Rega: A Platform for the Prediction of the Regioselectivity of C–H Functionalisation Reactions

Sulfinate-mediated radical C–H functionalisation reactions are widely used for the modification and diversification of scaffolds in drug discovery. However, prediction of the regiochemistry can be challenging. There may be multiple sites of reaction, each with its own unique steric and electronic environment. Here we present Rega, an automated transition state searching program for the prediction of regioselectivity from inexpensive HF/6-31G* activation energies. In a set of 23 compounds the regioselectivity is correctly identified in 22 cases (reactivity correctly identified for 66/68 potential sites of reaction). The modular Rega workflow allows reaction exploration of multiple substrates simultaneously, enabling the generation of a synthetic dataset of 490 compounds consisting of 2780 sites with labelled reactivity for this reaction for use in machine learning models. Rega is readily extensible to other reaction systems and can be applied to many other reaction classes in which a radical intermediate is formed as the regiochemistry determining step.