Elastic Network Models: Theoretical and Empirical Foundations

TL;DR

This paper reviews the theoretical foundations and empirical applications of Elastic Network Models, highlighting their ability to analyze protein dynamics efficiently and discussing potential artifacts in their use.

Contribution

It provides a comprehensive overview of the theoretical tools and practical considerations for studying Elastic Network Models in biological macromolecules.

Findings

Elastic Network Models effectively predict protein dynamics.

Coarse-grained models offer valuable insights into macromolecular behavior.

Potential artifacts in model application are discussed.

Abstract

Fifteen years ago Monique Tirion showed that the low-frequency normal modes of a protein are not significantly altered when non-bonded interactions are replaced by Hookean springs, for all atom pairs whose distance is smaller than a given cutoff value. Since then, it has been shown that coarse-grained versions of Tirion's model are able to provide fair insights on many dynamical properties of biological macromolecules. In this text, theoretical tools required for studying these so-called Elastic Network Models are described, focusing on practical issues and, in particular, on possible artifacts. Then, an overview of some typical results that have been obtained by studying such models is given.