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

TL;DR

Schr"odinger-ANI is a neural network potential energy model that significantly expands chemical element coverage for druglike molecules, achieving high accuracy and speed to aid drug discovery efforts.

Contribution

The paper introduces an extended neural network potential supporting more elements, improving conformer energy predictions for druglike molecules.

Findings

RMSE of 0.70 kcal/mol for conformer energies

Expanded element support from 41% to 94% of druglike molecules

Potential to accelerate protein-ligand binding calculations

Abstract

We have developed a neural network potential energy function for use in drug discovery, with chemical element support extended from 41% to 94% of druglike molecules based on ChEMBL. We expand on the work of Smith et al., with their highly 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 relative conformer energies, for which we show that our new potential energy function has an RMSE of 0.70 kcal/mol for prospective druglike molecule conformers, substantially better than the previous state of the art. The speed and accuracy of this model could greatly accelerate the parameterization of protein-ligand binding free energy calculations for novel druglike molecules.