Getting Started =============== gninatorch_ is a PyTorch_ implementation of GNINA_ scoring function, a CNN-based scoring function for molecular docking. .. note:: gninatorch_ depends on libmolgrid_, and therefore it is only available on Linux and requires a NVIDIA_ GPU. If you use gninatorch_, please consider citing the following papers: :cite:`ragoza2017protein`, :cite:`sunseri2020libmolgrid`, :cite:`francoeur2020three`, and :cite:`mcnutt2021gnina`. Help ---- If you find an issue with gninatorch_, please open a `GitHub issue`_. If you have a question about gninatorch_, please use `GitHub Discussions`_. Installation ------------ Installation from Source ~~~~~~~~~~~~~~~~~~~~~~~~ Clone the repository from GitHub_: .. code-block:: bash git clone https://github.com/RMeli/gnina-torch.git cd gnina-torch Create a conda_ or mamba_ environment with all the dependencies: .. code-block:: bash conda env create -f devtools/conda-envs/gninatorch.yaml conda activate gninatorch Install gninatorch_ from source: .. code-block:: bash python -m pip install . Installation from PyPI ~~~~~~~~~~~~~~~~~~~~~ .. code-block:: bash python -m pip install gninatorch .. warning:: Packages on PyPI are still WIP and should be considered experimental. Testing ------- Run tests with pytest_ and report code coverage: .. code-block:: bash pytest --cov=gninatorch .. raw:: html
.. bibliography:: :cited: .. _GNINA: https://github.com/gnina/gnina .. _conda: https://docs.conda.io/en/latest/ .. _mamba: https://mamba.readthedocs.io/en/latest/user_guide/mamba.html .. _gninatorch: https://gnina-torch.readthedocs.io/en/latest/index.html .. _libmolgrid: https://gnina.github.io/libmolgrid/ .. _NVIDIA: https://www.nvidia.com/ .. _PyTorch: https://pytorch.org/ .. _pytest: https://docs.pytest.org/en/7.1.x/contents.html .. _GitHub: https://github.com/ .. _`GitHub issue`: https://github.com/RMeli/gnina-torch/issues .. _`GitHub Discussions`: https://github.com/RMeli/gnina-torch/discussions