Discovery, Design, and Structural Characterization of Alkane-Producing Enzymes across the Ferritin-like Superfamily

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...

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Bibliographic Details
Published in:Biochemistry (Easton) 2020-10, Vol.59 (40), p.3834-3843
Main Authors: Mak, Wai Shun, Wang, XiaoKang, Arenas, Rigoberto, Cui, Youtian, Bertolani, Steve, Deng, Wen Qiao, Tagkopoulos, Ilias, Wilson, David K, Siegel, Justin B
Format: Article
Language:English
Subjects:
Aldehydes - metabolism
Alkanes - metabolism
Bacteria - chemistry
Bacteria - enzymology
Bacteria - genetics
Bacteria - metabolism
Bacterial Proteins - chemistry
Bacterial Proteins - genetics
Bacterial Proteins - metabolism
Ferritins - chemistry
Ferritins - genetics
Ferritins - metabolism
Genes, Bacterial
Models, Molecular
Oxygenases - chemistry
Oxygenases - genetics
Oxygenases - metabolism
Protein Conformation
Protein Engineering
Ribonucleotide Reductases - chemistry
Ribonucleotide Reductases - genetics
Ribonucleotide Reductases - metabolism
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Summary: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.
ISSN:0006-2960
1520-4995
DOI:10.1021/acs.biochem.0c00665