Graph neural network to assign bond vibrational frequency

Neural network model discussed in "A graph-based machine learning framework to assign empirical interaction parameters for novel molecules" (doi)

It is recommeded that you use a new conda environment to install this package and its dependencies.

conda create --name gravy python=3.11.8

Dependencies

• python 3.11.8
• CUDA 12.1 (optional, see point about DGL)
• chemical_equivalence
• atb_output
• NXMol
• DGL NOTE that the specific DGL version specified in pyproject.toml is tested and compliant with CUDA 12.1 on Linux/WSL. DGL has dropped support for Windows and MacOS, so if you're on those platforms, you will need to comment out the DGL line in pyproject.toml and manually install DGL with an older version of torch.

Installation

# clone this repo
cd Gravy
pip install .

Inference

Example PDB files are in src/gravy/examples. To execute the dexverapamil example, simply run python query.py.

To use your own PDB file (geometry should be optimised), edit query.py so that

PDB_PATH
MOL_NAME
NET_CHARGE

reflect your molecule of interest.

TODO

• Manual passing of fractional bond orders during PDB