henhaobio
Sign in

Science AdvancesSynthetic BiologyPeer-reviewed journal article

Systematic Engineering of Artificial Metalloenzymes for New-to-Nature Reactions

Tobias VornholtiD, Fadri ChristoffeliD, Michela M. PellizzoniiD, Sven PankeiD, Thomas R. WardiD, Markus JeschekiD

PDFDOIPreprint

Abstract

Artificial metalloenzymes (ArMs) catalyzing new-to-nature reactions under mild conditions could play an important role in the transition to a sustainable, circular economy. While ArMs have been created for a variety of bioorthogonal transformations, attempts at optimizing their performance by enzyme engineering have been case-specific and resulted only in modest improvements. To realize the full potential of ArMs, methods that enable the rapid discovery of highly active ArM variants for any reaction of interest are required. Here, we introduce a broadly applicable, automation-compatible ArM engineering platform, which relies on periplasmic compartmentalization in Escherichia coli to rapidly and reliably identify improved ArM variants based on the biotin-streptavidin technology. We systematically assess 400 ArM mutants for five bioorthogonal transformations involving different metal cofactors, reaction mechanisms and substrate-product pairs, including novel ArMs for gold-catalyzed hydroamination and hydroarylation. The achieved activity enhancements of up to fifteen-fold over wild type highlight the potential of the systematic approach to ArM engineering. We further capitalize on the sequence-activity data to suggest and validate smart strategies for future screening campaigns. This systematic, multi-reaction study has important implications for the development of highly active ArMs for novel applications in biocatalysis and synthetic biology.

Citations
96
FWCI
5.94
Field percentile
top 2%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISVornholt '24Shan '26Nesr '26Merlicek '25Vallapurack '21Wang '25
69% semantic matchSynthetic Biology
Tobias Vornholt, Mojmír Mutný, Gregor W. Schmidt+6 more·ACS Central Science·May 22, 2024· 33 citations