https://github.com/peptoneltd/pepkalc
Robust simulation software for the comprehensive evaluation of protein electrostatics in unfolded state.
https://github.com/peptoneltd/pepkalc
bioinformatics biophysics electrostatics polymer prediction protein protein-sequence protonation simulation
Last synced: 8 days ago
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Robust simulation software for the comprehensive evaluation of protein electrostatics in unfolded state.
- Host: GitHub
- URL: https://github.com/peptoneltd/pepkalc
- Owner: PeptoneLtd
- License: other
- Created: 2017-08-15T10:14:33.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2022-08-23T09:00:20.000Z (over 2 years ago)
- Last Synced: 2025-04-20T18:41:03.946Z (about 1 month ago)
- Topics: bioinformatics, biophysics, electrostatics, polymer, prediction, protein, protein-sequence, protonation, simulation
- Language: Python
- Homepage: https://peptone.io
- Size: 24.4 KB
- Stars: 5
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# pepkalc
Robust simulation software for the comprehensive evaluation of protein electrostatics in unfolded state.
## Protein electrostatics
Protonation is a ubiquitous and important process in biology. Protein folding, ligand recognition, enzyme catalysis, membrane potentials, and the energetics of cells depend on ionization and proton transfer. Charge-charge interactions are of special importance for Intrinsically Disordered Proteins, which are known to contain abnormally high numbers of consecutive charged amino acids. Consequently, a great theoretical effort has been devoted to elucidation of protein electrostatic interactions in unfolded state.
## The problem
Polypeptide sequence length is the single dominant factor hampering the effectiveness of currently available software tools for _de novo_ calculation of amino acid-specific protonation constants in disordered polypeptides.
## Our solution
**pepKalc** is robust simulation software for the comprehensive evaluation of protein electrostatics in unfolded state. Our software completely removes the limitations of the previously described Monte-Carlo approaches in the computation of protein electrostatics, by using a hybrid approach that effectively combines exact and mean-field calculations to rapidly obtain accurate results. Paired with a modern architecture CPUs, **pepKalc** is capable of evaluating protonation behavior for an arbitrary-size polypeptide in a sub-second time regime.
## Installation
Clone this repository,
```
git clone https://github.com/PeptoneInc/pepkalc.git
```
and install Python dependencies (you will need `pip` utility for that),
```
pip install scipy numpy
```
## Usage
Call **pepkalc** like any other Python script, parsing command-line paramters, e.g.
```
python pepkalc.py --sequence DDD
```
will perform pKa and Hill parameter estimations for `DDD` polypeptide. Amino acid titration curves will be generated by default in root directory `_titration.dat`. Total charge `Total_Q.dat` and pH dependence of folding stability `Total_G.dat` curves will be produced.
## Parameters
**pepkalc** accepts the following input parameters:
#### --help
Prints out help file in human readable format.
#### --sequence
One-letter amino acid sequence following FASTA convention. Please use `n` and `c` to include N- and C-Terminus in your calculations. Default value `nMDVFMKGLSKAKEGVVAAAEKTKQGVAEAAGKTKEGVLYVGSKTKEGVVHGVATVAEKTKEQVTNVGGAVVTGVTAVAQKTVEGAGSIAAATGFVKKDQLGKNEEGAPQEGILEDMPVDPDNEAYEMPSEEGYQDYEPEAc`.
#### --temperature
The temperature in `K`. Default value `283.15`.
#### --ionicstrength
The ionic strength in `M`. Default value `0.0`.
#### --epsilon
The dielectric permeability of solvent. Default value `83.83` (assuming aqueous solution).
#### --gca
Charge distance shift due to side chain. Default value `5.0`.
#### --gcb
The effective residue separation. Default value `7.5`.
#### --cutoff
The cutoff size for explicit interaction energy calculations. Default value `2`.
#### --ncycles
The number of calculation super-cycles. Default value `3`.
#### --nooutput
Disable titration curve output. `_titration.dat` files will not be written.
#### --silent
Do not write diagnostic messages to Terminal.
## Issues
We are always looking forward to improving **pepkalc**.
Please file bug reports, issues or suggestions using https://github.com/PeptoneLtd/pepkalc/issues
Should you have questions related to scientific and industrial implications of **pepkalc**, please contact us at [email protected].
## Acknowledgments
Authors thank Alison Lowndes and Carlo Ruiz, (NVIDIA Corporation) for facilitating collaboration and access to DGX-1 supercomputing node.
## References
**pepkalc** is based on ongoing scientific research of [Frans A.A. Mulder Laboratory at Aarhus University (Denmark)](http://inano.au.dk/about/research-groups/laboratory-for-biomolecular-nmr-spectroscopy/) and [Peptone - The Protein Intelligence Company](https://peptone.io) into protein electrostatics in unfolded state and development of numerical methods for biophysical characterization of Intrinsically Disordered Proteins.
Please cite **pepkalc** as:
pepKalc - scalable and comprehensive calculation of electrostatic interactions in random coil polypeptides. Tamiola K., Scheek R.M., van der Meulen P., and Mulder F.A.A. Bioinformatics 2017 (Submitted).