propka
Heuristic pKa calculations with ligands
Decision gist · record as of 2026-08-14
Yes, if you need offline pKa prediction from PDB structures and can verify the method's accuracy for your use case. The package is mature, has no dependencies, and installs easily. However, dormant maintenance and lack of recent commits mean you should test predictions against your own data or literature benchmarks before using results in new publications. The LGPL copyleft license requires derivative works to remain open-source.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a valid PDB structure file as input; PROPKA is a command-line and library tool for offline calculation, not a web service.
- Low install friction with no runtime dependencies.
- Dormant maintenance status (955 days since last release) but marked mature and supporting current Python versions through 3.12.
License · maintenance · safety
LGPL v2.1 (copyleft) — Licensed under LGPL v2.1 (copyleft). Derivative works and modifications must be distributed under the same license; static linking or bundling requires careful compliance review.
last release 2024-01-02 (955 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 436,779 downloads/mo, #6,673 on PyPI
Alternatives
Verify before relying
pip install propka
from propka.molecular_container import MolecularContainer
mol = MolecularContainer('protein.pdb')
mol.calculate_pka()- Whether the dormant status (no commits tracked) reflects genuine maintenance or only PyPI release infrequency.
- Performance characteristics and accuracy benchmarks for modern protein structures or large complexes.
- Whether ligand handling in version 3.1+ is production-ready or still experimental.
What it is and what it does
PROPKA is a mature bioinformatics library that calculates pKa values—the pH at which ionizable amino acid residues protonate or deprotonate—directly from protein 3D structures. It uses empirical heuristics calibrated on experimental data and handles both standalone proteins and protein-ligand complexes. The method is described in peer-reviewed literature and has been in use since at least 2011.
The package provides both a command-line interface and a Python API for integration into computational workflows. It requires only a PDB structure file as input and has no external runtime dependencies, making it straightforward to install and use in analysis pipelines. However, the project shows dormant maintenance (last release January 2024, no recent commits tracked), so users should verify that its predictions meet their accuracy requirements before relying on it for new research.
Use it for
- Calculate protonation states of proteins at physiological pH for molecular dynamics simulations or docking studies.
- Predict ionizable residue pKa shifts caused by protein-ligand binding to understand binding thermodynamics.
- Batch-process PDB structures to generate pKa tables for structural biology databases or annotation pipelines.
- Rationalize experimental pH-dependent protein behavior by mapping predicted pKa values to observed titration curves.
- Prepare protein structures for pH-dependent computational studies by assigning appropriate protonation states.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need offline pKa prediction from PDB structures and can verify the method's accuracy for your use case.
The package is mature, has no dependencies, and installs easily. However, dormant maintenance and lack of recent commits mean you should test predictions against your own data or literature benchmarks before using results in new publications. The LGPL copyleft license requires derivative works to remain open-source.
Install
propka on PyPI
Before you install
Low install friction with no runtime dependencies. Dormant maintenance status (955 days since last release) but marked mature and supporting current Python versions through 3.12.
Requires a valid PDB structure file as input; PROPKA is a command-line and library tool for offline calculation, not a web service.
License in practice
Licensed under LGPL v2.1 (copyleft). Derivative works and modifications must be distributed under the same license; static linking or bundling requires careful compliance review.
Quickstart
pip install propka
from propka.molecular_container import MolecularContainer
mol = MolecularContainer('protein.pdb')
mol.calculate_pka()Verify before relying
- Whether the dormant status (no commits tracked) reflects genuine maintenance or only PyPI release infrequency.
- Performance characteristics and accuracy benchmarks for modern protein structures or large complexes.
- Whether ligand handling in version 3.1+ is production-ready or still experimental.
Package facts
| License | LGPL v2.1 copyleft |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Dormant 955 days since the last release |
| First released | |
| Downloads | 436,779 / month, #6,673 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 6 - MatureEnvironment :: ConsoleIntended Audience :: Science/ResearchLicense :: OSI Approved :: GNU Lesser General Public License v2 (LGPLv2)Operating System :: MacOS :: MacOS XOperating System :: Microsoft :: WindowsOperating System :: POSIXProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/Engineering :: Bio-InformaticsTopic :: Scientific/Engineering :: Chemistry |
Evidence: propka-3.5.1-py3-none-any.whl
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See also pdb2pqr · prolif · tmtools · mordredcommunity · pydssp · py3Dmol · fair-esm · chemprop · mhctools · pdbeccdutils