{"id":19213766,"url":"https://github.com/peptoneltd/pepkalc","last_synced_at":"2025-05-12T22:20:36.119Z","repository":{"id":110042067,"uuid":"100365687","full_name":"PeptoneLtd/pepkalc","owner":"PeptoneLtd","description":"Robust simulation software for the comprehensive evaluation of protein electrostatics in unfolded state.","archived":false,"fork":false,"pushed_at":"2022-08-23T09:00:20.000Z","size":25,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-20T18:41:03.946Z","etag":null,"topics":["bioinformatics","biophysics","electrostatics","polymer","prediction","protein","protein-sequence","protonation","simulation"],"latest_commit_sha":null,"homepage":"https://peptone.io","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/PeptoneLtd.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2017-08-15T10:14:33.000Z","updated_at":"2024-10-16T20:09:52.000Z","dependencies_parsed_at":"2023-04-14T22:31:51.009Z","dependency_job_id":null,"html_url":"https://github.com/PeptoneLtd/pepkalc","commit_stats":{"total_commits":22,"total_committers":4,"mean_commits":5.5,"dds":"0.13636363636363635","last_synced_commit":"68ab37f23b8ade192a4f6b88589e06f47f991d81"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PeptoneLtd%2Fpepkalc","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PeptoneLtd%2Fpepkalc/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PeptoneLtd%2Fpepkalc/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/PeptoneLtd%2Fpepkalc/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/PeptoneLtd","download_url":"https://codeload.github.com/PeptoneLtd/pepkalc/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253831183,"owners_count":21971046,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bioinformatics","biophysics","electrostatics","polymer","prediction","protein","protein-sequence","protonation","simulation"],"created_at":"2024-11-09T14:07:33.973Z","updated_at":"2025-05-12T22:20:36.091Z","avatar_url":"https://github.com/PeptoneLtd.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# pepkalc\nRobust simulation software for the comprehensive evaluation of protein electrostatics in unfolded state.\n\n## Protein electrostatics\nProtonation 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.\n\n## The problem\nPolypeptide 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.\n\n## Our solution\n**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.\n\n## Installation\nClone this repository,\n```\ngit clone https://github.com/PeptoneInc/pepkalc.git\n```\nand install Python dependencies (you will need `pip` utility for that),\n```\npip install scipy numpy\n```\n\n## Usage\nCall **pepkalc** like any other Python script, parsing command-line paramters, e.g.\n```\npython pepkalc.py --sequence DDD\n```\nwill 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.\n\n## Parameters\n**pepkalc** accepts the following input parameters:\n\n#### --help\nPrints out help file in human readable format.\n\n#### --sequence\nOne-letter amino acid sequence following FASTA convention. Please use `n` and `c` to include N- and C-Terminus in your calculations. Default value `nMDVFMKGLSKAKEGVVAAAEKTKQGVAEAAGKTKEGVLYVGSKTKEGVVHGVATVAEKTKEQVTNVGGAVVTGVTAVAQKTVEGAGSIAAATGFVKKDQLGKNEEGAPQEGILEDMPVDPDNEAYEMPSEEGYQDYEPEAc`.\n\n#### --temperature\nThe temperature in `K`. Default value `283.15`.\n\n#### --ionicstrength\nThe ionic strength in `M`. Default value `0.0`.\n\n#### --epsilon\nThe dielectric permeability of solvent. Default value `83.83` (assuming aqueous solution).\n\n#### --gca\nCharge distance shift due to side chain. Default value `5.0`.\n\n#### --gcb\nThe effective residue separation. Default value `7.5`.\n\n#### --cutoff\nThe cutoff size for explicit interaction energy calculations. Default value `2`.  \n\n#### --ncycles\nThe number of calculation super-cycles. Default value `3`.\n\n#### --nooutput\nDisable titration curve output. `_titration.dat` files will not be written.\n\n#### --silent\nDo not write diagnostic messages to Terminal.\n\n## Issues\nWe are always looking forward to improving **pepkalc**.\n\nPlease file bug reports, issues or suggestions using https://github.com/PeptoneLtd/pepkalc/issues\n\nShould you have questions related to scientific and industrial implications of **pepkalc**, please contact us at support@peptone.io.\n\n## Acknowledgments\nAuthors thank Alison Lowndes and Carlo Ruiz, (NVIDIA Corporation) for facilitating collaboration and access to DGX-1 supercomputing node.\n\n## References\n**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.\n\nPlease cite **pepkalc** as:\n\npepKalc - 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).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpeptoneltd%2Fpepkalc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpeptoneltd%2Fpepkalc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpeptoneltd%2Fpepkalc/lists"}