Computation-driven redesign of an NRPS-like carboxylic acid reductase improves activity and selectivity

利用计算机驱动的重新设计方法,对类NRPS羧酸还原酶进行改造,提高了其活性和选择性。

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Abstract

Engineering nonribosomal peptide synthetases (NRPSs) has been a "holy grail" in synthetic biology due to their modular nature and limited understanding of catalytic mechanisms. Here, we reported a computational redesign of the "gate-keeper" adenylation domain of the model NRPS-like enzyme carboxylic acid reductases (CARs) by using approximate mechanism-based geometric criteria and the Rosetta energy score. Notably, MabCAR3 mutants ACA-1 and ACA-4 displayed a remarkable improvement in catalytic efficiency (k(cat)/K(M)) for 6-aminocaproic acid, up to 101-fold. Furthermore, G418K exhibited an 86-fold enhancement in substrate specificity for adipic acid compared to 6-aminocaproic acid. Our work provides not only promising biocatalysts for nylon monomer biosynthesis but also a strategy for efficient NRPSs engineering.

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