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Modeling Protein-Ligand Interactions with GraphConvolutional Networks for InterpretablePharmaceutical Discovery

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PLA-Net: Predicting Protein-Ligand Interactions with Graph Convolutional Networks for Interpretable Pharmaceutical Discovery

Paola Ruiz Puentes, Laura Rueda-Gensini, Natalia Valderrama, Isabela Hernández, Cristina González, Laura Daza, Carolina Muñoz-Camargo, Juan C. Cruz, Pablo Arbeláez

This repository contains the official implementation of PLA-Net: Predicting target–ligand interactions with graph convolutional networks for interpretable pharmaceutical discovery.

Paper

Predicting target–ligand interactions with graph convolutional networks for interpretable pharmaceutical discovery,
Paola Ruiz Puentes1,2, Laura Rueda-Gensini1,2, Natalia Valderrama1,2, Isabela Hernández1,2, Cristina González1,2, Laura Daza1,2, Carolina Muñoz-Camargo2, Juan C. Cruz2, Pablo Arbeláez1
Scientific Reports, 2022.

1 Center for Research and Formation in Artificial Intelligence .(CINFONIA), Universidad de los Andes, Bogotá 111711, Colombia.
2 Department of Biomedical Engineering, Universidad de los Andes, Bogotá 111711, Colombia.

Installation

The following steps are required in order to run PLA-Net:

$ export PATH=/usr/local/cuda-11.0/bin:$PATH <br />
$ export LD_LIBRARY_PATH=/usr/local/cuda-11.0/lib64:$LD_LIBRARY_PATH <br />

$ conda create --name PLA-Net <br />
$ conda activate PLA-Net <br />

$ bash env.sh

Models

We provide trained models available for download in the following link.

Usage

To train each of the components of our method: LM, LM+Advs, LMPM and PLA-Net please refer to planet.sh file and run the desired models.

To evaluate each of the components of our method: LM, LM+Advs, LMPM and PLA-Net please run the corresponding bash file in the inference folder.

Citation

We hope you find our paper useful. To cite us, please use the following BibTeX entry:

@article{ruiz2022predicting,
  title={Predicting target--ligand interactions with graph convolutional networks for interpretable pharmaceutical discovery},
  author={Ruiz Puentes, Paola and Rueda-Gensini, Laura and Valderrama, Natalia and Hern{\'a}ndez, Isabela and Gonz{\'a}lez, Cristina and Daza, Laura and Mu{\~n}oz-Camargo, Carolina and Cruz, Juan C and Arbel{\'a}ez, Pablo},
  journal={Scientific reports},
  volume={12},
  number={1},
  pages={1--17},
  year={2022},
  publisher={Nature Publishing Group}
}

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Modeling Protein-Ligand Interactions with GraphConvolutional Networks for InterpretablePharmaceutical Discovery

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