Journal of Biology ›› 2020, Vol. 37 ›› Issue (4): 1-.doi: 10.3969/j.issn.2095-1736.2020.04.001
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Abstract: Directed evolution plays a central role in the fields of biocatalysis, biomedicine and biotechnology, etc. Taking advantages of increasingly computer performance and numerous datasets, artificial intelligence has rapidly developed. Recently, machine learning algorithms have also been applied to protein engineering, especially in helping prediction of protein structures, improving enzyme stability / selectivity / solubility, and guiding rational protein design as well as other functions. This paper reviews the state of the art in algorithms and descriptors used in enzyme engineering.
Key words: artificial intelligence, protein engineering, directed evolution, machine learning
CLC Number:
Q503
Q814
Q55
JIANG Ying-ying, QU Ge, SUN Zhou-tong. Machine learning-assisted enzyme directed evolution[J]. Journal of Biology, 2020, 37(4): 1-.
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http://www.swxzz.com/EN/Y2020/V37/I4/1