Molecular dynamics simulation analysis of structural dynamic cross correlation induced by odorant hydrogen-bonding in mouse eugenol olfactory receptor

TL;DR

This study uses molecular dynamics simulations to analyze how odorant binding induces structural dynamic cross-correlations in a mouse olfactory receptor, revealing a specific correlation transfer pathway.

Contribution

It introduces a novel MD simulation approach to study ligand-induced dynamic cross-correlations in an olfactory receptor using AI-generated structure.

Findings

Hydrogen bond to Ser113 forms within 2-4 ns during MD simulation.

The H-bond lifetime ranges from 1 to 20 ns.

Identified a correlation transfer pathway from Ser113 to Tyr291.

Abstract

Structural fluctuations and dynamic cross-correlations in the mouse eugenol olfactory receptor (Olfr73) were studied by molecular dynamics (MD) simulation to characterize the dynamic response of the protein upon ligand binding. The initial structure was generated by the artificial intelligence tool AlfaFold2 due to the current lack of experimental data. We focused on the hydrogen (H) bond of the odorant eugenol to Ser113, Asn207, and Tyr260 of the receptor protein, the importance of which has been suggested by previous experimental studies. The H-bond was not observed in docking simulations, but in subsequent MD simulations the H-bond to Ser113 was formed in 2--4 ns. The lifetime of the H-bond was in the range of 1--20 ns. On the trajectory with the most stable (20 ns) H-bond, the structural fluctuation of the $\alpha$-carbon atoms of the receptor main chain was studied by calculating the root mean square fluctuations, the dynamic cross-correlation map, and the time-dependent dynamic cross-correlation. The analysis suggested a correlation transfer pathway Ser113 $\to$ Phe182 $\to$ (Leu259 or Tyr260) $\to$ Tyr291 induced by the ligand binding with a time scale of 4--6 ns.