Characterization of carboxylic acid reductases as enzymes in the toolbox for synthetic chemistry
This is the author accepted manuscript of an open access article. The final version is available from Wiley via the DOI in this record. Distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/
Carboxylic acid reductase enzymes (CARs) meet the demand in synthetic chemistry for a green and regio-specific route to aldehydes from their respective carboxylic acids. However, relatively few of these enzymes have been characterized. A sequence alignment with members of the ANL superfamily of enzymes shed light on CAR functional dynamics. Using a phylogenetic analysis of known and hypothetical CARs, four unstudied enzymes were selected, and for the first time, a thorough biochemical characterization carried out. Kinetic analysis of these enzymes with various substrates shows they have a broad, but similar substrate specificity. Electron rich acids are favored, suggesting that the first step in the proposed reaction mechanism, attack by the carboxylate on the -phosphate of ATP, is the step determining substrate specificity and reaction kinetics. The effects of pH and temperature provide a clear operational window for the use of these CARs, while investigation of product inhibition by NADP+, AMP and pyrophosphate (PPi) indicates that binding of substrates at the adenylation domain is ordered with ATP binding first. This paper consolidates CARs as important and exciting enzymes in the toolbox for sustainable chemistry, providing specifications for their use as a biocatalyst.
The authors thank Andrew Hill (University of Manchester) for providing many of the substrates tested, the pCDF-Sfp plasmid and the plasmid for the expression of niCAR; and Clive Mountain (GSK), Stacy Clark (GSK), and Alison Hill (University of Exeter) for advice on the chemistry of the CAR reaction, and Jennifer Farrar (Georgia Institute of Technology) for providing walltime on her server to run the Bayesian analyses. Nzomics (Prof. Gary Black and team) and Prozomix (Simon Charnock and team) are gratefully acknowledged for cloning msCAR and tpCAR. WF was funded by BBSRC (grant no. BB/K501001/1) and GlaxoSmithKline; AT was funded by BBSRC (grant no. BB/J014400/1). Requests for raw data should be sent to NJH.
Vol. 9, pp. 1–14.