Open-ComBind is an easy-to-use, open-source alternative to ComBind, although more work is needed to match the performance gains achieved by Paggi et al. . Open-ComBind provides the molecular modeling community the opportunity to quickly and easily modify the featurization pipeline for increased pose prediction performance utilizing the large quantity of available, non-structural data. Features such as π -π bonds and ligand shape similarity can be added easily to the docking pipeline. Since Open-ComBind uses gnina as the pose generator, we can utilize the internal representation of the CNN scoring functions within the docking pipeline as a featurization of the protein-ligand interaction for little extra computational cost. gnina also allows flexible sidechains during docking which could be used in the Open-ComBind framework for finding different pocket configurations to fit ligands of different sizes or ligands forming non-bonded interactions in different relative locations. Finally, Open-ComBind could be extended to predict the protonation state of the ligand to form better hydrogen bonds with the receptor and select better ligand poses than docking with the input protonation state.