminating non-productive hydrogen bonds, and unlocking a secondary ligand tunnel through a mutation-induced gating mechanism. When coupled with a SAM-regeneration module, the engineered cascade enables preparative-scale ERG synthesis, reaching a titer of 6.05 g center dot L- 1 within 14.5 h and productivity of 10.01 g center dot L- 1d- 1-the highest report to date. This work showcases a structure-guided, AI-assisted approach that overcomes evolutionary constraints, unlocks latent reactivity, and accelerates the development of efficient biocatalytic cascades for high-value compound synthesis.
WOS关键词STRUCTURAL BASIS
资助项目Program of Introducing Talents of Discipline to Universities[LITE2018-12] ; [111-2-06]
WOS研究方向Biochemistry & Molecular Biology ; Chemistry ; Polymer Science
语种英语
WOS记录号WOS:001567280700001
出版者ELSEVIER
源URL[http://119.78.100.183/handle/2S10ELR8/321444]  
专题国家级研究中心_原创新药研究全国重点实验室
通讯作者Zhang, Rongzhen
作者单位1.Jiangnan Univ, Sch Biotechnol, Minist Educ, Wuxi 214122, Peoples R China
2.Jiangnan Univ, Key Lab Ind Biotechnol, Minist Educ, Wuxi 214122, Peoples R China
3.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, State Key Lab Drug Res, Shanghai 201203, Peoples R China
4.Johns Hopkins Univ, Sch Med, Solomon H Snyder Dept Neurosci, Baltimore, MD 21205 USA
5.Univ Chinese Acad Sci, Shanghai Inst Organ Chem, State Key Lab Chem Biol, 345 Ling Ling Rd, Shanghai 200032, Peoples R China
6.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Li, Yamiao,Rao, Jingxin,Jiang, Zhentao,et al. AI-driven engineering of EgtD enabling high-efficiency ergothioneine synthesis with a multi-enzyme cascade[J]. INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES,2025,327:13.
APA Li, Yamiao.,Rao, Jingxin.,Jiang, Zhentao.,Zhang, Xinyi.,Zhu, Qiang.,...&Zhang, Rongzhen.(2025).AI-driven engineering of EgtD enabling high-efficiency ergothioneine synthesis with a multi-enzyme cascade.INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES,327,13.
MLA Li, Yamiao,et al."AI-driven engineering of EgtD enabling high-efficiency ergothioneine synthesis with a multi-enzyme cascade".INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES 327(2025):13.

入库方式： OAI收割

来源：上海药物研究所

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