Function changing mutations in glucocorticoid receptor evolution correlate with their relevance to mode coupling

TL;DR

This study demonstrates that nonlinear effects in protein dynamics, analyzed through a novel method, can predict functionally relevant amino acids in glucocorticoid receptor evolution, linking mutations to mode coupling.

Contribution

The paper introduces a method leveraging nonlinear dynamics to identify functional amino acids, applied here to ancestral glucocorticoid receptors, revealing mutation sites linked to mode coupling.

Findings

Mutations restricting GR activity correlate with nonlinear dynamic hotspots.

Nonlinear effects are essential for understanding protein functionality.

The method predicts functional sites based on nonlinear contributions.

Abstract

Nonlinear effects in protein dynamics are expected to play role in function, particularly of allosteric nature, by facilitating energy transfer between vibrational modes. A recently proposed method focusing on the non-Gaussian shape of the population near equilibrium projects this information onto real space in order to identify the aminoacids relevant to function. We here apply this method to three ancestral proteins in glucocorticoid receptor (GR) family and show that the mutations that restrict functional activity during GR evolution correlate significantly with locations that are highlighted by the nonlinear contribution to the near-native configurational distribution. Our findings demonstrate that nonlinear effects are not only indispensible for understanding functionality in proteins, but they can also be harnessed into a predictive tool for functional site determination.