For instance, several groups have used 3D convolutional neural networks (CNNs) on voxel grids defined by protein-ligand complexes. Notably, this is the approach taken by Gnina. Alternatively, graph neural network architectures such as message-passing neural networks (MPNNs) on the 3D interaction graph of the complex have been proposed. Regardless of the architecture, the performance of all deep learning models that score 3D protein-ligand complexes is limited by the available data. For instance, many models have been trained with the PDBbind dataset, which uses 3D protein-ligand complexes from the Protein Data Bank (PDB) mapped to known activities. This dataset incorporates ca.