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We have developed a neural network potential energy function for use in drugdiscovery, with chemical element support extended from 41% to 94% of druglikemolecules based on ChEMBL. We expand on the work of Smith et al., with theirhighly accurate network for the elements H, C, N, O, creating a network for H,C, N, O, S, F, Cl, P. We focus particularly on the calculation of relativeconformer energies, for which we show that our new potential energy functionhas an RMSE of 0.70 kcal/mol for prospective druglike molecule conformers,substantially better than the previous state of the art. The speed and accuracyof this model could greatly accelerate the parameterization of protein-ligandbinding free energy calculations for novel druglike molecules.

Schr\"odinger-ANI: An Eight-Element Neural Network Interaction Potential with Greatly Expanded Coverage of Druglike Chemical Space