Biological free energy transduction is an Achilles heel of mean-field transport theory

TL;DR

This paper investigates the limitations of mean-field approximations in modeling biological nanoscale transport systems, revealing that it fails in energy-transducing networks due to essential correlations.

Contribution

It demonstrates the failure of mean-field theory in describing energy transduction in biological networks, highlighting the importance of correlations for accurate modeling.

Findings

Mean-field works for linear electron transfer chains.

Fails catastrophically in energy-transducing systems.

Correlations are essential for efficient energy transduction.

Abstract

Studies of nanoscale biological transport often use a mean-field approximation that is exact only when the system is at equilibrium and there are no interactions between particles on different sites in the network. We explore the limitations of this approximation to describe many-particle transport in the context of enzyme function and biological transport networks. Our focus is on three bioenergetic networks: a linear electron transfer chain (as found in bacterial nanowires), a redox-coupled proton pump (as in complex IV of respiration), and a near reversible electron bifurcation network (as in complex III of respiration and other recently discovered structures). Away from equilibrium and with typical site-site interactions, we find that the mean-field approximation adequately describes linear transport chains. However, the mean-field approximation fails catastrophically to describe energy-transducing systems, as in the redox coupled proton pump and reversible electron bifurcation reactions. The mean-field approximation fails to capture the essential correlations that are needed to prevent slippage events and to produce efficient energy transduction.