Deep Graph Networks for Drug Repurposing with Multi-Protein Targets (with COVID-19 use case)

Official code repository for our paper Deep Graph Networks for Drug Repurposing with Multi-Protein Targets.

If you find our work useful for your research, please consider citing the following paper:

@article{gravina2023DrugRep,
	 author = {Bacciu, Davide and Errica, Federico and Gravina, Alessio and Madeddu, Lorenzo and Podda, Marco and Stilo, Giovanni},
	 title = {Deep Graph Networks for Drug Repurposing with Multi-Protein Targets},
	 journal = {IEEE Transactions on Emerging Topics in Computing},
	 year = {2023},
	 volume={}
	 number={},
	 pages={1-14},
	 doi={10.1109/TETC.2023.3238963}
}

Installation

We provide a script to install the environment. You will need the conda package manager, which can be installed from here.

To install the required packages (tested on a linux terminal):

• clone the repository

  • git clone https://github.com/gravins/covid19-drug-repurposing-with-DGNs.git

• cd into the cloned directory

  • cd covid19-drug-repurposing-with-DGNs

• run the install script

  • ./requirements/install_cpu.sh

The script will create a virtual environment named covid-cpu, with all the required packages needed to run our code.

Data download

The zipped dataset folder can be downloaded from here.

Run the experiment

Note: To run the experiment is fundamental to define the task and model in the file run.sh or run_cluster.sh files.

• if you run the experiment on a standard machine:

  • ./run.sh

• if you run the experiment on cluster managed by slurm:

  • ./run_cluster.sh

• if you want to run the GraphDTA or DeepDTA baseline then

  • cd DeepPurpose_baselines
  • python3 -u main.py
  • For more details launch python3 main.py --help

Troubleshooting

If you get errors like /lib64/libstdc++.so.6: version 'GLIBCXX_3.4.21' not found:

• conda install -c conda-forge c-compiler cxx-compiler
• echo $LD_LIBRARY_PATH should contain :[path to your anaconda or miniconda folder name]/lib