Evolving artificial metalloenzymes via random mutagenesis

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.

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Figure 1: Model reaction and ArM structure.
Figure 2: Overview of ArM evolution protocol.
Figure 3: Overview of the directed evolution lineages generated and time-course comparison of several catalysts.
Figure 4: Location of mutations in evolved ArMs.
Figure 5: Combinatorial codon mutagenesis sites and protocol.
Figure 6: Time-course experiments of ArM-catalysed cyclopropanations of styrene with (4-methoxyphenyl)methyldiazoacetate.

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Acknowledgements

This work was supported by, or in part by, the US Army Research Laboratory and the US Army Research Office under contract/grant nos. W911NF-14-1-0334 and 66796-LS-RIP (to J.C.L.), the National Science Foundation (NSF) under CAREER Award CHE-1351991 (to J.C.L.), The David and Lucile Packard Foundation (to J.C.L.), the National Institutes of Health (NIH) National Cancer Institute (R00CA175399 to R.E.M.), the Damon Runyon Cancer Research Foundation (DFS-08-14 to R.E.M.) and the NSF under the Center for Chemical Innovation Center for Selective C–H Functionalization (CHE-1700982, to J.C.L.). K.E.G. and D.M.U. were funded by an NIH Chemistry and Biology Interface Training Grant (T32 GM008720) and G.L. was supported by the Kwanjeong Educational Foundation. MS data were acquired on instruments purchased using an NSF instrumentation grant (CHE-1048528).

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H.Y. and P.S. developed the soluble ArM evolution procedure. C.Z. optimized the soluble ArM evolution procedure. A.M.S. and D.M.U. optimized the soluble ArM evolution procedure and collected conversion and selectivity data for all evolved ArMs. H.J.P. optimized and executed the immobilized ArM evolution procedure. K.B. and Y.G. cloned POP amber mutants and the combinatorial codon mutagenesis library. K.E.-G., G.L. and R.E.M. conducted and analysed the LC-MS/MS experiments. J.C.L. devised the experiments and procedures, designed the ArM variants and libraries, analysed data and wrote the manuscript.

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Correspondence to Jared C. Lewis.

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Yang, H., Swartz, A., Park, H. et al. Evolving artificial metalloenzymes via random mutagenesis. Nature Chem 10, 318–324 (2018). https://doi.org/10.1038/nchem.2927

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