Retinal Conformation Changes Rhodopsin's Dynamic Ensemble

Abstract

G protein-coupled receptors are vital membrane proteins that allosterically transduce biomolecular signals across the cell membrane. However, the process by which ligand binding induces protein conformation changes is not well understood biophysically. Rhodopsin, the mammalian dim-light receptor, is a unique test case for understanding these processes because of its switch-like activity; the ligand, retinal, is bound throughout the activation cycle, switching from inverse agonist to agonist after absorbing a photon. By contrast, the ligand-free opsin is outside the activation cycle and may behave differently. We find that retinal influences rhodopsin dynamics using an ensemble of all-atom molecular dynamics simulations that in aggregate contain 100 μs of sampling. Active retinal destabilizes the inactive state of the receptor, whereas the active ensemble was more structurally homogenous. By contrast, simulations of an active-like receptor without retinal present were much more heterogeneous than those containing retinal. These results suggest allosteric processes are more complicated than a ligand inducing protein conformational changes or simply capturing a shifted ensemble as outlined in classic models of allostery.

Figure 1

Rhodopsin activation cycle. 11-cis retinal is prebound in the inactive dark-state. Absorption of a photon causes 11-cis to all-trans photoisomerization, and changes retinal from an inverse agonist to agonist. Activation then proceeds through several trappable nonequilibrium intermediates (not all shown) before reaching Metarhodopsin-I (Meta-I). Meta-I exists in equilibrium with the fully active Metarhodopsin-II (Meta-II). The retinal-rhodopsin bond is cleaved and retinal is able to leave, resulting in the apo-protein opsin. Upon rebinding of an 11-cis retinal this cycle is then ready to be repeated. To see this figure in color, go online.

Figure 2

Retinal dynamics distinguish the Meta-I and Meta-II ensembles. (a) Illustration showing rhodopsin in a lipid bilayer. The protein is shown as a rainbow colored cartoon with the N-terminus colored blue. Lipids are shown in a black/white ball-and-stick representation (note several lipids are removed for clarity). The black arrow denotes the membrane normal. The inset shows a close-up view of retinal (purple ball-and-sticks) in the binding pocket. It is covalently attached to Lys296^7.43 (orange) by a Schiff-base linked nitrogen. (b) Retinal orientations. A morphed retinal is shown colored as in (a). Its orientation was monitored using the three vectors illustrated by yellow, gray, and green arrows. Specifically, we computed the dot-product between a vector drawn from either: the C1–C5 atoms (yellow), the C9–C19 atoms (gray), or the C13–C20 atoms (green) and the membrane normal (black arrow in a). This angle was histogrammed over the entire Meta-I (blue data) or Meta-II (red data) ensemble of trajectories. The average histograms are shown below, with error bars representing the standard error. To see this figure in color, go online.

Figure 3

Dynamics of biologically distinguished structural motifs. (Center) Rhodopsin is shown as a rainbow cartoon embedded in a lipid bilayer. The bottom view shows the protein’s cytoplasmic face. (a) Illustration showing retinal (white spheres) in its binding pocket and rotamer toggle residues: Phe261^6.44 (pale yellow), Trp265^6.48 (pale violet), and Tyr268^6.51 (dark red). (b) Histograms of the population of ${\chi }_1$ torsion angles for each of the three toggle switch residues. Data is colored by the simulation ensemble. (Note: a version of this figure with error bars is depicted in Fig. S8.) (c) Close-up view of the NPxxY motif. (d) The ionic lock. Arg135^3.50 and Glu247^6.30 are shown forming a salt bridge (left) as in the inactive crystal structure (PDB ID: 1U19) or in an open conformation (right) as in the active crystal structure (PDB ID: 3PXO). (e) NPxxY motif versus ionic lock dynamics. The NPxxY RMSD from the inactive crystal structure (y axis) is shown versus the ionic lock distance (x axis). Every frame (sampled at a rate of 1 ns) is shown colored according to ensemble. To see this figure in color, go online.

Figure 4

Contact-based reaction coordinate shows opsin and Meta-I ensembles are more heterogeneous. The average transition is shown for all 24 trajectories as a function of simulation time. This value is calculated using Eq. 1, where contacts are computed on a per-residue basis using side-chain centers of mass. Data is averaged over the six independent simulations in each of the four ensembles with error bars representing the standard deviation. The single dark-state simulation from Grossfield et al. (45) is shown for reference. To see this figure in color, go online.

Figure 5

Ensemble-based principal component analysis was conducted on the transmembrane α-carbons of all 24 trajectories in aggregate, so the results depict how each simulation is projected onto the same basis set. Each of the trajectories used in this analysis is labeled according to its ensemble as shown in the key at the bottom of the figure. (a) Average projection of trajectory time course onto principal component one. Simulations are grouped by the four starting structures outlined in Table 1. Curves show the average across all six trajectories for each ensemble, with error bars showing the average of the standard deviations in each dataset, to emphasize which trajectories are more heterogeneous. (b and c) Projection onto the first two principal components. Each data point represents a structure from the ensemble of trajectories (sampled at 1 ns a piece) and colored according to ensemble. The x axis represents displacement along PC1, the y axis displacement along PC2. (b) Each ensemble is shown separately on the same scale. (c) Merged view of the result from (b). Opacity of the points shows the time evolution of each independent trajectory. To see this figure in color, go online.

Figure 6

Mapping principal components back onto structures. (a) Illustration showing PC1. The first eigenvector is projected back onto a cartoon representation of the average structure from all 24 simulations. Rhodopsin is shown as a rainbow, with blue indicating the N-terminus. Black sticks project from the c_α position in the direction of the first principal component, with a length proportional to their contribution to the motion. Transparent overlays show the Meta-II (78) (dark red) and dark-state (72) (marine) crystal structures. The top view shows rhodopsin in the plane of the membrane, the bottom view is normal to the membrane from the cytoplasmic side. (b) As in (a), except with sticks representing the second principal component of motion. To see this figure in color, go online.

Figure 7

Structure-based clustering reveals a heterogeneity of substates in opsin and Meta-I. A k-means clustering algorithm based on RMSD was used on all 24 simulations in aggregate plus the dark-state and complex counterion simulations from Grossfield et al. (45). (a) Histogram showing the raw counts for each cluster. Data is colored according to starting structure. Cluster numbering is arbitrary. (b–e) Time course of clustering data for all six simulations with the same starting structure. The color intensity represents population, which is plotted for each cluster (y axis) as a function of simulation time (x axis). The data is averaged in 50 ns windows across all six trajectories for (b) dark opsin, (c) Meta-I, (d) opsin, and (e) Meta-II. To see this figure in color, go online.