Heuristic pKa calculations with ligands (Acellera fork)
Project description
PROPKA3
PROPKA predicts the pKa values of ionizable groups in proteins (version 3.0) and protein-ligand complexes (version 3.1 and later) based on the 3D structure.
For proteins without ligands both versions should produce the same result.
The method is described in the following papers, which you should cite in publications:
-
Sondergaard, Chresten R., Mats HM Olsson, Michal Rostkowski, and Jan H. Jensen. "Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of pKa Values." Journal of Chemical Theory and Computation 7, no. 7 (2011): 2284-2295.
-
Olsson, Mats HM, Chresten R. Sondergaard, Michal Rostkowski, and Jan H. Jensen. "PROPKA3: consistent treatment of internal and surface residues in empirical pKa predictions." Journal of Chemical Theory and Computation 7, no. 2 (2011): 525-537.
See http://propka.org/ for the PROPKA web server.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file acellera_propka-3.5.1.post1.tar.gz.
File metadata
- Download URL: acellera_propka-3.5.1.post1.tar.gz
- Upload date:
- Size: 85.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d929e998f44d1e44b4646e45a5864d831624080c2adaceb6c95b2ea218ab1f95
|
|
| MD5 |
af8ec96880322a8d82865c878bb5fdba
|
|
| BLAKE2b-256 |
7b335705482d58ba8708c689c4afa4076d1ca2054e545b021f7698062f9f6b2d
|
File details
Details for the file acellera_propka-3.5.1.post1-py3-none-any.whl.
File metadata
- Download URL: acellera_propka-3.5.1.post1-py3-none-any.whl
- Upload date:
- Size: 93.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.13.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
df2744ca1640bad37ec5c78a25e6efe44bb623b283cfff624344f235c44367c4
|
|
| MD5 |
bc84415c663e9a4777675cd393c1fa65
|
|
| BLAKE2b-256 |
6545f8e1e734960be167a045bfbcacd1652a95291c7e3361044800bae23cb496
|