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FastMDXplora

Molecular dynamics from a PDB code to a finished study — in one command.

DOI PyPI conda-forge Python License: MIT

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Documentation · Quick start · GUI · Cite


fastmdx explore --system 181L
setup  →  simulation  →  analysis  →  report

Four characters of PDB ID as input. FastMDXplora fetches T4 lysozyme, parameterises the benzene bound in its cavity, runs the dynamics, analyses the trajectory, works out which residues hold the ligand in place, and writes the whole study up as a PDF.

Run all four phases, or any one on its own — fastmdx setup, simulate, analyze, report. Each records what it did, so a run can be picked up, repeated or explained afterwards.

Or do the whole thing in the GUI:

fastmdx gui

The GUI is not a viewer bolted onto a command-line tool. Its form is generated from the same schema the CLI validates against, so every one of the hundred settings is reachable, every system FastMDXplora can study can be built there, and nothing can be configured in one interface and not the other. What it hands back is a config file — checked by the same validator before you ever see it — and fastmdx explore --config runs those same bytes on a laptop or a cluster. Build the study where it is convenient to think; run it where the compute is.

Install

conda install -c conda-forge fastmdxplora
fastmdx info

fastmdx info lists every backend and how to get anything missing.

What you can study

A protein on its own Fold, flexibility, secondary structure, native contacts, conformational clustering — from a PDB code.
A protein with a ligand The ligand is found, its chemistry resolved, its protonation settled in the binding site. Eight interaction types against published criteria tell you what holds it, not just what it touches.
A membrane protein Embedded in one of seven bilayers, with the orientation checked rather than assumed and pressure coupling that suits a lipid system.
Free energy along a coordinate Umbrella sampling, metadynamics and steered MD from a named collective variable — eight of them — without writing PLUMED input. Each says what its output is and is not: a surface if the bias converged, a pathway and the work along it, a potential of mean force if the windows overlap.
A trajectory from another engine Skip the simulation and analyse what you already have — GROMACS .xtc and .trr, Amber .nc, NAMD and CHARMM .dcd, LAMMPS .lammpstrj, or .pdb, .cif and .h5 that carry their own topology.
Many systems at once Mutants against wild type, a sweep across a setting, runs pinned one per GPU, and a comparison report across all of them.

It refuses rather than guesses. An ambiguous ligand charge, or a protein pointed the wrong way into a membrane, stops the run and gets named. A metadynamics run that crossed its barrier once when you asked for four gets no free energy surface. Averages from a biased trajectory are corrected back to equilibrium where the bias allows it, and labelled where it does not.

Every step says why it is happening, and cites the paper worth reading. What comes out is something you can defend — or is marked clearly as something you cannot.

The config is the study

A FastMDXplora config is the whole description of a molecular dynamics study: the system, how it is prepared, how it is simulated, what is measured, and how it is written up. Capture that, and the four phases — setup, simulation, analysis, report — run themselves.

systems:
  - system: 181L
simulation:
  duration_ns: 100

That is a complete study. Everything unnamed takes a documented default, and every run writes resolved_config.yml with defaults, file and command line merged, so the exact study can be run again by anyone holding that one file.

Three ways to build a config, and each of them also runs all four phases:

The GUI fastmdx gui. A form generated from the schema, so every system and every setting is reachable. Worth using even for a command-line or Python workflow: build the study where the options are visible and explained, then take the file away.
The CLI fastmdx explore --config study.yml, or fastmdx init-config for a commented template, or a flag for any setting.
The Python API FastMDXplora(config="study.yml").explore(), or the same blocks passed as options.

A fourth way is to write the YAML by hand, which is short and readable enough that people do.

None of these is the primary interface and none is a subset of another. The form, the flags and the API are generated from one declaration of what the software can do, so a study you can express in one you can express in all of them. A study designed on a laptop in the GUI runs unchanged on a cluster from the command line, because what travels between them is the config.

Documentation

Start hereInstall · Your first run · The GUI · The four phases

Going furtherRestraints, membranes, enhanced sampling · Production and GPUs · Protein-ligand interactions

ReferenceCLI · Configuration · Examples · Python API

Citation

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 welcome — see CONTRIBUTING.md. FastMDXplora follows the Contributor Covenant.

License

MIT. See LICENSE.


Built in the AAI Research Lab at California State University Dominguez Hills, on MDTraj, OpenMM, PDBFixer, OpenFF, RDKit, NumPy, SciPy, scikit-learn and Matplotlib.

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