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FastMDXplora

Fully Automated SysTem for Molecular Dynamics eXploration

DOI PyPI version Python versions License: MIT Tests codecov


FastMDXplora explores a protein's behavior end to end from a single command. Given a structure (or just a PDB ID) it performs molecular dynamics exploration all the way through setup, simulation, analysis, and reporting, then hands back publication-ready results.

  setup  →  simulation  →  analysis  →  report

Highlights

  • Explore a protein's full dynamics with a single command, covering setup, simulation, analysis, and reporting
  • Probe protein-ligand binding automatically with analyses for pose stability, contacts, and protein-ligand hydrogen bonds
  • Reach beyond plain MD with built-in PLUMED enhanced sampling (metadynamics, umbrella sampling, steered MD)
  • Design, start, watch, and review an exploration from a browser, with a 3D viewer and live telemetry
  • Scale from a quick single-protein exploration to large parallel campaigns, driven the same way from the CLI or the Python API

Phases of FastMDXplora

Phase What it does
setup Cleans up your structure and builds a simulation-ready system: fixes missing atoms, adds hydrogens, solvates, and adds ions.
simulation Runs the molecular dynamics (energy minimization, equilibration, and production), with optional enhanced sampling.
analysis Computes the standard structural and dynamic metrics (and protein-ligand metrics when a ligand is present), with figures ready to use.
report Packages everything into a slide deck, a written report, and a self-contained bundle you can share.

Install

Analysis and reporting are pure pip. Setup and simulation additionally need OpenMM and PDBFixer, which come from conda-forge.

# analysis and reporting only
pip install fastmdxplora

# all four phases
conda create -n fastmdxplora "python>=3.9,<3.14"
conda activate fastmdxplora
conda install -c conda-forge openmm pdbfixer openmmforcefields
pip install fastmdxplora

To work on FastMDXplora itself, clone the repository and use the bundled environment.yml. Full instructions, including Windows and WSL2, optional extras, and troubleshooting, are in the installation guide.

Quick start

fastmdx explore --system 1L2Y      # a full exploration, from a PDB ID
fastmdx gui                        # design, start, and watch one in a browser
fastmdx info                       # what is installed and which backends are present

From Python:

import fastmdxplora as fastmdx

runs = fastmdx.FastMDXplora(system="1L2Y", output_dir="trpcage").explore()
print(runs[0].output_dir)

For anything beyond a quick run, capture the whole exploration in a YAML file. fastmdx init-config writes a commented template, and the same file drives both the CLI and the Python API:

fastmdx explore --config study.yml

Parameter sweeps, multi-system campaigns, cross-run comparison, parallel execution, and the full flag list are covered in the usage examples and the CLI reference.

Outputs by phase

Each phase writes to its own subdirectory under the output root, with a parameters manifest so every artifact is traceable to the options that produced it.

Phase Key outputs
setup prepared.pdb, solvated.pdb, setup_parameters.json
simulation production.dcd, topology.pdb, simulation_parameters.json
analysis <analysis>/*.dat, <analysis>/*.png, analysis_manifest.json
report report.md, dashboard.html, slides.pptx, project_bundle.zip

Documentation

Full documentation is at fastmdxplora.readthedocs.io:

Citation

If you use FastMDXplora in your work, please cite:

Aina, A.; Kwan, D. FastMDAnalysis: Software for Automated Analysis of Molecular Dynamics Trajectories. J. Comput. Chem. 2026, 47, e70350. DOI: 10.1002/jcc.70350

@article{aina2026fastmd,
  author  = {Aina, Adekunle and Kwan, Derrick},
  title   = {FastMDAnalysis: Software for Automated Analysis of Molecular Dynamics Trajectories},
  journal = {Journal of Computational Chemistry},
  volume  = {47},
  number  = {8},
  pages   = {e70350},
  year    = {2026},
  doi     = {10.1002/jcc.70350},
}

Contributing

Contributions are welcome. See CONTRIBUTING.md. FastMDXplora follows the Contributor Covenant.

License

MIT. See LICENSE.

Acknowledgements

FastMDXplora is developed in the AAI Research Lab at California State University Dominguez Hills. It builds on a deep ecosystem of open-source scientific Python: MDTraj, OpenMM, PDBFixer, NumPy, SciPy, scikit-learn, Matplotlib, python-pptx, and many others.

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