{"id":16467440,"url":"https://github.com/andrewtarzia/enzyme_screen","last_synced_at":"2025-10-07T08:17:52.868Z","repository":{"id":129352576,"uuid":"293850724","full_name":"andrewtarzia/enzyme_screen","owner":"andrewtarzia","description":"Molecular size calculations for enzyme reaction screening in metal--organic frameworks","archived":false,"fork":false,"pushed_at":"2021-02-10T22:15:04.000Z","size":11025,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-07-26T11:41:26.176Z","etag":null,"topics":["enzymes","mofs","molecular-size","screening"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# enzyme_screen\n\n\nScripts and functions for extracting and analysing biochemical reactions.\n\nAuthor: Andrew Tarzia\nEmail: andrew.tarzia@gmail.com or atarzia@ic.ac.uk\n\nThis work was produced in the final year of my PhD at the University of Adelaide under the supervision of A/Prof David Huang and Prof Christian Doonan.\n\nPreviously at: https://bitbucket.org/andrewtarzia/psp_source/src/master/\n\nA Jupyter notebook that runs through the molecular size calculation from a SMILES string is available:\n\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/andrewtarzia/enzyme_screen/master?filepath=examples%2Fcalculate_molecular_size.ipynb)\n\nThe molecular size calculation code is also available in a refactored form at my GitHub and through PyPi: https://github.com/andrewtarzia/mol-ellipsize\n\n## Installation\n\n* Tested on Ubuntu 18.04 using conda and pip\n* Install Anaconda in standard way (Python 3.7.3)\n* Packages required outside of what comes with conda\n * RDKit:\n   * `conda install -c conda-forge rdkit`\n   * Version: 2019.09.2.0\n * chemcost:\n   * Python code written by Steven Bennett for the extraction of purchasability from the ZINC15 database.\n   * Follow instructions found here: https://github.com/stevenbennett96/chemcost\n   * Only required for `molecule_population.py`\n\n## Workflow\n\n\n### Collecting database from KEGG\n\n* Download br08201 JSON file from [the KEGG library](https://www.genome.jp/kegg-bin/get_htext?query=08201\u0026htext=br08902.keg)\n * Used version as of May12_2020 of br08201: Enyzmatic reactions\n* Run `util/split_KEGG.py` in working directory to produce:\n    * `_ECtop.json`: A dictionary of all reactions for all ECs\n    * `_EClist.txt`: A list of all ECs to iterating through\n* Update `data/param_file.txt` with location of these files.\n\n\n### Parameter testing\n\n\n* All parameter screens in the supporting information of DOI: **awaiting** are run in `param_screening.py`\n    * `data/test_molecules.txt` contains the required molecular information\n    * Within `param_screening.py` are the range of parameters to test, the originals being set in `data/param_file.txt`\n\n\n### Reaction collection and analysis\n\n* `RS_collection.py`\n    * Iterates through provided EC and reaction files to collect reaction systems\n    * Also collects unique molecules to molecule database\n    * Currently only implements API for KEGG\n    * To be run in directory with reactions\n\n* `molecule_population.py`\n    * Trivial parallelisation done using `utils/molecule_splitter.py`\n    * Takes _unopt.mol file of all collected molecules:\n        * Optimises them using ETKDG -\u003e _opt.mol\n        * Calculates their properties -\u003e _prop.json\n        * Calculates the molecule size of N conformers -\u003e _size.csv\n    * To be run in directory with molecules\n    * Produces some plots of chemical space\n\n* `chemical_space_plot.py`\n    * Iterates through all collected molecules and plots various chemical space plots\n    * To be run in directory with molecules\n\n* `RS_analysis.py`\n    * `molecule_population.py` must be run before this point!\n        * Unanalysed molecules result in skipped reactions\n    * Populates the properties of each reaction system based on the properties of constituent molecules (in molecule database)\n    * To be run in directory with reactions\n    * Outputs all properties to `rs_properties.csv`\n\n* `screening.py`\n    * Produces the plots and screening of all reaction systems seen in DOI: **awaiting**\n    * Multiple cases are defined within the script to look at specific EC numbers or system types\n        * case = production for plots in DOI:\n    * To be run in directory with reactions\n\n\n## Examples\n\n* `biomin_screening.py`\n    * A script used to produce Figure **XX** in DOI:\n    * Analyses a list of molecules that have been tested for enzyme@ZIF-8 reactions\n\n* `examples/calculate_molecular_size.ipynb`\n    * Jupyter notebook that runs a user through calculating the size of any molecule\n\n* `examples/screen_new_reactions.ipynb`\n    * Jupyter notebook that runs through the screening process exemplified in the paper search for new reactions\n\n* `visualise_ellipsoid_steps.py`\n    * Allows the user to visualise the step-wise calculation of the min. vol. enclosing ellipsoid\n\n* `visualise_reaction_system.py`\n    * Allows the user to print properties of a reaction system\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrewtarzia%2Fenzyme_screen","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fandrewtarzia%2Fenzyme_screen","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrewtarzia%2Fenzyme_screen/lists"}