Microscopic machines utilize free energy to create and maintain out-ofequilibrium organization in virtually all living things. Often this takes the form of converting the free energy stored in nonequilibrium chemical potential differences into useful work, via a series of reactions involving the binding, chemical catalysis, and unbinding of small molecules. Such chemical reactions occur on timescales much faster than the protein conformational rearrangements they induce. Here, we derive the energetic cost for driving a system out of equilibrium via a series of such effectively instantaneous (and hence discrete) perturbations. This analysis significantly generalizes previously established results, and provides insight into qualitative, as well as quantitative, aspects of finite-time, minimum-dissipation discrete control protocols. We compare our theoretical formalism to an exactly solvable model system and also demonstrate the dissipation reduction achievable in a simple multistable model for a discretely driven molecular machine.

Cells must operate far from equilibrium, utilizing and dissipating energy continuously to maintain their organization and to avoid stasis and death. However, they must also avoid unnecessary waste of energy. Recent studies have revealed that molecular machines are extremely efficient thermodynamically compared with their macroscopic counterparts. However, the principles governing the efficient out-of-equilibrium operation of molecular machines remain a mystery. A theoretical framework has been recently formulated in which a generalized friction coefficient quantifies the energetic efficiency in nonequilibrium processes. Moreover, it posits that, to minimize energy dissipation, external control should drive the system along the reaction coordinate with a speed inversely proportional to the square root of that friction coefficient. Here, we demonstrate the utility of this theory for designing and understanding energetically efficient nonequilibrium processes through the unfolding and folding of single DNA hairpins.

Quantifying energy flows at nanometer scales promises to guide future research in a variety of disciplines, from microscopic control and manipulation, to autonomously operating molecular machines. A general understanding of the thermodynamic costs of nonequilibrium processes would illuminate the design principles for energetically efficient microscopic machines. Considerable effort has gone into finding and classifying the deterministic control protocols that drive a system rapidly between states at minimum energetic cost. But when the nonequilibrium driving is imposed by a molecular machine that is itself strongly fluctuating, driving protocols are stochastic. Here we generalize a linear-response framework to incorporate such protocol variability and find a lower bound on the work that is realized at finite protocol duration, far from the quasistatic limit. Our findings are confirmed in model systems. This theory provides a thermodynamic rationale for rapid operation, independent of functional incentives.

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