《生命科学》 2021, 33(12): 1493-1501

合成生物学酶改造设计技术的研究进展

王　千¹ , 白　杰^1,2 , 江会锋^1,*

¹中国科学院天津工业生物技术研究所，中国科学院系统微生物工程重点 实验室，天津 300308 ²天津科技大学生物工程学院，天津 300457

摘　要：

酶是一种优秀的生物催化剂，酶促反应以高效性、专一性、条件温和、绿色环保等优点著称，但天然酶仍存在活性低、稳定性差、专一性不佳等问题。合成生物学与人工智能技术的不断进步为天然酶的催化机制研究、催化活性改造以及新功能酶的设计提出了更高的要求和全新的思路。定向进化、理性及半理性设计和新酶设计等是目前发展和应用较为成熟的酶改造设计技术。同时，机器学习也为拓展酶改造设计技术提供了新的可能。该文对经典的酶改造设计方法和机器学习指导的酶改造设计进行了概括，着眼于酶改造设计技术的发展及其应用，为合成生物学中关键酶的设计改造提供参考和依据。

通讯作者：江会锋 , Email:jiang_hf@tib.cas.cn

Research progress on technologies of enzyme engineering and design in synthetic biology

WANG Qian¹ , BAI Jie^1,2 , JIANG Hui-Feng^1,*

¹Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China ²College of Biotechnology, Tianjin University of Science and Technology, Tianjin 300457, China

Abstract:

As natural catalysts, enzymes have excellent characteristics like high catalytic efficiency, high substrate specificity, mild reaction conditions, environmental friendliness, and so on. However, natural enzymes still suffer the shortages like low catalytic activity, poor stability, and promiscuous substrate specificity. The continuous advancement of synthetic biology and artificial intelligence put forward higher requirements and provide new insights for understanding the catalytic mechanisms, engineering the catalytic properties, and designing enzymes with novel functions. Currently developed and maturely applied enzyme engineering methods include directed evolution, rational and semi-rational design, new enzyme design, etc. Meanwhile, machine learning also provides new possibilities for enzyme engineering and design. This paper outlines the classical and machine learning-guided enzyme engineering and design methods, focuses on the advancements and applications of enzyme engineering and design technologies, so as to provide reference and basis for the engineering of key enzymes serve in synthetic
biology.

Communication Author：JIANG Hui-Feng , Email:jiang_hf@tib.cas.cn