Machine learning for molecular surfaces and implicit solvent

We bring machine learning to implicit-solvent modeling: graph and convolutional neural networks that learn the solvent-excluded molecular surface, and data-driven models of Poisson–Boltzmann reaction-field energies. Implemented on GPUs (AmberTorchPB), these methods make continuum electrostatics fast and smooth enough for routine biomolecular simulation.