Generative artificial intelligence for enzyme design: Recent advances in models and applications

被引:0
|
作者
Wen, Shuixiu [1 ]
Zheng, Wen [2 ]
Bornscheuer, Uwe T. [3 ]
Wu, Shuke [1 ]
机构
[1] Huazhong Agr Univ, Coll Life Sci & Technol, Natl Key Lab Agr Microbiol, 1 Shizishan St, Wuhan 430070, Peoples R China
[2] Wuhan Grand Pharmaceut Grp Biotechnol Co Ltd, B6 Opt Valley Biol Pk, Wuhan 430000, Peoples R China
[3] Univ Greifswald, Inst Biochem, Dept Biotechnol & Enzyme Catalysis, Felix Hausdorff Str 4, D-17487 Greifswald, Germany
基金
中国国家自然科学基金;
关键词
artificial intelligence; biocatalysis; enzyme design; generative models; PROTEIN-SEQUENCE DESIGN; REDESIGN;
D O I
10.1016/j.cogsc.2025.101010
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Enzyme catalysis is a key enabling technology for green and sustainable production of chemicals. Developing suitable enzymes is at the heart of this technology, which is currently changing by Artificial Intelligence (AI) such as machine learning. AI-based methods were used for enzyme discovery and design. We review the recent advances in generative AI models for enzyme design, with a particular focus on those that have been validated by experiments. Furthermore, we discuss the applications of the enzymes designed by generative AI, including artificial luciferases, non-heme iron (II)-dependent oxygenases, and P450 enzymes. We provide our opinions on several current issues encountered in computational enzyme design. With the fast development of new generative models in enzymes and the implementation of these models by the research community, we believe that the precise design of efficient enzymes with new catalytic functions and/or potential industrial applications will be a mature method in the near future.
引用
收藏
页数:10
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