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enzyme_screen

Scripts and functions for extracting and analysing biochemical reactions.

Author: Andrew Tarzia Email: andrew.tarzia@gmail.com or atarzia@ic.ac.uk

This 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.

Previously at: https://bitbucket.org/andrewtarzia/psp_source/src/master/

A Jupyter notebook that runs through the molecular size calculation from a SMILES string is available:

Binder

The molecular size calculation code is also available in a refactored form at my GitHub and through PyPi: https://github.com/andrewtarzia/mol-ellipsize

Installation

  • Tested on Ubuntu 18.04 using conda and pip
  • Install Anaconda in standard way (Python 3.7.3)
  • Packages required outside of what comes with conda
  • RDKit:
    • conda install -c conda-forge rdkit
    • Version: 2019.09.2.0
  • chemcost:

Workflow

Collecting database from KEGG

  • Download br08201 JSON file from the KEGG library
  • Used version as of May12_2020 of br08201: Enyzmatic reactions
  • Run util/split_KEGG.py in working directory to produce:
    • _ECtop.json: A dictionary of all reactions for all ECs
    • _EClist.txt: A list of all ECs to iterating through
  • Update data/param_file.txt with location of these files.

Parameter testing

  • All parameter screens in the supporting information of DOI: awaiting are run in param_screening.py
    • data/test_molecules.txt contains the required molecular information
    • Within param_screening.py are the range of parameters to test, the originals being set in data/param_file.txt

Reaction collection and analysis

  • RS_collection.py

    • Iterates through provided EC and reaction files to collect reaction systems
    • Also collects unique molecules to molecule database
    • Currently only implements API for KEGG
    • To be run in directory with reactions
  • molecule_population.py

    • Trivial parallelisation done using utils/molecule_splitter.py
    • Takes _unopt.mol file of all collected molecules:
      • Optimises them using ETKDG -> _opt.mol
      • Calculates their properties -> _prop.json
      • Calculates the molecule size of N conformers -> _size.csv
    • To be run in directory with molecules
    • Produces some plots of chemical space
  • chemical_space_plot.py

    • Iterates through all collected molecules and plots various chemical space plots
    • To be run in directory with molecules
  • RS_analysis.py

    • molecule_population.py must be run before this point!
      • Unanalysed molecules result in skipped reactions
    • Populates the properties of each reaction system based on the properties of constituent molecules (in molecule database)
    • To be run in directory with reactions
    • Outputs all properties to rs_properties.csv
  • screening.py

    • Produces the plots and screening of all reaction systems seen in DOI: awaiting
    • Multiple cases are defined within the script to look at specific EC numbers or system types
      • case = production for plots in DOI:
    • To be run in directory with reactions

Examples

  • biomin_screening.py

    • A script used to produce Figure XX in DOI:
    • Analyses a list of molecules that have been tested for enzyme@ZIF-8 reactions
  • examples/calculate_molecular_size.ipynb

    • Jupyter notebook that runs a user through calculating the size of any molecule
  • examples/screen_new_reactions.ipynb

    • Jupyter notebook that runs through the screening process exemplified in the paper search for new reactions
  • visualise_ellipsoid_steps.py

    • Allows the user to visualise the step-wise calculation of the min. vol. enclosing ellipsoid
  • visualise_reaction_system.py

    • Allows the user to print properties of a reaction system

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