合理设计
计算模型
背景(考古学)
生化工程
计算机科学
计算生物学
蛋白质设计
化学
转化式学习
生物系统
序列(生物学)
氢键
定向进化
钥匙(锁)
合成生物学
纳米技术
组合化学
选择性
生物催化
残留物(化学)
设计要素和原则
不完美的
药物设计
计算复杂性理论
催化作用
催化效率
蛋白质工程
作者
Ruichen Gao,Xiaodi Fu,Zonglin Li,Zheng Wang,Zhiyao Wang,Guanjian Li,Jun Ge,Frank Hollmann,Zhanfeng Wang,Zhanfeng Wang,Wen‐Yong Lou,Xiaoling Wu
出处
期刊:Science Advances
[American Association for the Advancement of Science]
日期:2026-01-30
卷期号:12 (5): eaeb6329-eaeb6329
被引量:2
标识
DOI:10.1126/sciadv.aeb6329
摘要
Computational rational design has emerged as a transformative approach to engineer enzymes with tailored selectivity and efficiency. In the context of carbon-hydrogen oxidation, a key challenge in synthetic chemistry, unspecific peroxygenases (UPOs) directly oxidize unactivated carbon-hydrogen bonds using hydrogen peroxide, yet their utility is limited by low activity and imperfect selectivity. By computational rational design, this study systematically navigated vast sequence spaces to identify mutations that enhance catalytic performance of UPOs, lastly yielded UPO variants with 13-fold enhanced activity and >99% enantioselectivity, and revealed the dominant role of residue Lys 165 in activity and enantioselectivity. This study shows how computational strategies overcome evolutionary constraints to deliver efficient biocatalysts for synthetic chemistry.
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