73 lines
2.9 KiB
Markdown
73 lines
2.9 KiB
Markdown
# PROPKA 3.2
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PROPKA predicts the pKa values of ionizable groups in proteins
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(version 3.0) and protein-ligand complexes (version 3.2 and later)
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based on the 3D structure.
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For proteins without ligands both version should produce the same result.
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The method is described in the following papers, which you should cite
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in publications:
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* 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. doi:[10.1021/ct200133y](https://doi.org/10.1021/ct200133y)
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* 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. doi:[10.1021/ct100578z](https://doi.org/10.1021/ct100578z)
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## Installation
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Clone repository or unpack the tar ball and install with
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[setuptools](http://pythonhosted.org/setuptools/index.html) (note: if
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you don't have setuptools installed you will need an internet
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connection so that the installation procedure can download the
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required files):
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cd <source directory>
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python setup.py install --user
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This will install the `propka32` script in your executable directory,
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as configured for setuptools, for instance `~/.local/bin`. You can
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change the bin directory with the `--install-scripts` option. For
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example, in order to install in the `bin` directory in the home
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directory:
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python setup.py install --user --install-scripts ~/bin
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For the purposes of testing or development, you may prefer to install PROPKA as
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an editable module via PIP by running
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```
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pip install -e .
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```
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from within a virtual environment (e.g., via [virtualenv](https://pypi.org/project/virtualenv/)).
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## Requirements
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* Python 3.5 or higher
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## Getting started
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1. Clone the code from GitHub
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2. `python setup.py install --user`
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2. Run `propka32` with a .pdb file (see Examples)
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## Examples
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Calculate using pdb file
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propka32 1hpx.pdb
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## Testing (for developers)
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Please see [`tests/README.md`](tests/README.md) for testing instructions.
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Please run these tests after making changes to the code and _before_ pushing commits.
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## References / Citations
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Please cite these references in publications:
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* 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.
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* 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.
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