Force distribution in a semiflexible loop

TL;DR

This study investigates the full distribution of forces in a thermally fluctuating semiflexible loop, revealing insights into force fluctuations beyond average thermodynamic measures using a novel phase-space sampling method.

Contribution

It introduces a new simulation approach for sampling equilibrium conformations in both position and momentum space, enabling detailed force distribution analysis in constrained polymer systems.

Findings

Mean force aligns with thermodynamic predictions

Force distribution is asymmetric and broader than Gaussian

Increasing chain length enhances force fluctuations

Abstract

Loops undergoing thermal fluctuations are prevalent in nature. Ring-like or cross-linked polymers, cyclic macromolecules, and protein-mediated DNA loops all belong to this category. Stability of these molecules are generally described in terms of free energy, an average quantity, but it may also be impacted by local fluctuating forces acting within these systems. The full distribution of these forces can thus give us insights into mechanochemistry beyond the predictive capability of thermodynamics. In this paper, we study the force exerted by an inextensible semiflexible polymer constrained in a looped state. By using a novel simulation method termed "phase-space sampling", we generate the equilibrium distribution of chain conformations in both position and momentum space. We compute the constraint forces between the two ends of the loop in this chain ensemble using Lagrangian mechanics, and show that the mean of these forces is equal to the thermodynamic force. By analyzing kinetic and potential contributions to the forces, we find that the mean force acts in the direction of increasing extension not because of bending stress, but in spite of it. Furthermore, we obtain a distribution of constraint forces as a function of chain length, extension, and stiffness. Notably, increasing contour length decreases the average force, but the additional freedom allows fluctuations in the constraint force to increase. The force distribution is asymmetric and falls off less sharply than a Gaussian distribution. Our work exemplifies a system where large-amplitude fluctuations occur in a way unforeseen by a purely thermodynamic framework, and offers novel computational tools useful for efficient, unbiased simulation of a constrained system.