most citedEnhancing Protein-Ligand Binding Affinity Predictions using Neural Network Potentials

1 citations · 1 across the 1 of their papers we have counts for

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2 papers

physics.chem-ph2024★ 1 cited

Enhancing Protein-Ligand Binding Affinity Predictions using Neural Network Potentials

Francesc Sabanes Zariquiey, Raimondas Galvelis, Emilio Gallicchio +3

This letter gives results on improving protein-ligand binding affinity predictions based on molecular dynamics simulations using machine learning potentials with a hybrid neural ne…

physics.chem-ph2023

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

Peter Eastman, Raimondas Galvelis, Raúl P. Peláez +22

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use…