docktgrid 0.0.3

📌 Features

• GPU-accelerated voxelization of protein-ligand complexes.

• Easy customization of voxel grid channels and parameters.

• Readily usable with PyTorch.

• Support for multiple file formats (to be expanded).

  • ✅ PDB

  • ✅ MOL2

🚀 Getting Started

$ python -m pip install docktgrid

$ git clone https://github.com/gmmsb-lncc/docktgrid.git
$ cd docktgrid

$ python3.11 -m venv env
$ source env/bin/activate

$ conda create --prefix ./venv python=3.11
$ conda activate ./venv

$ python -m pip install -r requirements.txt

$ python -m pytest tests/

🖥️ Usage

See the documentation for more information on how to use DockTGrid.

There are also some examples in the notebooks folder.

📄 License

This project is licensed under the LGPL v3.0 license.

📝 Citation

If you use DockTGrid in your research, please cite:

• da Silva, M. M. P., Guedes, I. A., Custódio, F. L., & Dardenne, L. E. (2024). DockTGrid (0.0.3). Zenodo. https://zenodo.org/doi/10.5281/zenodo.10304711

@software{mpds2024docktgrid,
    author       = {da Silva, Matheus Müller Pereira and
              Guedes, Isabella Alvim and
              Custódio, Fábio Lima and
              Dardenne, Laurent Emmanuel},
    title        = {DockTGrid},
    month        = mar,
    year         = 2024,
    publisher    = {Zenodo},
    version      = {0.0.3},
    doi          = {10.5281/zenodo.10304711},
    url          = {https://zenodo.org/doi/10.5281/zenodo.10304711}
    }