Publication
Journal of Molecular Biology
Paper

Dynamic Structure of Retinylidene Ligand of Rhodopsin Probed by Molecular Simulations

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Abstract

Rhodopsin is currently the only available atomic-resolution template for understanding biological functions of the G protein-coupled receptor (GPCR) family. The structural basis for the phenomenal dark state stability of 11-cis-retinal bound to rhodopsin and its ultrafast photoreaction are active topics of research. In particular, the β-ionone ring of the retinylidene inverse agonist is crucial for the activation mechanism. We analyzed a total of 23 independent, 100 ns all-atom molecular dynamics simulations of rhodopsin embedded in a lipid bilayer in the microcanonical (N,V,E) ensemble. Analysis of intramolecular fluctuations predicts hydrogen-out-of-plane (HOOP) wagging modes of retinal consistent with those found in Raman vibrational spectroscopy. We show that sampling and ergodicity of the ensemble of simulations are crucial for determining the distribution of conformers of retinal bound to rhodopsin. The polyene chain is rigidly locked into a single, twisted conformation, consistent with the function of retinal as an inverse agonist in the dark state. Most surprisingly, the β-ionone ring is mobile within its binding pocket; interactions are non-specific and the cavity is sufficiently large to enable structural heterogeneity. We find that retinal occupies two distinct conformations in the dark state, contrary to most previous assumptions. The β-ionone ring can rotate relative to the polyene chain, thereby populating both positively and negatively twisted 6-s-cis enantiomers. This result, while unexpected, strongly agrees with experimental solid-state 2H NMR spectra. Correlation analysis identifies the residues most critical to controlling mobility of retinal; we find that Trp265 moves away from the ionone ring prior to any conformational transition. Our findings reinforce how molecular dynamics simulations can challenge conventional assumptions for interpreting experimental data, especially where existing models neglect conformational fluctuations. © 2007 Elsevier Ltd. All rights reserved.