This would result in the protein-ligand interaction features failing to capture important interactions between the protein and the ligand, as an accurate docked pose with respect to the correct conformation of the protein's binding pocket is not available. This highlights the need for new experiments to look at the influence of induced fit on docking and subsequent binding affinity predictions when using machine learning models. By opening the door to the use of docked poses, our hybrid approach expands the utility machine learning scoring functions for the discovery of novel small molecules for novel targets.