The pairwise feature similarity distributions are pivotal to the Open-ComBind objective function. Shifts from the reference to native distribution help to ensure the poses selected by the Open-ComBind objective are more likely to be pulled from the set of near-native poses. We calculate the pairwise feature similarity distributions by crossdocking all ligands in the Similarity Dataset using gnina. Then the top 100 poses of each ligand were analyzed for their interaction with the receptor structure used for docking. We see in Figure that all of the intermolecular interactions: Hydrogen bonds, Salt Bridges, and Hydrophobic contacts have higher similarity in the native distribution than in the reference distribution. The hydrogen bonds reference distribution is heavily right-skewed, while the native distribution is centered around 0.42 with a Gaussian-like appearance. Salt Bridges are much less frequent interactions, therefore both the native and reference distributions are heavily focused on the points 1 3 , 1 2 , and 2 3 indicating that most ligands only make a small number of salt bridges with the protein. The native distribution shift is not as pronounced in the salt bridge due to its infrequency; however, we still see an increase in the density centered around 2 3 and a decrease in the density around 1 3 Pseudo-Tanimoto similarity relative to the reference distribution. Hydrophobic contact similarity is left skewed in both the native and reference distributions. The native distribution has a mean of 0.83, while the reference distribution has a mean of 0.69. The RMSD of the MCSS shows the same trend as the intermolecular interactions, with the native poses being more similar than the similarity distribution of all poses. Due to the cutoff at 6 Åwe see a spike in both distributions at 6 Å. The spike in the reference distribution far outweighs the left tail. The hyperparameter C is set to 1 following the slopes of the best fit lines in ??.