Modeling of biomolecular machines in non-equilibrium steady states

TL;DR

This paper introduces isothermal stochastic thermodynamics as a framework for modeling the complex non-equilibrium dynamics of biomolecular machines, addressing the challenge of extending thermodynamic principles to large, intricate systems.

Contribution

It advances stochastic thermodynamics from simple models to complex biomolecular systems with many degrees of freedom, providing a systematic multiscale modeling approach.

Findings

Provides an introduction to isothermal stochastic thermodynamics for biomolecular systems

Outlines open challenges in multiscale modeling of biomolecular machines

Bridges the gap between theoretical principles and complex biological applications

Abstract

Numerical computations have become a pillar of all modern quantitative sciences. Any computation involves modeling--even if often this step is not made explicit--and any model has to neglect details while still being physically accurate. Equilibrium statistical mechanics guides both the development of models and numerical methods for dynamics obeying detailed balance. For systems driven away from thermal equilibrium such a universal theoretical framework is missing. For a restricted class of driven systems governed by Markov dynamics and local detailed balance, stochastic thermodynamics has evolved to fill this gap and to provide fundamental constraints and guiding principles. The next step is to advance stochastic thermodynamics from simple model systems to complex systems with ten thousands or even millions degrees of freedom. Biomolecules operating in the presence of chemical gradients and mechanical forces are a prime example for this challenge. In this Perspective, we give an introduction to isothermal stochastic thermodynamics geared towards the systematic multiscale modeling of the conformational dynamics of biomolecular and synthetic machines, and we outline some of the open challenges.