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fingerprints

fingerprints

Run ProLIF fingerprints on trajectories, ligand-pose iterables, or molecule pairs and export results safely.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: fingerprints description: "Run ProLIF fingerprints on trajectories, ligand-pose iterables, or molecule pairs and export results safely." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

ProLIF Fingerprints

Use this sub-skill when an agent must execute a ProLIF interaction fingerprint, inspect the sparse IFP results, convert results to tabular or RDKit vector forms, compare frames or docking poses, or persist/reload a completed fingerprint.

Route First

  • Choose or parameterize interaction classes in ../interactions/ before constructing prolif.Fingerprint(...) with non-default interactions, parameters, count=True, implicit_hydrogens=True, bridged interactions, or custom ignore predicates.
  • Prepare MDAnalysis.AtomGroup, iterable prolif.Molecule, supplier, residue, and use_segid inputs in ../molecules-and-io/ before running fingerprints.
  • Create ligand-network, barcode, or 3D plots in ../visualization/ after a fingerprint has been run; this sub-skill only cross-links plotting preconditions.

Choose The Execution API

  • Use Fingerprint.run(traj, lig, prot, ...) for MDAnalysis trajectories, sliced trajectories, indexed frames, or a single timestep with ligand/protein AtomGroup objects.
  • Use Fingerprint.run_from_iterable(lig_iterable, prot_mol, ...) for docking poses or any iterable yielding prolif.Molecule ligand conformers against one prepared protein Molecule.
  • Use Fingerprint.generate(lig_mol, prot_mol, ...) for one ligand/protein Molecule pair when you want an immediate sparse IFP or bitvector dictionary without storing a trajectory-scale fp.ifp.
  • Use prolif.utils.select_over_trajectory(...) before run() when a distance-based MDAnalysis selection must include atoms that appear near a reference over multiple frames.

Core References

  • references/api-reference.md lists the installed runtime signatures and result object contracts.
  • references/workflows.md gives executable trajectory, docking-pose, single-pair, and parallel recovery recipes.
  • references/results-and-export.md covers to_dataframe, to_bitvectors, to_countvectors, to_pickle, from_pickle, IFP indexing, Tanimoto comparison, and count fingerprints.
  • references/troubleshooting.md covers run-before-export errors, empty results, residue-selection mistakes, multiprocessing differences, converter_kwargs, pickle portability, progress/noise, and use_segid surprises.

Safe Smoke Check

Run the bundled helper to confirm the installed package can execute a minimal package-data fingerprint:

python scripts/run_fingerprint_smoke.py --no-progress

Expected JSON includes dataframe_shape, frame_keys, and interactions. A verified package-data run with three interactions produced shape [1, 10] and frame key [0].

Gespeicherte Skills