OpenMM 8.5
Stanford / OpenMM Community
Python-first MD framework with native ML potential API (openmm-ml). Wraps MACE, NequIP, AceFF, and other ML force fields directly.
Best For
ML force field integration; prototyping enhanced sampling protocols
License
Open Source (MIT)
Strengths
- +Python API
- +ML potential integration
- +MIT license
- +Extensible
Limitations
- −Single-node only
- −Slower than GROMACS for pure classical simulations
R&D Pipeline Coverage
Related Tools
GROMACS 2026
GROMACS Consortium (KTH, Max Planck, et al.)
High-performance all-atom and coarse-grained MD engine. GROMACS 2026 added native NNP/MM support for hybrid ML-classical simulations.
MACE-OFF24
Cambridge (Csányi Lab)
Equivariant ML force field for organic molecules covering H, C, N, O, F, P, S, Cl, Br, I (~90% of drug-like space). Near-DFT accuracy for torsion profiles.
More in MD & Simulation
GROMACS 2026
GROMACS Consortium (KTH, Max Planck, et al.)
High-performance all-atom and coarse-grained MD engine. GROMACS 2026 added native NNP/MM support for hybrid ML-classical simulations.
AMBER 24
AMBER Consortium (UCSF et al.)
MD suite with best-in-class GPU acceleration (pmemd.cuda) and strong force field ecosystem. Now includes NNP integration via DeePMD-GNN.
Desmond / FEP+
D.E. Shaw Research / Schrödinger
GPU-accelerated MD engine integrated with Schrödinger's platform. FEP+ is the industry gold standard for relative binding free energy predictions in lead optimization.
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