2026: De Novo Design of Miniature and Efficient Metallo-Ketoreductases
- YL Xu, YH Li
- , HW Zheng
- , E Delfosse
- , YX Gao
- , D Baker
- &
- P. Ji*
The rational design of enzymes capable of catalyzing abiotic transformations represents a frontier in synthetic biocatalysis. While computational strategies have successfully produced enzymes for acid-base chemistry, examples of de novo designed oxidoreductases are still rare. Here, we report a deep learning-guided workflow for designing metallo-ketoreductases from theoretical active sites, enabling asymmetric reduction of ketones via an abiotic hydride-transfer mechanism. The resulting miniature enzyme contains only 130 residues, while exhibiting high catalytic performance under whole-cell conditions, achieving kcat/kuncat up to 1.4 × 106, turnover numbers (TON) up to 19,000, enantiomeric excess (e.e.) values of up to 98%, broad substrate scope, and regioselective reduction of diketones. Notably, the designed scaffold shows exceptional thermal stability toward 90 °C treatment, outperforming natural promiscuous reductases, and exhibits tolerance to various organic solvents. This work demonstrates the power of de novo enzyme design to access non-natural catalytic functions, offering a scalable and sustainable route to engineer tailor-made biocatalysts for asymmetric synthesis.
合理设计能够催化非生物转化的酶，代表了合成生物催化领域的前沿方向。尽管计算策略已成功用于构建适用于酸碱化学反应的酶，但从头设计氧化还原酶的案例目前仍属罕见。在此，我们报道了一种由深度学习引导的工作流程，用于基于理论活性位点设计金属酮还原酶，从而通过非生物氢负离子转移机制实现酮类化合物的不对称还原。所获得的微型酶仅包含130个氨基酸残基，但在全细胞条件下展现出卓越的催化性能：其催化效率比（kcat/kuncat）高达1.4 × 10⁶，转化数（TON）最高达19,000，对映体过量值（e.e.）最高达98%；此外，该酶还具有广泛的底物适用范围，并能实现对二酮类底物的区域选择性还原。值得注意的是，所设计的酶骨架展现出极佳的热稳定性，在90 °C的高温处理下依然性能稳健，其热稳定性甚至优于天然的广谱还原酶；同时，该酶对多种有机溶剂也表现出良好的耐受性。本工作充分展示了“从头设计酶”策略在赋予酶非天然催化功能方面的强大潜力，为构建用于不对称合成的定制化生物催化剂提供了一条可扩展且可持续的途径。