Internal energy and information flows mediate input and output power in bipartite molecular machines

TL;DR

This paper investigates how internal energy and information transfer influence power output in coupled molecular machines, revealing optimal coupling conditions that maximize power and information flow, with implications for biological energy transduction.

Contribution

It introduces a model of coupled stochastic rotary motors to analyze the role of coupling strength in thermodynamic performance and information transfer in molecular machines.

Findings

Maximum power occurs near optimal coupling strength.

Information transduction peaks at intermediate coupling.

Equal entropy production rates in subsystems at optimal power.

Abstract

Microscopic biological systems operate far from equilibrium, are subject to strong fluctuations, and are composed of many coupled components with interactions varying in nature and strength. Researchers are actively investigating the general design principles governing how biomolecular machines achieve effective free-energy transduction in light of these challenges. We use a model of two strongly coupled stochastic rotary motors to explore the effect of coupling strength between components of a molecular machine. We observe prominent thermodynamic characteristics at intermediate coupling strength, near that which maximizes output power: a maximum in power and information transduced from the upstream to the downstream system, and equal subsystem entropy production rates. These observations are unified through a bound on the machine's input and output power, which accounts for both the energy and information transduced between subsystems.