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. 2010 Apr 6;107(14):6275-80.
doi: 10.1073/pnas.1001832107. Epub 2010 Mar 22.

One-microsecond molecular dynamics simulation of channel gating in a nicotinic receptor homologue

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One-microsecond molecular dynamics simulation of channel gating in a nicotinic receptor homologue

Hugues Nury et al. Proc Natl Acad Sci U S A. .

Abstract

Recently discovered bacterial homologues of eukaryotic pentameric ligand-gated ion channels, such as the Gloeobacter violaceus receptor (GLIC), are increasingly used as structural and functional models of signal transduction in the nervous system. Here we present a one-microsecond-long molecular dynamics simulation of the GLIC channel pH stimulated gating mechanism. The crystal structure of GLIC obtained at acidic pH in an open-channel form is equilibrated in a membrane environment and then instantly set to neutral pH. The simulation shows a channel closure that rapidly takes place at the level of the hydrophobic furrow and a progressively increasing quaternary twist. Two major events are captured during the simulation. They are initiated by local but large fluctuations in the pore, taking place at the top of the M2 helix, followed by a global tertiary relaxation. The two-step transition of the first subunit starts within the first 50 ns of the simulation and is followed at 450 ns by its immediate neighbor in the pentamer, which proceeds with a similar scenario. This observation suggests a possible two-step domino-like tertiary mechanism that takes place between adjacent subunits. In addition, the dynamical properties of GLIC described here offer an interpretation of the paradoxical properties of a permeable A13'F mutant whose crystal structure determined at 3.15 A shows a pore too narrow to conduct ions.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Fig. 1.
Fig. 1.
Schematic representation of the simulation protocol. Starting from the crystal structure at pH 4.6, a brief equilibration is carried out (step a, 20 ns). Then, an instantaneous change in pH (step b) is made (Fig. S1a and Table S1), followed by the relaxation towards a closed conformation (step c, 1.06 μs). Only results from step c are discussed in this work. The curves with broken and plain lines represent energy landscapes for pH 4.6 and 7.0, respectively. Cross-sections of the channel illustrate each state involved in this scheme: an equilibrated open state at pH 4.6, an open state at pH 7 (simulation at 0 μs), and a state at pH 7 (simulation at 1.06 μs) on the way to the closed conformation. The protein’s surface is represented in light blue with residues changing charge during the pH jump in red. The protein’s cross-section is shown in black. The approximate position of the membrane is indicated by a gray rectangle.
Fig. 2.
Fig. 2.
Pore radius. (A) Side and top views of GLIC M2 helices are shown for the start (Top) and end (Bottom) of the simulation; side chains facing the pore are depicted. Hydrophobic, polar, and negative residues are colored yellow, blue, and red, respectively. In the side view, only two subunits are shown, including the S5 subunit with a particular motion towards the channel axis resulting in partial unwinding at its top. The channel pathway is represented as a mesh. The central panel shows the pore radius along the channel axis for the GLIC crystal structure (Black, Broken Line) and for several stretches of the molecular dynamics simulation. The simulation results are averages over 20-ns windows, starting at 0.0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06 (blue to orange) and at 1.04 μs (red). Standard deviations are shown as error bars for the 0.0- and 1.04-μs windows. The radii of Na+ and K+ ions liganded in a protein environment are indicated. (B) Pore structure of the A13′F mutant, whose crystal structure was solved at 3.15 Å resolution. Same views as above with the density from initial Fourier difference maps contoured at 4σ represented as green mesh around the mutated A13′F position. The primed residue numbers are a common numbering scheme for all cys-loop receptors in the M2 helices, starting at its cytosolic end. GLIC’s V225 is V1′.
Fig. 3.
Fig. 3.
Quaternary changes. (A) Top view of the principal axes of inertia for TMD helices M1–M4 of each subunit (colored in blue, red, green, and orange, respectively) at the end of the simulation. The principal axes at the start of the simulation are superposed in lighter colors. The number of each subunit is indicated with colors red, green, blue, orange, and magenta for S1–S5, respectively. (B) Same view as in A for the ECDs shown in dark blue. (C) Theta twist angle in successive z slabs normal to the membrane. The snapshot on the left is a side view of subunit S1. The indicated twist direction corresponds to positive (Bottom) and negative (Top) theta angles, respectively. On the right, time evolution is provided by superposition of averages on successive 0.2-μs windows.
Fig. 4.
Fig. 4.
M2 helix movement analysis. (A) Stereographic projections of polar δ and azimuthal θ angles of the M2 helix principal axis of inertia in each subunit (same subunit color code as in Fig. 3). Red dots represent initial positions. Lines depict the trajectory between average orientations at 0.1-μs intervals. The sampling of the angle space of each subunit is represented by covariance ellipsoids centered on mean positions (see Full Methods). The fraction of time spent in each cluster (normalized to 1) is indicated. (B1) Exploration of A, B, C, and D clusters along the simulation, for each subunit, using the same color code as in A. (B2) Subunit rmsd is calculated as compared to the beginning of the simulation. Curves are smoothed for clarity, with an example of the raw curve given for subunit 4. (C1) Normalized solvent accessible surface areas for the M2 helices determined for the crystal structure (Black Line), averaged over subunits S1–S4 (Green Line), and for subunit S5 (Purple Line). The top C1 panel displays the average accessible areas for the start of the simulation (0–0.1 μs); the bottom C2 panel shows the averages over 0.96–1.06 μs. (C3) Comparison of solvent accessibility changes between MD simulation data and substituted cysteine accessibility method (SCAM) measurements. The MD result for each residue was obtained by calculating the difference between the mean normalized SASA of S1–S5 over the last 100 ns and the crystal structure. The displayed SCAM results are -0.05 ln(k + /k - ), where k+ and k- are second-order rate constants in the presence and absence of acetylcholine, respectively (26).

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