Steady-state balance conditions for molecular motor cycles and stochastic nonequilibrium processes

Molecular motors and nanomachines are considered that are coupled to exergonic processes which provide energy input to these motors and allow them to perform work. The motor dynamics is described by continuous-time Markov processes on a discrete state space, which can contain an arbitrary number of cycles consisting of two dicycles with opposite orientation. For the steady state of such a motor, the statistical entropy produced during the completion of each dicycle is expressed in terms of its transition rates. Identifying this statistical entropy with the heat released by the motor and using the first law of thermodynamics, we derive steady-state balance conditions that generalize the well-known detailed balance conditions in equilibrium. Our derivation is rather general and applies to any nonequilibrium system described as a Markov process. For molecular motors, these balance conditions depend on the external load force and can be decomposed into a zero-force and a force-dependent part