area from the MD simulation 10 or choosing a combination of protein and ligand atoms that result in the lowest standard deviation across all six bond, angle and dihedral terms calculated across the equilibration simulation. All methods have in common that only protein backbone (and C beta) atoms were considered for the restraints. Approaches varied in the selection of the ligand atoms. Neighboring heavy atoms were considered, while others only considered heavy atoms within rigid scaffolds 10 to avoid restraining rotatable bonds and therefore locking-in conformations. A different approach selects ligand atoms with the farthest distance from one another. Our approach builds on previous work by developing a heuristic algorithm aimed at identifying atoms that are likely to remain relatively stable as long as the ligand maintains the same binding mode, thus allowing them to effectively restrain the ligand's motion as ligand interactions are removed. An example is shown in Figure . Restraining ligand atoms that change their position during the simulation (Figure I.) may lead to slow convergence while restraining stable ligand atoms (Figure III.) can be more efficient. Similarly, convergence can be negatively affected if protein atoms involved in the restraints change their position substantially during a simulation. The algorithm is therefore designed to pick protein atoms that are likely to maintain a fairly constant position. Our aim here is to develop a restraining protocol that should work well on a large fraction of systems, however, we are aware that it is possible that no single algorithm will be ideally suited to all cases. The code for this restraining protocol is detailed below can be found in the GitHub repository SeparatedTopologies. As one option, the equilibrated and minimized complex structure could be used to determine the Boresch restraint atoms. However, this has the drawback that it may not always be obvious which atoms will be stable from a single set of coordinates. A way to get around this is to use an entire trajectory. For example, protein-ligand complexes are often equilibrated and some data is collected prior to binding free energy calculations. Such simulations can be analyzed to help select atoms for restraints. In this work, we designed our restraints selection tool so that, if an input trajectory is provided, it is used to ensure that only atoms with relatively minimal fluctuations in their positions are considered as possible reference atoms for restraints. In particular, all protein and ligand atoms with an RMSF > 0.1 Å are excluded and not considered for the restraints. While the ideal cutoff value might depend on the length of the input simulation, we found this cutoff at 0.1 Å to be a practical threshold for simulations of 2 ns where frames are saved every 4 ps.