Computational Evolution Of New Catalysts For The Morita-Baylis-Hillman Reaction.

Abstract

We present a de novo discovery of an efficient catalyst of the Morita-Baylis-Hillman (MBH) reaction by searching chemical space for molecules that lower the estimated barrier of the rate-determining step using a genetic algorithm (GA) starting from randomly selected tertiary amines. We identify 435 candidates, virtually all of which contain an azetidine N as the catalytically active site, which is discovered by the GA. Two molecules are selected for further study based on their predicted synthetic accessibility and have predicted rate-determining barriers that are lower than that of a known catalyst. Azetidines have not been used as catalysts for the MBH reaction. One suggested azetidine is successfully synthesized and showed an eightfold increase in activity over a commonly used catalyst. We believe this is the first experimentally verified de novo discovery of an efficient catalyst using a generative model.