To better understand the basis of the remarkable levels of asymmetric induction imparted by the TDO camphorsultam sidechain, we turned to computational modelling. Quantum mechanics (QM) calculations and molecular dynamics simulations driven by machine learning potentials (MLPs) were performed to model the cycloaddition step. MLPs "learn" the high-dimensional potential energy surfaces (PES) from QM calculations, effectively mapping atomic positions to energies and, often, forces with accuracy comparable to QM and efficiency comparable to simple empirical force fields .