Calculating Binding Free Energies in Model Host–Guest Systems with Unrestrained Advanced Sampling

Host–guest interactions are important to the design
of pharmaceuticals
and, more broadly, to soft materials as they can enable targeted,
strong, and specific interactions between molecules. The binding process
between the host and guest may be classified as a “rare event”
when viewing the system at atomic scales, such as those explored in
molecular dynamics simulations. To obtain equilibrium binding conformations
and dissociation constants from these simulations, it is essential
to resolve these rare events. Advanced sampling methods such as the
adaptive biasing force (ABF) promote the occurrence of less probable
configurations in a system, therefore facilitating the sampling of
essential collective variables that characterize the host–guest
interactions. Here, we present the application of ABF to a rod–cavitand
coarse-grained model of host–guest systems to acquire the potential
of mean force. We show that the employment of ABF enables the computation
of the configurational and thermodynamic properties of bound and unbound
states, including the free energy landscape. Moreover, we identify
important dynamic bottlenecks that limit sampling and discuss how
these may be addressed in more general systems.