Sep 2026· Journal of Chemical Information and Modeling· Vol 66, pp. 11556 - 11562· 0 citations· 18 references
TL;DR
FMM-AutoOpt is developed for the automated benchmarking of FMM parameters with GROMACS, a versatile and flexible tool facilitating rapid parameter screening to ensure optimal performance and high simulation accuracy.
Abstract
The fast multipole method (FMM) for computing Coulombic forces in molecular dynamics (MD) simulations offers benefits for a variety of systems, including nonperiodic configurations such as molecules in vacuum and large-scale systems where many other approaches encounter limitations. Because FMM parameters govern both simulation accuracy and computational performance, and because the optimal solution is highly system-dependent, we have developed FMM-AutoOpt for the automated benchmarking of FMM parameters with GROMACS. Relying solely on standard Python libraries and GROMACS FMM ( KohnkeB., J. Chem. Theory Comput. 2020, 16, 6938–6949 10.1021/acs.jctc.0c00744PMC766074633084336), the tool is versatile and flexible, facilitating rapid parameter screening to ensure optimal performance and high simulation accuracy.
A new software package, Fast-Forward, which aids parametrization of models for the widely used Martini coarse-grained force field, and offers a system-agnostic suite of tools to parametrize molecules of any size, existing in any environment.
Christopher Brasnett, Maximilian Fidlin, Thilo Duve et al.· Journal of Chemical Informat...· 1 citation· ⚡1
Neural network potentials (NNPs), trained on quantum mechanical (QM) data, can deliver near QM-level accuracy while being much faster than QM calculations. In this work, we introduce a new software tool, Torsionator, which currently supports MACE, OBIWAN, and UMA NNPs for energy minimization of small molecules. Torsi...
Giorgia Brosio, Alice Triveri, Pietro Vidossich et al.· Journal of Chemical Theory a...· 0 citations
This work presents a robust and fully periodic QM/MM interface between the open-source molecular dynamics engine GROMACS and the electronic structure theory code CP2K that enables efficient and reproducible QM/MM molecular dynamics and enhanced sampling simulations with a consistent treatment of long-range electrostati...
D. Morozov, C. Blau, Ole Schütt et al.· Journal of Chemical Informat...· 0 citations
Chemical reactivity modeling in large systems over extended time scales is computationally and theoretically challenging; ab initio methods are too expensive, while classical force fields cannot handle bond breaking/formation. Existing solutions like reactive force fields require extensive expertise to develop, and m...
Blake I. Armstrong, Peter R. Spackman, Luc M. LeBlanc et al.· Journal of Chemical Theory a...· 0 citations
Classical force fields (FFs) remain the workhorse for large-scale simulations even as machine-learned interatomic potentials (MLIPs) approach ab initio accuracy. They decompose total configuration energies into simple effective interactions whose parameters are traditionally assigned based on atom or bond types, enabli...
Berkay Gunes, Leif Seute, Jigyasa Nigam et al.· 0 citations
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