The Open Forcefield Toolkit provides implementations of the SMIRNOFF format, parameterization engine, and other tools. Documentation available at http://open-forcefield-toolkit.readthedocs.io

A project (and object) for storing, manipulating, and converting molecular mechanics data.

A physical property evaluation toolkit from the Open Forcefield Consortium.

Fragment molecules for quantum mechanics torsion scans

A Package for Parametrization of Molecular Mechanics Force Fields

Generate canonical molecule identifiers for quantum chemistry database

Bayesian tools for fitting molecular mechanics torsion parameters to quantum chemical data.

An implementation of the 3SPN2 and 3SPN2.C coarse-grained DNA forcefields in OpenMM

BlockBreakEvent and BlockPlaceEvent is better when canceled!

A library for analyzing potential energy surfaces (PESs) and using the resulting PES descriptors for constructing forcefield parameters.

Python-based library for easy force-field fitting

Modeling the synthesis of SILica materials VIA multiscale computer simulation. (implementation in MARTINI forcefield)

Nucleic acid labeling and all-atom MD simulations with explicit fluorophores

Analysis scripts for the CHARMM GUI Drude Prepper Paper

Classical force-field for peptides containing 4-fluorinated proline residues (or any canonical peptide). Includes a proline ring pucker correction

MFFS is a mod for Minecraft that adds a modular forcefield system to the game. It is based on the 1.12.2 MFFS mod, but has been completely rewritten for the newer versions of Minecraft.

Plot individual potential functions that comprise force fields. Ideal for presentations. Includes energy terms for bonds (harmonic), angles (harmonic), proper torsion (periodic cosine), improper torsion (harmonic), van der Waals (Lennard-Jones), electrostatics (Coulomb), and the Morse potential.

First program for a class in molecular modelling (done in june 2016). Its an implementation of simple Molecular Dynamics for atoms with a possibility to choose from different algorithms (Verlet, VelocityVerlet, Leepfrog) and potentials (Lenard-Jones, SoftWall, min-barrier-bin).

Linear Machine learning Interatomic Potential for atomistic simulations