Computational design of generalist cyclopropanases with stereodivergent selectivity.

Stereodivergent catalysis, whereby the full complement of stereoisomeric products is obtained through a set of stereocomplementary catalysts, represents a powerful tool for synthetic organic and medicinal chemistry. Despite recent progress in engineering biocatalysts for new-to-nature cyclopropanation reactions, cyclopropanases featuring a combination of stereodivergent selectivity with broad substrate scope have been elusive. Here, we report a mechanism-based, multi-state computational design workflow useful for the design of 'generalist' cyclopropanation biocatalysts with tailored selectivity. Using this strategy, cyclopropanases with high and predictable trans-(1 R,2 R), cis-(1 R,2S), or cis-(1S,2 R)-stereoselectivity in the transformation of a broad range of olefin substrates are designed based on three different hemoprotein scaffolds, including one (indoleamine 2,3-dioxygenase-1) not previously reported to support non-native carbene transfer reactions. Combined with a previously reported trans-(1S,2S)-stereoselective cyclopropanase, this biocatalytic toolbox provides access to a full set of cyclopropane stereoisomers from over 20 structurally diverse olefin substrates with high diastereo- and enantioselectivity (up to 99% de. and 99% ee). Crystal structures of a designed catalyst show good agreement with the computational model and highlight the role of subtle conformational heterogeneity in determining stereoselectivity. We envision that the present computational design methodology can guide the development of biocatalysts with tailored stereoselectivity for other carbene transfer reactions and enzymatic transformations.