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Machine Learning Enables Selection of Epistatic Enzyme Mutants for Stability Against Unfolding and Detrimental Aggregation
ChemBioChem ( IF 3.2 ) Pub Date : 2020-10-22 , DOI: 10.1002/cbic.202000612
Guangyue Li 1 , Youcai Qin 1 , Nicolas T Fontaine 2 , Matthieu Ng Fuk Chong 2 , Miguel A Maria-Solano 3 , Ferran Feixas 3 , Xavier F Cadet 2 , Rudy Pandjaitan 2 , Marc Garcia-Borràs 3 , Frederic Cadet 2 , Manfred T Reetz 4, 5, 6
Affiliation  

A quick learner: Machine learning based on the innov'SAR algorithm leads to efficient selection of highly robust limonene epoxide hydrolase mutants with enhanced unfolding stability and resistance to aggregation by recognizing epistatic mutational interactions.
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中文翻译:

机器学习能够选择上位酶突变体,以保持稳定性,防止展开和有害聚集

快速学习者:基于 innov'SAR 算法的机器学习可通过识别上位突变相互作用,有效选择高度稳健的柠檬烯环氧化物水解酶突变体,这些突变体具有增强的解折叠稳定性和抗聚集性。
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更新日期:2020-10-22
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