Robust simulation software for the comprehensive evaluation of protein electrostatics in unfolded state.
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.
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.
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.
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
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.
pepkalc accepts the following input parameters:
Prints out help file in human readable format.
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.
The temperature in K. Default value 283.15.
The ionic strength in M. Default value 0.0.
The dielectric permeability of solvent. Default value 83.83 (assuming aqueous solution).
Charge distance shift due to side chain. Default value 5.0.
The effective residue separation. Default value 7.5.
The cutoff size for explicit interaction energy calculations. Default value 2.
The number of calculation super-cycles. Default value 3.
Disable titration curve output. _titration.dat files will not be written.
Do not write diagnostic messages to Terminal.
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 support@peptone.io.
Authors thank Alison Lowndes and Carlo Ruiz, (NVIDIA Corporation) for facilitating collaboration and access to DGX-1 supercomputing node.
pepkalc is based on ongoing scientific research of Frans A.A. Mulder Laboratory at Aarhus University (Denmark) and Peptone - The Protein Intelligence Company 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).