ProLIF (PROtein-Ligand Interaction Fingerprints) is a Python library for generating interaction fingerprints from molecular dynamics trajectories or docking poses. It supports both 2D and 3D fingerprints based on pharmacophore-like interaction types (e.g., hydrophobic, H-bond, pi-stacking). The current version is 2.1.0, requiring Python >=3.10. The project is under active development with releases every few months.
pip install prolifNo compatibility data collected yet for this library.
Verified import paths — ran on the pinned version, not inferred.
Basic usage: load a complex, compute interactions, and export to DataFrame.
Update imports: from prolif import run; also use prolif.Fingerprint instead of prolif.fingerprint.Fingerprint.
Use the new DataFrame columns; run `print(df.columns)` to inspect.
Replace `from prolif.plot import plot_2D` with `from prolif import plot_network` and adjust arguments.
Add hydrogens using RDKit: `mol = Chem.AddHs(mol)` for both protein and ligand.
Pre-process with RDKit to ensure proper valence and bond orders.