3 citations · 4 across the 3 of their papers we have counts for
3 papers
QuantumBind-RBFE: Accurate Relative Binding Free Energy Calculations Using Neural Network Potentials
Francesc Sabanés Zariquiey, Stephen E. Farr, Stefan Doerr +1
Accurate prediction of protein-ligand binding affinities is crucial in drug discovery, particularly during hit-to-lead and lead optimization phases, however, limitations in ligand…
A Scalable Molecular Force Field Parameterization Method Based on Density Functional Theory and Quantum-Level Machine Learning
Raimondas Galvelis, Stefan Doerr, Joao M. Damas +2
Fast and accurate molecular force field (FF) parameterization is still an unsolved problem. Accurate FFs are not generally available for all molecules, like novel druglike molecule…
Machine Learning of coarse-grained Molecular Dynamics Force Fields
Jiang Wang, Simon Olsson, Christoph Wehmeyer +5
Atomistic or ab-initio molecular dynamics simulations are widely used to predict thermodynamics and kinetics and relate them to molecular structure. A common approach to go beyond…