Computational Evolution Of New Catalysts For The Morita–Baylis–Hillman Reaction

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. An efficient catalyst of the Morita–Baylis–Hillman reaction was discovered using a graph‐based genetic algorithm. The catalytic activity was experimentally verified by a kinetic study and the newly discovered catalyst outcompetes a widely used catalyst for this reaction.