Issue 20, 2021

Computational studies on the substrate specificity of an acyltransferase domain from salinomycin polyketide synthase

Abstract

Polyketides are a large group of natural products with diverse chemical structures and biological activities. They are biosynthesized by modular polyketide synthases (PKSs) from coenzyme A (CoA) thioesters of short-chain carboxylic acids like malonyl-CoA (MCoA), methylmalonyl-CoA (MMCoA) and ethylmalonyl-CoA (EMCoA). Acyltransferase (AT) domains of modular PKSs are responsible for selecting CoA thioesters and therefore attractive targets for engineering to generate novel polyketides. Herein, molecular dynamics (MD) simulations combined with quantum mechanical/molecular-mechanical (QM/MM) calculations were conducted to dissect the substrate specificity of an AT domain from the 14th module of the salinomycin modular PKS (SalAT14), which displays a preference for its cognate substrate EMCoA over MCoA and MMCoA. Comparison of MD simulations unveiled that the hydrophobic interactions between the active site residues and the acyl groups exert a significant effect on enzyme–substrate recognition. The complex of SalAT14 and its cognate substrate EMCoA exhibited a greater tendency to stay in a conformation suitable for the reaction. QM/MM calculations demonstrated that the concerted nucleophilic attack on the thioester carbonyl group of the substrate is the rate-limiting step in the first half of transacylation. Our computational investigations revealed the structural basis of AT specificity and could potentially help the engineering of modular PKSs.

Graphical abstract: Computational studies on the substrate specificity of an acyltransferase domain from salinomycin polyketide synthase

Supplementary files

Article information

Article type
Paper
Submitted
14 Feb 2021
Accepted
25 Aug 2021
First published
25 Aug 2021

Catal. Sci. Technol., 2021,11, 6782-6792

Computational studies on the substrate specificity of an acyltransferase domain from salinomycin polyketide synthase

H. Ji, T. Shi, L. Liu, F. Zhang, W. Tao, Q. Min, Z. Deng, L. Bai, Y. Zhao and J. Zheng, Catal. Sci. Technol., 2021, 11, 6782 DOI: 10.1039/D1CY00284H

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