bcpaff - Exploring protein-ligand binding affinity prediction with electron density-based geometric deep learning
Details are described in our [paper] (TODO: add link). Please cite if you use this work.
To setup the conda environment, install Multiwfn, and download the datasets, just run the following in your $CWD:
cd bcpaff
make
(this step uses mamba, you can change it to conda by using make with_conda
instead).
Structure preparation and training (remove --test_run
to run on all structures; remove --cluster_options no_cluster
to run via Slurm):
make data_processing
(basically running bcpaff.data_processing.data_processing
)
ML model training:
make ml_experiments
To interactively visualize BCPs in Jupyter Notebook:
from bcpaff.qtaim.qtaim_viewer import QtaimViewer
from bcpaff.qtaim.qtaim_reader import QtaimProps
qp = QtaimProps(basepath="PATH_TO_COMPOUND_FOLDER")
v = QtaimViewer(qp)
v.show()