Biocatalysis is an effective tool to access chiral molecules that are otherwise hard to synthesize or purify. Time-efficient processes are needed to develop enzymes that adequately perform the desired chemistry. We evaluated machine-directed evolution as an enzyme engineering strategy using a moderately stereoselective imine reductase as the model system. We compared machine-directed evolution approaches to deep mutational scanning (DMS) and error-prone PCR. Within one cycle, it was found that machine-directed evolution yielded a library of high-activity mutants with a dramatically shifted activity distribution compared to that of traditional directed evolution. Structure-guided analysis revealed that linear additivity might provide a simple explanation for the effectiveness of machine-directed evolution. The most active and selective enzyme mutant, which was identified through DMS and error-prone PCR, was used for the gram-scale synthesis of the H4 receptor antagonist ZPL389 with full conversion, > 99% ee (R), and a 72% yield.

中文翻译：

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用于活性和立体选择性的亚胺还原酶的机器定向进化

生物催化是获取难以合成或纯化的手性分子的有效工具。需要时间效率高的过程来开发能够充分执行所需化学反应的酶。我们使用适度立体选择性亚胺还原酶作为模型系统评估了机器定向进化作为酶工程策略。我们将机器定向进化方法与深度突变扫描 (DMS) 和易错 PCR 进行了比较。在一个循环内，发现机器定向进化产生了一个高活性突变体库，与传统定向进化相比，其活性分布发生了显着变化。结构引导分析表明，线性可加性可能为机器定向进化的有效性提供一个简单的解释。R )，产率为 72%。