Random mutagenesis has the potential to optimize the efficiency and selectivity of protein catalysts without requiring detailed knowledge of protein structure; however, introducing synthetic metal cofactors complicates the expression and screening of enzyme libraries, and activity arising from free cofactor must be eliminated. Here we report an efficient platform to create and screen libraries of artificial metalloenzymes (ArMs) via random mutagenesis, which we use to evolve highly selective dirhodium cyclopropanases. Error-prone PCR and combinatorial codon mutagenesis enabled multiplexed analysis of random mutations, including at sites distal to the putative ArM active site that are difficult to identify using targeted mutagenesis approaches. Variants that exhibited significantly improved selectivity for each of the cyclopropane product enantiomers were identified, and higher activity than previously reported ArM cyclopropanases obtained via targeted mutagenesis was also observed. This improved selectivity carried over to other dirhodium-catalysed transformations, including N–H, S–H and Si–H insertion, demonstrating that ArMs evolved for one reaction can serve as starting points to evolve catalysts for others.

随机诱变有可能优化蛋白质催化剂的效率和选择性，而无需详细了解蛋白质结构。然而，引入合成金属辅因子会使酶文库的表达和筛选复杂化，并且必须消除由游离辅因子引起的活性。在这里，我们报告了一个有效的平台，可通过随机诱变创建和筛选人工金属酶（ArMs）库，我们将其用于进化高度选择性的dirhodium环丙烷酶。容易出错的PCR和组合密码子诱变技术可以对随机突变进行多重分析，包括在使用假定诱变方法难以鉴定的推定ArM活性位点远端的位点。鉴定出对每种环丙烷产物对映异构体表现出显着改善的选择性的变体，并且还观察到比通过靶向诱变获得的先前报道的ArM环丙烷酶更高的活性。这种改进的选择性延续到了其他由D催化的转化中，包括N–H，S–H和Si–H的插入，这表明一个反应中生成的ArM可以作为其他反应中生成催化剂的起点。