Allocating and splitting free energy to maximize molecular machine flux

TL;DR

This paper investigates how free energy allocation affects the efficiency of biomolecular machines, revealing that optimal energy splitting depends on detailed dynamics and that reducing vulnerable state occupation enhances processivity in vivo.

Contribution

It introduces a generalized framework for optimizing free energy distribution in molecular machines, considering complex dynamics and vulnerable states, advancing beyond previous simplistic models.

Findings

Flux is maximized by optimal free energy splitting, not just by increasing forward or decreasing reverse rates.

In vivo conditions favor reducing occupation of vulnerable states to maximize processivity.

Optimal energy allocation depends on the detailed conformational dynamics of the machine.

Abstract

Biomolecular machines transduce between different forms of energy. These machines make directed progress and increase their speed by consuming free energy, typically in the form of nonequilibrium chemical concentrations. Machine dynamics are often modeled by transitions between a set of discrete metastable conformational states. In general, the free energy change associated with each transition can increase the forward rate constant, decrease the reverse rate constant, or both. In contrast to previous optimizations, we find that in general flux is neither maximized by devoting all free energy changes to increasing forward rate constants nor by solely decreasing reverse rate constants. Instead the optimal free energy splitting depends on the detailed dynamics. Extending our analysis to machines with vulnerable states (from which they can break down), in the strong driving corresponding to in vivo cellular conditions, processivity is maximized by reducing the occupation of the vulnerable state.