MD is typically used to simulate the dynamics of biomolecular systems by application of a force field which gives the forces between the atoms in the system as a function of their positions. With enough simulation time, MD should sample different metastable states with populations that are correct for a given choice of force field and ensemble, assuming that other simulation details-such as the integrator used to propagate dynamics-do not introduce errors. However, in practice sampling transitions between binding modes using MD is typically inefficient because of large energy barriers (and hence slow timescales) separating binding modes. Some free energy calculations attempt to get around this problem by assuming that similar ligands will have similar binding modes, so if a bound structure of a related ligand is available, it is assumed that new related ligands will share the same binding mode. However, this is not necessarily the case -even closely related ligands can have disparate binding modes that are slow to interconvert Perhaps this is one reason why the accuracy of relative free energy calculations based on MD still falls short of what is desired for pharmaceutical applications, therefore, adequate binding mode sampling via direct MD simulation requires considerable computational expense and can necessitate specialized simulation hardware. This inefficiency is compounded further in free energy calculations, as detailed above, where it is often necessary to adequately sample all relevant binding modes at each value to obtain correct binding free energies. In some cases, it is possible to sample long enough at the physical end states to cover all binding modes and then apply restraints to restrict the space treated at intermediate values, then compute the free energy of imposing and removing the restraints at the end states. This can improve efficiency modestly, but still requires simulations on timescales substantially longer than the timescales of the relevant motions.