Evolving artificial metalloenzymes via random mutagenesis View Full Text


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Article Info

DATE

2018-03

AUTHORS

Hao Yang, Alan M. Swartz, Hyun June Park, Poonam Srivastava, Ken Ellis-Guardiola, David M. Upp, Gihoon Lee, Ketaki Belsare, Yifan Gu, Chen Zhang, Raymond E. Moellering, Jared C. Lewis

ABSTRACT

Random mutagenesis has the potential to optimize the efficiency and selectivity of protein catalysts without requiring detailed knowledge of protein structure; however, introducing synthetic metal cofactors complicates the expression and screening of enzyme libraries, and activity arising from free cofactor must be eliminated. Here we report an efficient platform to create and screen libraries of artificial metalloenzymes (ArMs) via random mutagenesis, which we use to evolve highly selective dirhodium cyclopropanases. Error-prone PCR and combinatorial codon mutagenesis enabled multiplexed analysis of random mutations, including at sites distal to the putative ArM active site that are difficult to identify using targeted mutagenesis approaches. Variants that exhibited significantly improved selectivity for each of the cyclopropane product enantiomers were identified, and higher activity than previously reported ArM cyclopropanases obtained via targeted mutagenesis was also observed. This improved selectivity carried over to other dirhodium-catalysed transformations, including N-H, S-H and Si-H insertion, demonstrating that ArMs evolved for one reaction can serve as starting points to evolve catalysts for others. More... »

PAGES

318

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/nchem.2927

DOI

http://dx.doi.org/10.1038/nchem.2927

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1100553251

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/29461523


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