A graph theoretical analysis of the energy landscape of model polymers

TL;DR

This paper uses graph theory and a renormalization method to analyze the energy landscape of model polymers, revealing how metastable state networks influence dynamics and stability.

Contribution

It introduces a renormalization approach to study the topology of metastable states in polymer energy landscapes, linking network structure to stability.

Findings

Smaller spectral dimension indicates greater stability of the global energy minimum.

Topology of metastable state networks affects polymer dynamics.

Renormalization reveals non-trivial effects of temperature on energy landscape topology.

Abstract

In systems characterized by a rough potential energy landscape, local energetic minima and saddles define a network of metastable states whose topology strongly influences the dynamics. Changes in temperature, causing the merging and splitting of metastable states, have non trivial effects on such networks and must be taken into account. We do this by means of a recently proposed renormalization procedure. This method is applied to analyze the topology of the network of metastable states for different polypeptidic sequences in a minimalistic polymer model. A smaller spectral dimension emerges as a hallmark of stability of the global energy minimum and highlights a non-obvious link between dynamic and thermodynamic properties.