{ "info": { "author": "Woolfson Group, University of Bristol", "author_email": "chris.wood@bristol.ac.uk", "bugtrack_url": null, "classifiers": [ "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering :: Bio-Informatics" ], "description": "# ISAMBARD\n\nIntelligent System for Analysis, Model Building And Rational Design.\n\n[![CircleCI](https://circleci.com/gh/isambard-uob/isambard.svg?style=shield)](https://circleci.com/gh/isambard-uob/isambard)\n[![Python Version](https://img.shields.io/badge/python-3.5%2C%203.6-lightgrey.svg)](https://woolfson-group.github.io/isambard/)\n[![MIT licensed](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/woolfson-group/isambard/blob/master/LICENSE.md)\n\nISAMBARD is a Python-based framework for structural analysis and rational\ndesign of biomolecules, with a particular focus on parametric modelling of\nproteins. It is developed and maintained by members of the [Woolfson group, University of Bristol](http://www.chm.bris.ac.uk/org/woolfson/index.html).\n\n### Citing ISAMBARD\nAny publication arising from use of the ISAMBARD software package should cite the following reference:\n\n[Wood CW *et al* (2017) ISAMBARD: an open-source computational environment for biomolecular analysis, modelling and design. *Bioinformatics*, **33**, 3043-50](https://doi.org/10.1093/bioinformatics/btx352)\n\n## Installation\n\nISAMBARD can be installed straight from PyPI using `pip`:\n\n```\npip install isambard\n```\nOr if you want to try an experimental build (you'll need a C compiler), download\nfrom GitHub either by downloading the zipped file or cloning, then navigate to\nthe ISAMBARD folder and type:\n\n```\npip install .\n```\n\n## External Programs\n\nIf you want to add side chains to your designs, you need to have [Scwrl4](\nhttp://dunbrack.fccc.edu/scwrl4/) installed and available on your system path. \n\n## Upgrading to ISAMBARD 2\n\nIf you were already using ISAMBARD prior to the 2.0.0 release, [here's a handy\nguide](https://gist.github.com/ChrisWellsWood/578fcea671acbb68d4a130315874027b)\non the differences between version 1 and 2.\n\n## Quick Start\n\n> Note
\n> If you're not sure what parametric modelling of proteins is, have a\n> play with [CCBuilder 2.0](http://coiledcoils.chm.bris.ac.uk/ccbuilder2/builder).\n\nLet's build a coiled-coil dimer with typical parameters:\n\n```Python\nimport isambard.specifications as specifications\nimport isambard.modelling as modelling\nimport isambard.optimisation\n\nmy_dimer = specifications.CoiledCoil.from_parameters(2, 28, 5, 225, 283)\ndimer_sequences = [\n 'EIAALKQEIAALKKENAALKWEIAALKQ',\n 'EIAALKQEIAALKKENAALKWEIAALKQ'\n]\nmy_dimer = modelling.pack_side_chains_scwrl(my_dimer, dimer_sequences)\nprint(my_dimer.pdb)\n# OUT: \n# HEADER ISAMBARD Model \n# ATOM 1 N GLU A 1 -5.364 -1.566 -0.689 1.00 0.00 N \n# ATOM 2 CA GLU A 1 -4.483 -2.220 0.308 1.00 0.00 C \n# ATOM 3 C GLU A 1 -3.886 -1.143 1.216 1.00 0.00 C \n# ATOM 4 O GLU A 1 -3.740 -1.337 2.425 1.00 0.00 O \n# ATOM 5 CB GLU A 1 -3.389 -3.028 -0.392 1.00 0.00 C \n# ...\n```\n\nDon't know what your parameters might be? Let's optimise them then!\n\n```Python\nimport budeff\nimport isambard.optimisation.evo_optimizers as ev_opts\nfrom isambard.optimisation.evo_optimizers import Parameter\n\nspecification = specifications.CoiledCoil.from_parameters\nsequences = [\n 'EIAALKQEIAALKKENAALKWEIAALKQ',\n 'EIAALKQEIAALKKENAALKWEIAALKQ'\n]\nparameters = [\n Parameter.static('Oligomeric State', 2),\n Parameter.static('Helix Length', 28),\n Parameter.dynamic('Radius', 5.0, 1.0),\n Parameter.dynamic('Pitch', 200, 60),\n Parameter.dynamic('PhiCA', 283, 27), # 283 is equivalent a g position\n]\n\ndef get_buff_total_energy(ampal_object):\n return budeff.get_internal_energy(ampal_object).total_energy\n\nopt_ga = ev_opts.GA(specification, sequences, parameters, get_buff_total_energy)\nopt_ga.run_opt(100, 5, cores=8)\n# OUT:\n# gen\tevals\tavg \tstd \tmin \tmax \n# 0 \t61 \t-820.401\t42.0119\t-908.875\t-750.001\n# 1 \t59 \t-859.86 \t31.4194\t-950.15 \t-807.265\n# 2 \t60 \t-887.028\t23.8683\t-951.153\t-847.346\n# 3 \t70 \t-907.257\t15.9615\t-952.863\t-882.028\n# 4 \t81 \t-922.522\t14.6206\t-972.335\t-903.444\n# Evaluated 431 models in total in 0:00:29.523487\n# Best fitness is (-972.3348571854714,)\n# Best parameters are [2, 28, 4.678360526981807, 151.35365923229745, 277.2061538048508]\noptimized_model = opt_ga.best_model\n```\n\nThis quick example of parametric modelling with ISAMBARD, the next thing to do\nis take a look at the [docs](https://isambard-uob.github.io/isambard/) from\ntutorials on the tools available, or just take a look through the code base and\nhack around. Feel free to contact us through email or the issues if you get\nstuck.\n\n# Release Notes\n\n### v2.2.0\n\n* **Adds pacc module for parametric analysis of coiled coils.**", "description_content_type": "text/markdown; charset=UTF-8; variant=GFM", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/isambard-uob/isambard", "keywords": "", "license": "", "maintainer": "", "maintainer_email": "", "name": "ISAMBARD", "package_url": "https://pypi.org/project/ISAMBARD/", "platform": "", "project_url": "https://pypi.org/project/ISAMBARD/", "project_urls": { "Homepage": "https://github.com/isambard-uob/isambard" }, "release_url": "https://pypi.org/project/ISAMBARD/2.2.0/", "requires_dist": null, "requires_python": "", "summary": "A package for biomolecular analysis, modelling and design", "version": "2.2.0" }, "last_serial": 4168344, "releases": { "2.0.1": [ { "comment_text": "", "digests": { "md5": "d8d82e648605fa055c088abd0aeac8df", "sha256": "7eccb792ee458742fd4ee8493ed18eb2789b33db723b260177ca8bda535836f3" }, "downloads": -1, "filename": "ISAMBARD-2.0.1.tar.gz", "has_sig": false, "md5_digest": "d8d82e648605fa055c088abd0aeac8df", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 337378, "upload_time": "2018-05-21T13:03:11", "url": "https://files.pythonhosted.org/packages/ca/6d/9456a011721c3376fc03e77d5ea89f563dfac30660be8b2517ad1ba2c44a/ISAMBARD-2.0.1.tar.gz" } ], "2.2.0": [ { "comment_text": "", "digests": { "md5": "1fb4c837635e20ccb08db47a74e89550", "sha256": "c7c81ce2deb77619aa561f69abb54980366bd8d29bb635c3a0e4e2ca6feb1c51" }, "downloads": -1, "filename": "ISAMBARD-2.2.0.tar.gz", "has_sig": false, "md5_digest": "1fb4c837635e20ccb08db47a74e89550", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 359587, "upload_time": "2018-08-06T14:37:58", "url": "https://files.pythonhosted.org/packages/9c/ba/636028b8e309e217e171016e34b2a9f5f0b37f3be916d02ad55f97cf4991/ISAMBARD-2.2.0.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "1fb4c837635e20ccb08db47a74e89550", "sha256": "c7c81ce2deb77619aa561f69abb54980366bd8d29bb635c3a0e4e2ca6feb1c51" }, "downloads": -1, "filename": "ISAMBARD-2.2.0.tar.gz", "has_sig": false, "md5_digest": "1fb4c837635e20ccb08db47a74e89550", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 359587, "upload_time": "2018-08-06T14:37:58", "url": "https://files.pythonhosted.org/packages/9c/ba/636028b8e309e217e171016e34b2a9f5f0b37f3be916d02ad55f97cf4991/ISAMBARD-2.2.0.tar.gz" } ] }