Thermodynamic uncertainty relation for biomolecular processes

TL;DR

This paper establishes a fundamental thermodynamic uncertainty relation for biomolecular processes, linking the precision of observables to the energetic cost in steady-state Markov systems, applicable to molecular motors and enzymatic reactions.

Contribution

It generalizes the thermodynamic uncertainty relation to biomolecular processes modeled as Markov networks, providing a universal bound on precision-cost trade-offs.

Findings

Dispersion of biomolecular observables is constrained by thermodynamic cost.

Uncertainty in output requires a minimum energetic expenditure of 2kBT/ε².

Relation holds for steady-state Markov processes in biological systems.

Abstract

Biomolecular systems like molecular motors or pumps, transcription and translation machinery, and other enzymatic reactions can be described as Markov processes on a suitable network. We show quite generally that in a steady state the dispersion of observables like the number of consumed/produced molecules or the number of steps of a motor is constrained by the thermodynamic cost of generating it. An uncertainty $\epsilon$ requires at least a cost of $2k_BT/\epsilon^2$ independent of the time required to generate the output.