Large-Scale Computation and Prediction of Sulfinate-Mediated C-H Functionalisation Regioselectivity - Walton, Peter J. (2025)
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 in these reactions can be challenging. For a given substrate, 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. We show that in a set of 23 compounds, the regioselectivity is correctly identified in 22 cases (reactivity correctly identified for 65/68 potential sites of reaction). The easy-to-use and 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 designed to be 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. From the generation of this dataset, machine learning was applied to predict regioselectivity in both regression and classification tasks.