Open-ComBind is an open-source alternative to ComBind, developed by Paggi et al. , that has comparable increases in pose prediction performance over the respective baseline docking method. Building out Open-ComBind took a concerted effort as the original pipeline uses opaque software tools with unspecified methods for pose generation and featurization of the docked poses. The feature distributions generated with only the poses of a single ligand conformation gnina docking run did not show more similarity in the native distribution than in the reference distributions. By comparing the inter-pose RMSD pose of both gnina and Glide, we found that Glide was much more likely to output a set of highly similar poses while gnina did not. Therefore, we were able to increase similarity of the native distributions by docking a set of ten ligand conformations and combining the docking runs of each conformation into one single set of poses which were sorted by CNNscore. This produces a list of 100 conformations that has a higher likelihood of being less than 2 ÅRMSD from the ground truth and reduces the RMSD between better scoring poses.