README for Reduced Graph Lead Optimisation Tool

This repository contains the implementation and dataset for our paper "Visualising Lead Optimisation Series Using Reduced Graphs"

Code

Installation

The code can be installed directly GitHub with:

$ pip install git+https://github.com/SheffieldChemoinformatics/reduced_graph_visualisation.git

Creating a Conda Environment

Please install a conda environment with all the requirements in visualisation_conda_env.yml

Instantiating The Server

Start the visualisation server by using the script

$ ./start_server.sh

or

$ python lead_optimisation_visualisation.py runserver

The visualisation can then be run on a laptop or computer at the following address:

http://127.0.0.1:5000/

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How To Use The Reduced Graph Visualisation

For instructions on how to use the Reduced Graph visualisation can be found in docs/How_to_use_the_RG_core_tool.docs

To Run Your Own Dataset Through The Reduced Graph Visualisation Tool

To run a new dataset - select 'New Dataset' and select your chosen file, it must be in the format SMILES ID pIC50.
This may take a while to run depending on the size of the dataset.

The workflow can be done independently and then the corresponding output files added to the visualisation

Workflow:
   Step 1: Run python/reduced_graph_code/reduced_graph.py
     Example code:

$ python reduced_graph.py -i input_smiles.smi -o output_rg.txt

   Step 2: Run python/MCS/mcs_similarity_matrix.py
     Example code:

$ python mcs_similarity_matrix.py -i output_rg.txt -s output_rg.sdf -o rg_mcs.txt

   Step 3: Run python/reduced_graph_core_extraction/finding_cores_from_whole_dataset.py
     Example code:

$ python finding_cores_from_whole_dataset.py -i output_rg.txt -m rg_mcs.txt -o output_rg_core_extraction.txt

   Step 4: Run python/generating_files_for_visualisation/generating_file_for_visualisation_coordinates.py (The -o must be in the format _coordinates.txt)
     Example code:

$ python generating_file_for_visualisation_coordinates.py -i output_rg.txt -s output_rg.sdf -o testdataset_coordinates.txt

   Step 5: Run python/generating_files_for_visualisation/creating_visualisation_file.py (The -o must be in the format _node_information.txt)
     Example code:

$ python creating_visualisation_file.py-i output_rg.txt -s output_rg.sdf -a testdataset_activities.txt -c output_rg_core_extraction.txt -o testdataset_node_information.txt

   Step 6: Run python/generating_files_for_visualisation/creating_core_breakdown_analysis_file.py (The -o must be in the format _core_analysis.txt)
     Example code:

$ python creating_core_breakdown_analysis_file.py -i testdataset_node_information.txt -o testdataset_core_analysis.txt

The output files from Step 4, 5 and 6 need to be added to the datasets folder and add the dataset name too datasets/datasets.json (for this example it would be testdataset) and restart the server to be able to see the dataset within the Reduced Graph Lead Optimisation Tool

Citing

If you use the Reduced Graph Visualisation in your analysis, please cite our paper.

Contacts

Please contact me at jessiestacey@msn.com for any questions or comments.