Structure-based drug design allows for rational design of ligands, as computational methods can help predict desired qualities of a potential ligand prior to its synthesis. However, an understanding of ligand binding modes is often viewed as critical for structure-based design yet binding modes are not necessarily well known before compounds are made and tested. Thus, many computational methods seek to predict ligand binding modes. Several such methods for binding mode prediction are available, but overall computational prediction of binding modes is a difficult problem. One of the most commonly used methods for binding mode prediction is docking, which is able to sift through millions of compounds efficiently. Docking, however, does not tend to do well at predicting the true binding mode. On the other end of the spectrum of computational cost are free energy simulation-based methods, which are very promising for structure-based design and are attracting tremendous interest from industry. However, computational methods for studying binding have their limitations. Free energy methods for predicting binding affinity need to start close to, or sample the correct binding mode in order to offer accurate free energy predictions. This reliance on the starting position can cause issues; since the binding mode of a novel ligand has to be predicted and is typically slow to sample in a simulation, adequate sampling of the ligand's motion in the binding site can be challenging. Even in the case of a congeneric series of molecules binding to the same target, the binding mode of the ligands can differ. In order to circumvent some of these shortcomings of MD-based methods, we previously developed a mixed MD/nonequilibrium can-didate Monte Carlo (NCMC) based method, and implemented it in a package called Binding modes of Ligands Using Enhanced Sampling (BLUES). Typically, Monte Carlo (MC) moves have difficulty achieving high acceptance rates in condensed-phase systems because of tight packing, allowing for only small perturbations to be performed on a system. NCMC provides a framework where a larger, instantaneous MC move can be broken up into a series of smaller perturbations. Between each perturbation the system is allowed to relax by applying dynamics. This process is repeated a number of times and the whole move is accepted or rejected based on the total work done during the perturbation steps. In BLUES we use NCMC moves to alchemically remove the interactions of a ligand and then reinstate them over the course of some number of steps (N ). At the start of reinserting the ligand, a MC move can also be performed to further improve binding mode sampling. By slowly removing and regrowing the ligand, we can insert the ligand into a new binding mode and allow the rest of the system to slowly relax in response to the ligand's motion, potentially leading to higher rates of acceptance compared to instantaneous MC moves.