It has been shown previously that BMS compounds inhibit the PD-1/PD-L1 interaction by inducing dimerization of PD-L1. Therefore, a PD-L1 homodimer crystal structure (PDB ID: 5N2F) was selected for docking all the compounds in this manuscript. A PD-1/PD-L1 crystal structure (PDB ID: 4ZQK) was also used to check whether the binding site location of PD-L1 in the homodimer crystal structure (5N2F) overlapped and aligned with each other using the PyMol software package (Figure ). In Figure , the selected binding site of the PD-L1 homodimer on the overlapped and aligned crystal structures is shown to indicate that the formation of the homodimer of PD-L1 with small molecules blocks the PD-1/PD-L1 interaction. A known inhibitor of the PD-1/PD-L1 interaction (ligand ID: 8HW) 8 in the selected binding site (Figure ) suggests that the selected binding site corresponding to PD-L1 homodimers is relevant to develop PD-1/PD-L1 inhibitors. Therefore, the docking interactions of the PD-L1 homodimer will be relevant towards identifying PD-1/PD-L1 inhibitors. Also, direct docking with the PD-1/PD-L1 was not carried out since the binding site in between the PD-1 and the PD-L1 is filled with interacting amino acid residues from both proteins. Therefore, there is no space to dock a small compound with the PD-1/PD-L1 complex. CANDOCK was used to generate docking conformations of small molecules with PD-L1 homodimer (see Experimental Section on Generation of Energy Features with Docking and Energy Vector (E) in EGNN for details). Before developing a machine learning method, we also assessed the ability of only using the docking scores for compounds in the training set for each of the 96 potential energy scoring functions in CANDOCK to classify the high potency vs low potency molecules. Cohen's Kappa scores were used to select the best scoring functions to differentiate between two classes. (Table ). The scoring function, radial cumulative complete 15 (RCC15) acquired the highest Cohen's kappa score of 0.41447. However, RCC15 scores were not able to clearly separate all the high and low potent classified molecules in the training data (see Violin plots in Figure ). Using only one scoring function is not sufficient to capture the different states of PD-1/PD-L1 inhibition with small molecules. Therefore, we developed an EGNN model using top scoring function of each class which demonstrated a positive Cohen's kappa value (Table ) to represent the global features (see Experimental Section on Generation of Energy Features with Docking and Energy Vector (E) in EGNN for details). This included RCR15 (kappa = 0.37746) and RCC15 (kappa = 0.41447) scoring functions. A model with kappa score between 0.21 -0.40 is considered as a fair agreement model and if the kappa score is between 0.41 -0.60, then the model is considered as a moderate agreement model.