Thermodynamics of protein folding: a random matrix formulation

TL;DR

This paper presents a random matrix approach to model protein folding, revealing that key thermodynamic properties evolve through a single parameter, which helps explain pathway selection and folding characteristics.

Contribution

It introduces a novel random matrix formulation for protein folding thermodynamics, simplifying complex interactions into a single parametric description.

Findings

Thermodynamic measures follow a single parametric evolution.

The model explains pathway selection in protein folding.

Results align with computer simulation observations.

Abstract

The process of protein folding from an unfolded state to a biologically active, folded conformation is governed by many parameters e.g the sequence of amino acids, intermolecular interactions, the solvent, temperature and chaperon molecules. Our study, based on random matrix modeling of the interactions, shows however that the evolution of the statistical measures e.g Gibbs free energy, heat capacity, entropy is single parametric. The information can explain the selection of specific folding pathways from an infinite number of possible ways as well as other folding characteristics observed in computer simulation studies.