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Machine-learned molecular mechanics force fields from large-scale quantum chemical data
The development of reliable and extensible molecular mechanics (MM) force fields—fast,
empirical models characterizing the potential energy surface of molecular systems—is …
empirical models characterizing the potential energy surface of molecular systems—is …
Bat2: an open-source tool for flexible, automated, and low cost absolute binding free energy calculations
Absolute binding free energy (ABFE) calculations with all-atom molecular dynamics (MD)
have the potential to greatly reduce costs in the first stages of drug discovery. Here, we …
have the potential to greatly reduce costs in the first stages of drug discovery. Here, we …
The open force field initiative: Open software and open science for molecular modeling
Force fields are a key component of physics-based molecular modeling, describing the
energies and forces in a molecular system as a function of the positions of the atoms and …
energies and forces in a molecular system as a function of the positions of the atoms and …
Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond
The development of reliable and extensible molecular mechanics (MM) force fields--fast,
empirical models characterizing the potential energy surface of molecular systems--is …
empirical models characterizing the potential energy surface of molecular systems--is …
Optimal Dielectric Boundary for Binding Free Energy Estimates in the Implicit Solvent
Accuracy of binding free energy calculations utilizing implicit solvent models is critically
affected by parameters of the underlying dielectric boundary, specifically, the atomic and …
affected by parameters of the underlying dielectric boundary, specifically, the atomic and …
Reversible molecular simulation for training classical and machine learning force fields
JG Greener - arxiv preprint arxiv:2412.04374, 2024 - arxiv.org
The next generation of force fields for molecular dynamics will be developed using a wealth
of data. Training systematically with experimental data remains a challenge, however …
of data. Training systematically with experimental data remains a challenge, however …