Trajectory and Cycle-Based Thermodynamics and Kinetics of Molecular Machines: The Importance of Microscopic Reversibility

A molecular machine is a nanoscale device that provides a mechanism for coupling energy from two (or more) processes that in the absence of the machine would be independent of one another. Examples include walking of a piTtein in one direction along a polymeric track (process 1, driving force X-1 = -(F) over right arrow.(l) over right arrow) and hydrolyzing ATP (process 2, driving force X-2 = Delta mu(ATP)); or synthesis of ATP (process 1, X-1 = -Delta mu(ATP)) and transport of protons from the periplasm to the cytoplasm across a membrane (process 2, X-2 = Delta mu(H+)); or rotation of a flagellum (process 1, X-1 = -torque) and transport of protons across a membrane (process 2, X-2 = Delta mu(H+)). In some ways, the function of a molecular machine is similar to that of a macroscopic machine such as a car that couples combustion of gasoline to translational motion. However, the low Reynolds number regime in which molecular machines operate is very different from that relevant for macroscopic machines. Inertia is negligible in comparison to viscous drag, and omnipresent thermal noise causes the machine to undergo continual transition among many states even at thermodynamic equilibrium. Cyclic trajectories among the states of the machine that result in a change in the environment can be broken into two classes: those in which process 1 in either the forward or backward direction (S-1) occurs and which thereby exchange work W-S = +/- X-1 with the environment; and those in which process 2 in either the forward or backward direction (S-2) occurs and which thereby exchange work W-S = +/- X-2 with the evironment. These two types of trajectories, S-1 and S-2, overlap, i.e., there are some trajectories in which both process 1 and process 2 occur, and for which the work exchanged is W-S = +/- X-1 +/- X-2. The four subclasses of overlap trajectories [(+1,+2), (+1,-2), (-1,+2), (-1,-2)] are the coupled processes. The net probabilities for process 1 and process 2 are designated pi(+2) - pi(-2) and pi(+1) - pi(-1), respectively. The probabilities pi(S) for any single trajectory S and pi(S dagger) for its microscopic reverse S-dagger are related by microscopic reversibility (MR), pi(S) = pi(S dagger) e(Ws), an equality that holds arbitrarily far from thermodynamic equilibrium, i.e., irrespective of the magnitudes of X-1 and X-2, and where W-S dagger = -W-S. Using this formalism, we arrive at a remarkably simple and general expression for the rates of the processes, J(i) = C-i(1 - < e(W+Xi)> e-(Xi)), i = 1, 2, where the angle brackets indicate an average over the ensemble of all microscopic reverse trajectories. Stochastic description of coupling is doubtless less familiar than typical mechanical depictions of chemical coupling in terms of ATP induced violent kicks, judo throws, force generation and power-strokes. While the mechanical description of molecular machines is comforting in its familiarity, conclusions based on such a phenomenological perspective are often wrong. Specifically, a power-stroke model (i.e. , a model based on energy driven promotion of a molecular machine to a high energy state followed by directional relaxation to a lower energy state) that has been the focus of mechanistic discussions of biomolecular machines for over a half century is, for catalysis driven molecular machines, incorrect. Instead, the key principle by which catalysis driven motors work is kinetic gating by a mechanism known as an information ratchet. Amazingly, this same principle is that by which catalytic molecular systems undergo adaptation to new steady states while facilitating an exergonic chemical reaction.