  Molecular dynamics simulations allow to study the structure and dynamics of
single biomolecules in microscopic detail. However, many processes occur on
time scales beyond the reach of fully atomistic simulations and require
coarse-grained multiscale models. While systematic approaches to construct such
models have become available, these typically rely on microscopic dynamics that
obey detailed balance. In vivo, however, biomolecules are constantly driven
away from equilibrium in order to perform specific functions and thus break
detailed balance. Here we introduce a method to construct Markov state models
for systems that are driven through periodically changing one (or several)
external parameter. We illustrate the method for alanine dipeptide, a widely
used benchmark molecule for computational methods, exposed to a time-dependent
electric field.
