Machine-learned molecular mechanics force fields from large-scale quantum chemical data

K Takaba, AJ Friedman, CE Cavender, PK Behara… - Chemical …, 2024 - pubs.rsc.org
The development of reliable and extensible molecular mechanics (MM) force fields—fast,
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

G Heinzelmann, DJ Huggins… - Journal of Chemical …, 2024 - ACS Publications
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 …

The open force field initiative: Open software and open science for molecular modeling

L Wang, PK Behara, MW Thompson… - The Journal of …, 2024 - ACS Publications
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 …

Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond

K Takaba, I Pulido, PK Behara, CE Cavender… - arxiv preprint arxiv …, 2023 - arxiv.org
The development of reliable and extensible molecular mechanics (MM) force fields--fast,
empirical models characterizing the potential energy surface of molecular systems--is …

Optimal Dielectric Boundary for Binding Free Energy Estimates in the Implicit Solvent

N Forouzesh, F Ghafouri, IS Tolokh… - Journal of Chemical …, 2024 - ACS Publications
Accuracy of binding free energy calculations utilizing implicit solvent models is critically
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 …