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Evolving Artificial Metalloenzymes via Random Mutagenesis
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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5891097/ https://www.ncbi.nlm.nih.gov/pubmed/29461523 http://dx.doi.org/10.1038/nchem.2927 |
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author | Yang, Hao Swartz, Alan M. Park, Hyun June Srivastava, Poonam Ellis-Guardiola, Ken Upp, David M. Lee, Gihoon Belsare, Ketaki Gu, Yifan Zhang, Chen Moellering, Raymond E. Lewis, Jared C. |
author_facet | Yang, Hao Swartz, Alan M. Park, Hyun June Srivastava, Poonam Ellis-Guardiola, Ken Upp, David M. Lee, Gihoon Belsare, Ketaki Gu, Yifan Zhang, Chen Moellering, Raymond E. Lewis, Jared C. |
author_sort | Yang, Hao |
collection | PubMed |
description | 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 co-factor 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 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 catalyzed 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. |
format | Online Article Text |
id | pubmed-5891097 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
record_format | MEDLINE/PubMed |
spelling | pubmed-58910972018-07-22 Evolving Artificial Metalloenzymes via Random Mutagenesis Yang, Hao Swartz, Alan M. Park, Hyun June Srivastava, Poonam Ellis-Guardiola, Ken Upp, David M. Lee, Gihoon Belsare, Ketaki Gu, Yifan Zhang, Chen Moellering, Raymond E. Lewis, Jared C. Nat Chem Article 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 co-factor 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 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 catalyzed 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. 2018-01-22 2018-03 /pmc/articles/PMC5891097/ /pubmed/29461523 http://dx.doi.org/10.1038/nchem.2927 Text en Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Yang, Hao Swartz, Alan M. Park, Hyun June Srivastava, Poonam Ellis-Guardiola, Ken Upp, David M. Lee, Gihoon Belsare, Ketaki Gu, Yifan Zhang, Chen Moellering, Raymond E. Lewis, Jared C. Evolving Artificial Metalloenzymes via Random Mutagenesis |
title | Evolving Artificial Metalloenzymes via Random Mutagenesis |
title_full | Evolving Artificial Metalloenzymes via Random Mutagenesis |
title_fullStr | Evolving Artificial Metalloenzymes via Random Mutagenesis |
title_full_unstemmed | Evolving Artificial Metalloenzymes via Random Mutagenesis |
title_short | Evolving Artificial Metalloenzymes via Random Mutagenesis |
title_sort | evolving artificial metalloenzymes via random mutagenesis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5891097/ https://www.ncbi.nlm.nih.gov/pubmed/29461523 http://dx.doi.org/10.1038/nchem.2927 |
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