Measuring irreversibility in stochastic systems by categorizing single-molecule displacements

TL;DR

This paper introduces a model-free method to quantify irreversibility in stochastic systems by categorizing single-molecule displacements, enabling insights into energy landscapes and protein folding without detailed force measurements.

Contribution

A novel, model-free approach to measure irreversibility from single-molecule data, linking it to entropy production and applied to protein folding experiments.

Findings

Irreversibility measurement correlates with energy landscape features

Method provides a lower bound to entropy production

Validated on protein force spectroscopy data

Abstract

Quantifying the irreversibility and dissipation of non-equilibrium processes is crucial to understanding their behavior, assessing their possible capabilities, and characterizing their efficiency. We introduce a physical quantity that quantifies the irreversibility of stochastic Langevin systems from the observation of individual molecules' displacements. Categorizing these displacements into a few groups based on their initial and final position allows us to measure irreversibility precisely without the need to know the forces and magnitude of the fluctuations acting on the system. Our model-free estimate of irreversibility is related to entropy production by a conditional fluctuation theorem and provides a lower bound to the average entropy production. We validate the method on single-molecule force spectroscopy experiments of proteins subject to force ramps. We show that irreversibility is sensitive to detailed features of the energy landscape underlying the protein folding dynamics and suggest how our methods can be employed to unveil key properties of protein folding processes.