Ensemble docking is a computational technique used in the field of molecular docking to address the challenge of protein flexibility when predicting the binding of ligands to their protein targets. Traditional docking methods often treat the protein as a rigid structure, which can lead to inaccuracies because proteins are dynamic and can adopt multiple conformations. Ensemble docking overcomes this limitation by considering multiple conformations of the protein target during the docking process. It uses a set of different protein structures, or an ensemble to represent the various conformations that a protein can adopt. These structures can be sourced from experimental data, such as X-ray crystallography or NMR spectroscopy, or generated computationally through techniques like molecular dynamics simulations . By accounting for protein flexibility, ensemble docking can provide a more accurate prediction of the ligand's binding mode and affinity. It allows the ligand to interact with different conformations of the binding site, which can lead to the identification of the most favorable binding pose across the ensemble . Ensemble docking is computationally more intensive than traditional docking because it involves multiple docking runs, one for each protein conformation. However, advancements in computational power and parallel processing have made it more feasible to perform ensemble docking on a large scale .