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Discovery, Design, and Structural Characterization of Alkane-Producing Enzymes across the Ferritin-like Superfamily.
Biochemistry ( IF 2.9 ) Pub Date : 2020-09-16 , DOI: 10.1021/acs.biochem.0c00665
Wai Shun Mak 1 , XiaoKang Wang 2 , Rigoberto Arenas 1, 3 , Youtian Cui 1 , Steve Bertolani 1 , Wen Qiao Deng 4 , Ilias Tagkopoulos 2, 5, 6 , David K Wilson 3, 7 , Justin B Siegel 1, 5, 8
Affiliation  

To complement established rational and evolutionary protein design approaches, significant efforts are being made to utilize computational modeling and the diversity of naturally occurring protein sequences. Here, we combine structural biology, genomic mining, and computational modeling to identify structural features critical to aldehyde deformylating oxygenases (ADOs), an enzyme family that has significant implications in synthetic biology and chemoenzymatic synthesis. Through these efforts, we discovered latent ADO-like function across the ferritin-like superfamily in various species of Bacteria and Archaea. We created a machine learning model that uses protein structural features to discriminate ADO-like activity. Computational enzyme design tools were then utilized to introduce ADO-like activity into the small subunit of Escherichia coli class I ribonucleotide reductase. The integrated approach of genomic mining, structural biology, molecular modeling, and machine learning has the potential to be utilized for rapid discovery and modulation of functions across enzyme families.

中文翻译:

铁蛋白样超家族中产烷烃的酶的发现,设计和结构表征。

为了补充已建立的合理的和进化的蛋白质设计方法,人们正在做出巨大的努力来利用计算模型和天然蛋白质序列的多样性。在这里,我们结合结构生物学,基因组挖掘和计算模型来确定对醛脱甲酰加氧酶(ADOs)至关重要的结构特征,该酶家族在合成生物学和化学酶法合成中具有重要意义。通过这些努力,我们在细菌和古细菌的各种物种中发现了类似铁蛋白样超家族的潜在ADO样功能。我们创建了一个机器学习模型,该模型使用蛋白质的结构特征来区分类似ADO的活性。然后利用计算酶设计工具将ADO样活性引入到小亚基中大肠杆菌I类核糖核苷酸还原酶。基因组挖掘,结构生物学,分子建模和机器学习的集成方法有可能被用于快速发现和调节酶家族功能的潜力。
更新日期:2020-10-13
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