计算驱动的 NRPS 样羧酸还原酶的重新设计提高了活性和选择性。

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

机构信息

State Key Laboratory of Bioreactor Engineering, School of Biotechnology, East China University of Science and Technology, 130 Meilong Road, Shanghai 200237, People's Republic of China.

Department of Biotechnology Institution, Delft University of Technology, Van der Maasweg 9, 2629HZ Delft, Netherlands.

出版信息

Sci Adv. 2024 Nov 29;10(48):eadp6775. doi: 10.1126/sciadv.adp6775.

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, CAR3 mutants ACA-1 and ACA-4 displayed a remarkable improvement in catalytic efficiency (/) 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.

由于非核糖体肽合成酶 (NRPSs) 的模块化性质和对催化机制的有限理解，对其进行工程改造一直是合成生物学的“圣杯”。在这里，我们报道了使用近似基于机制的几何标准和 Rosetta 能量评分对模型 NRPS 样酶羧酸还原酶 (CARs) 的“守门员”氨酰化结构域进行计算重设计。值得注意的是，CAR3 突变体 ACA-1 和 ACA-4 对 6-氨基己酸的催化效率 (/ ) 显著提高，最高可达 101 倍。此外，与 6-氨基己酸相比，G418K 对己二酸的底物特异性提高了 86 倍。我们的工作不仅为尼龙单体生物合成提供了有前途的生物催化剂，而且还为高效 NRPSs 工程提供了一种策略。