In some cases, sampling can be dramatically accelerated by introducing Monte Carlo proposals informed by prior information, but this becomes increasingly difficult in condensed phase systems. As a running example, consider a bistable dimer. If we know approximately the relative locations of free energy minima (i.e. how far apart are the minima of the bond-length term), we might construct proposals that instantaneously hop from the vicinity of one minimum to the vicinity of the other. In a vacuum, this will dramatically accelerate mixing between the two metastable states of the dimer. However, in a densely solvated environment it can be difficult to construct nontrivial proposals that avoid having near-universal rejection since instantaneously perturbing the coordinate of interest is likely to introduce clashes with solvent. While high acceptance rates could be achieved with extremely small perturbations, the long correlation times resulting from these small perturbations leads to highly inefficient sampling. Thus, while MC techniques have seen substantial use for biomolecular systems, much of the field has moved towards using MD as a more general sampling engine and MC has to some extent fallen out of favor, partly because naïve MC moves in densely packed systems tend to overwhelmingly be rejected. However, there have been some successes at combining MC and MD. For example the common replica and Hamiltonian replica exchange approaches use MC moves (involving swaps between replica simulations run under different conditions) to allow increased sampling in a variety of systems. MD itself can also be used as a Markov Chain Monte Carlo (MCMC) proposal move as in hybrid Monte Carlo. Additionally, in prior work in the YANK package, MC rotational and translational moves have been combined with MD to help with rapid ligand positional/orientational decorrelation while doing binding free energy calculations in implicit solvent. In general, however, designing MC moves that fully exploit available knowledge (to make nonlocal proposals) while retaining reasonable acceptance rates is difficult in the condensed-phase.