  Most computer simulations of molecular dynamics take place under equilibrium
conditions -- in a closed, isolated system, or perhaps one held at constant
temperature or pressure. Sometimes, extra tensions, shears, or temperature
gradients are introduced to those simulations to probe one type of
nonequilibrium response to external forces. Catalysts and molecular motors,
however, function based on the nonequilibrium dynamics induced by a chemical
reaction's thermodynamic driving force. In this scenario, simulations require
chemostats capable of preserving the chemical concentrations of the
nonequilibrium steady state. We develop such a dynamic scheme and use it to
observe cycles of a new particle-based classical model of a catenane-like
molecular motor. Molecular motors are frequently modeled with
detailed-balance-breaking Markov models, and we explicitly construct such a
picture by coarse-graining the microscopic dynamics of our simulations in order
to extract rates. This work identifies inter-particle interactions that tune
those rates to create a functional motor, thereby yielding a computational
playground to investigate the interplay between accuracy, current generation,
and efficiency of molecular information ratchets.
