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酶工程:从人工设计到人工智能
引用本文:王雅丽,付友思,陈俊宏,黄佳城,廖浪星,张永辉,方柏山. 酶工程:从人工设计到人工智能[J]. 化工学报, 2021, 72(7): 3590-3600. DOI: 10.11949/0438-1157.20201941
作者姓名:王雅丽  付友思  陈俊宏  黄佳城  廖浪星  张永辉  方柏山
作者单位:1.厦门大学化学化工学院,福建 厦门 361005;2.厦门市合成生物学重点实验室,福建 厦门 361005;3.福建省化学生物学重点实验室,福建 厦门 361005;4.集美大学食品与生物工程学院,福建 厦门 361021
基金项目:国家自然科学基金项目(21978245)
摘    要:计算机在酶工程中的应用使得酶的序列空间探索度不断被扩大。随着不同分子力场参数的建立,涌现出诸多以计算分子能量为基础的算法,并被用于酶的催化活性、稳定性、底物特异性等的改造与筛选。伴随计算机硬件的提升与算法的优化,从头设计全新功能的人工酶取得成功并得以发展。近年来,人工智能在蛋白质结构预测上不断获得突破,同时也被应用到酶的设计中。介绍了分子力场基础和酶设计与筛选的算法,重点阐述了从头设计的方法和成功案例,以及机器学习设计酶的流程和最新的研究进展,展望了人工智能在酶工程领域的未来发展,为酶的改造与全新功能的生物催化剂的设计助力。

关 键 词:酶工程  从头设计  人工智能  机理  能量函数  
收稿时间:2020-12-30

Enzyme engineering: from artificial design to artificial intelligence
WANG Yali,FU Yousi,CHEN Junhong,HUANG Jiacheng,LIAO Langxing,ZHANG Yonghui,FANG Baishan. Enzyme engineering: from artificial design to artificial intelligence[J]. Journal of Chemical Industry and Engineering(China), 2021, 72(7): 3590-3600. DOI: 10.11949/0438-1157.20201941
Authors:WANG Yali  FU Yousi  CHEN Junhong  HUANG Jiacheng  LIAO Langxing  ZHANG Yonghui  FANG Baishan
Affiliation:1.College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, Fujian, China;2.The Key Laboratory for Synthetic Biotechnology of Xiamen City, Xiamen University, Xiamen 361005, Fujian, China;3.The Key Laboratory for Chemical Biology of Fujian Province, Xiamen 361005, Fujian, China;4.College of Food and Biological Engineering, Jimei University, Xiamen 361021, Fujian, China
Abstract:The application of computers in enzyme engineering has led to the continuous expansion of the sequence space exploration of enzymes. With the establishment of different molecular force fields, many algorithms came out upon computing molecular energy and were applied to the enzyme redesign and screening of catalytic activity, stability, substrate specificity, etc. With the improvement of computer hardware and the optimization of algorithms, artificial enzymes with completely new functions have been successfully designed and developed. In recent years, artificial intelligence has made breakthroughs in protein structure prediction and has also been applied to enzyme design. Basis of molecular force field and enzyme design and selection algorithm were introduced in this paper. The methods and successful cases of de novo design, as well as the process of machine learning to design enzymes and the latest research progress are described emphatically. The outlooks of artificial intelligence in the enzyme engineering are given in the end, contributing for enzymatic engineering and brand-new functional biocatalysts design.
Keywords:enzyme engineering  de novo design  artificial intelligence  mechanism  energy function  
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