重组
定向进化
定向分子进化
上位性
基石
合成生物学
突变
选择(遗传算法)
计算机科学
基因组工程
蛋白质工程
多样性(政治)
生化工程
代谢工程
同源重组
生物
遗传学
计算生物学
突变
人工智能
工程类
清脆的
基因组编辑
基因
生物化学
酶
艺术
社会学
突变体
人类学
视觉艺术
作者
Xinyue Wang,Anni Li,Xiujuan Li,Haiyang Cui
标识
DOI:10.1002/chem.202303889
摘要
Directed evolution stands as a seminal technology for generating novel protein functionalities, a cornerstone in biocatalysis, metabolic engineering, and synthetic biology. Today, with the development of various mutagenesis methods and advanced analytical machines, the challenge of diversity generation and high-throughput screening platforms is largely solved, and one of the remaining challenges is: how to empower the potential of single beneficial substitutions with recombination to achieve the epistatic effect. This review overviews experimental and computer-assisted recombination methods in protein engineering campaigns. In addition, integrated and machine learning-guided strategies were highlighted to discuss how these recombination approaches contribute to generating the screening library with better diversity, coverage, and size. A decision tree was finally summarized to guide the further selection of proper recombination strategies in practice, which was beneficial for accelerating protein engineering.
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