$E_\mathrm h(\Gamma_n)$ is many times $T^*_A$, then the configuration is “hung up” and does not obey the constraints. If this happens frequently, the simulation needs to be rerun with a smaller setting for $\alpha$; if, on the other hand, it happens only rarely, we would merely reject the step. We can also monitor the mean acceptance rates $ \overline A \mathord{\uparrow}$ and $\overline A \mathord{\downarrow}$. These should be about the same; however, if $\alpha$ is too large, we will find $ \overline A
\mathord{\uparrow} \gg \overline A \mathord{\downarrow}$.

A useful guideline for picking $T^*_A$ is that once the $n$ $E_\mathrm
h$ moves are completed and the system is presumably equilibrated to $T^*_A$, we should be able to enforce the constraints by setting $T^* =
0$ (using any convenient energy minimization technique) with a negligible change in the configuration, e.g., with a negligible change in $E_\mathrm s(\Gamma)$.

Pairwise terms in energy
========================

Having made an adiabatic move using $E_\mathrm h$, the final step is to accept the move depending on the change in $E_\mathrm s$. We wish to compute this energy as efficiently as possible by using the rigidity of the fragments. Force fields such as Amber [@cornell95] include two types 