The top 100 docked poses of each ligand are investigated for their interactions with the receptor and their distance from the ground truth, if available. Each pose has associated docking scores from both Autodock Vina and the Convolutional Neural Network (CNN) scoring functions in gnina. Additionally, the interaction fingerprint of each docked pose is computed. The interaction fingerprint profiles and scores the hydrogen bonds, salt bridges, and hydrophobic contacts between the protein and ligand. Hydrogen bond scores are a product of the distance between the donor and the acceptor's hydrogen and the angle between the donor, hydrogen, and acceptor. However, since gnina ignores hydrogens in both the input and output, we add hydrogens to the docked poses with RDKit and minimize the hydrogen atom placement with UFF, ignoring the effect of the protein environment. Both the salt bridge and hydrophobic contact scores are simply the distance between the involved atoms. Unique to Open-ComBind, salt bridges are determined via ligand substructure matches to SMARTS strings, taken from Pharmit , for the detection of positive and negative ions rather than using atoms with a formal charge since gnina does not modify the formal charge of the input molecule based on the receptor environment. These scores are summed by protein residue for each feature type.