Identification of a Possible Secondary Picrotoxin ... - ACS Publications

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Identification of a Possible Secondary Picrotoxin-Binding Site on the GABAA Receptor Timothy S. Carpenter, Edmond Y. Lau, and Felice C. Lightstone* Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States S Supporting Information *

ABSTRACT: The type A GABA receptors (GABARs) are ligand-gated ion channels (LGICs) found in the brain and are the major inhibitory neurotransmitter receptors. Upon binding of an agonist, the GABAR opens and increases the intraneuronal concentration of chloride ions, thus hyperpolarizing the cell and inhibiting the transmission of the nerve action potential. GABARs also contain many other modulatory binding pockets that differ from the agonist-binding site. The composition of the GABAR subunits can alter the properties of these modulatory sites. Picrotoxin is a noncompetitive antagonist for LGICs, and by inhibiting GABAR, picrotoxin can cause overstimulation and induce convulsions. We use addition of picrotoxin to probe the characteristics and possible mechanism of an additional modulatory pocket located at the interface between the ligand-binding domain and the transmembrane domain of the GABAR. Picrotoxin is widely regarded as a pore-blocking agent that acts at the cytoplasmic end of the channel. However, there are also data to suggest that there may be an additional, secondary binding site for picrotoxin. Through homology modeling, molecular docking, and molecular dynamics simulations, we show that binding of picrotoxin to this interface pocket correlates with these data, and negative modulation occurs at the pocket via a kinking of the pore-lining helices into a more closed orientation.

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INTRODUCTION GABARs [γ-aminobutyric acid (GABA) type A receptors] are chloride ion channels that are opened by the binding of GABA. These receptors contain many distinct binding regions, pockets, and clefts and thus can also be modulated by a variety of pharmacologically important drugs, such as benzodiazepines (e.g., diazepam) and anesthetics (e.g., halothane). Other regularly abused drugs (e.g., ethanol) along with insecticides (e.g., dieldrin) also affect the activity of GABARs. GABARs are found in the brain and are the major inhibitory neurotransmitter receptors. They are part of the Cys-loop receptors1 in the ligand-gated ion channel (LGIC) superfamily. Upon binding of an agonist, the GABAR opens and increases the intraneuronal concentration of chloride ions, thus hyperpolarizing the cell2,3 and inhibiting the transmission of the nerve action potential. GABARs are heteropentameric receptors, with the five subunits combining to form an ion channel through the membrane. Each monomer has three domains: the extracellular ligand-binding domain (LBD), the four-helix transmembrane (TM) domain, and a cytoplasmic domain formed by the region between helices 3 and 4. GABAR subunits are drawn from a pool of 19 distinct gene products (α1−6, β1−4, γ1−3, δ, ε, π, and ρ1−3). Most agree that the α1β2γ2 receptor is the most common subtype.4−7 The δ-containing GABAR subtypes are known to be the most highly GABA (and ethanol) sensitive8 but make up only 5−10% of the total GABARs in the brain.9 Historically, many of the early discoveries about the functions, behaviors, and ligand interactions of GABARs were © 2013 American Chemical Society

found through their exposure to and behavioral modification by the plant-derived toxin picrotoxinin (PTX).10,11 PTX is still used as a tool to probe the behavior of GABARs.12 PTX inhibits chloride flux through GABARs13 and is used as a typical example of a GABAR noncompetitive antagonist (NCA). For a GABAR to display NCA sensitivity, a β-subunit14,15 is required. The artificial, nonphysiological β3 homopentamer has a higher NCA sensitivity than any other GABAR combination.16 Surprisingly, the highly homologous β1 and β2 are relatively insensitive to NCAs, with β1 displaying little or no activity unless it is expressed with other subunits.14,17,18 The majority of experimental and structural evidence shows PTX acts as a channel blocker with a binding site at the intracellular end of the pore at residues 2′−6′ of the GABAR M2 helix19−22 (and residues −2′ to 2′ of the structurally analogous invertebrate glutamate-gated chloride channel, GluCl).23 Here it is thought to act by a simple NCA channel blocking mechanism. By studying how PTX binding affected GABARs, Ticku et al.24 were able to characterize much about GABAR ionophore function, laying the foundations for our current detailed knowledge of the complicated GABAR system, and how binding of a ligand to different sites can modulate the behavior of the GABAR. Besides the well-defined GABA-binding cleft, several other small molecule-binding sites are present on the receptor. Binding of molecules to these sites acts to antagonize or modulate the behavior of the GABAR. Indeed, many of these Received: May 3, 2013 Published: September 12, 2013 1444

dx.doi.org/10.1021/tx400167b | Chem. Res. Toxicol. 2013, 26, 1444−1454

Chemical Research in Toxicology

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the pioneering early experimental work on GABARs by using the interactions of PTX with the receptor as a tool to learn more about GABAR functions. We identify (and validate against existing data) the binding of PTX to the interface pocket on the GABAR and determine how binding of an antagonist to the site may elicit modulation in the GABAR behavior. On the basis of physiological prevalence and behavioral profiles, two different molecular models of GABARs are used. One GABAR model contains the highly PTX sensitive β3 subunit (α6β3δ), and the other receptor contains the relatively less sensitive β2 subunit (α1β2γ2). The two different receptor subtypes not only allow comparison for PTX binding sensitivity but also provide additional controls. These two models provide differing subunit environments but also have the greatest amount of available experimental data for comparison. Thus, where possible, results are further validated through evaluation against experimental results. Our observations, resulting from binding of PTX to the interface pocket, explain the anomalous data that contradict the simple pore blocking mechanism. Furthermore, the characterization of this region and the small molecule (PTX)-induced dynamics provide a possible mechanism for general antagonism at this site.

sites require specific subunit subtypes to function, thereby creating specialization in the pharmaceutical profile of the different GABAR combinations. The use of PTX in early GABAR experiments allowed an improved understanding of the intricate coupling between these various sites on the GABARs, as well as elucidating how other ligands operate on GABARs.25 One recently proposed binding site on the GABAR is at the interface between the LBD and the TM domain (Figure 1). This region may act as a binding site for both insecticides26 and anesthetics.23 We shall subsequently refer to this site as the “interface pocket”.

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COMPUTATIONAL METHODS

Model Generation and System Setup. For this study, we used our previously published and validated GABAR models40 for the α1β2γ2 and α6β3δ receptors. The use of multiple secondary templates allowed us to more accurately model regions with lower degrees of homology to our main template. Each assembled model was inserted into a preformed and equilibrated palmitoyloleoylphosphatidylcholine (POPC) bilayer that was also used for previous GABAR simulations.40,41 The system was then solvated and had the charge neutralized via addition of counterions. Additional Na+ and Cl− ions were added to create an effective concentration of 0.15 M. The final system (protein, bilayer, water and ions comprising a total of ∼210000 atoms) was energy minimized to remove unfavorable interactions and/ or steric clashes. The bilayer and water were equilibrated for 1 ns while positional restraints were implemented on the protein to allow the relaxation of the lipid and water molecules around it. Only a short relaxation time was required because of the extensive pre-equilibration of the membrane itself, and the fact that the lipids has already been relaxed around a very similar protein. The area per lipid was monitored to ensure the values remained within measured values. The positional restraints were subsequently removed, and the systems were equilibrated for 2 ns. Each system was also run in an apo state for a further 20 ns to generate additional starting conformations for each receptor to increase the sampling for our small molecule docking. This resulted in four initial protein systems (two α1β2γ2 receptor conformations and two α6β3δ receptor conformations) to which PTX was docked. Docking Protocol. The PTX molecules had Gasteiger charges calculated and added using Autodock Tools.42 The protein had the nonpolar hydrogens merged into the heavy atoms for the Kollman united atom set force field43 and adding Kollman charges and Stouten desolvation terms for each atom. The rotatable bonds of PTX were also defined, to ensure the different possible conformations are sampled during the docking process. The region of the receptors selected for the docking protocol encapsulated the entire TM domain, and the lower part of the extracellular LBDs. This region was chosen to cover the vast majority of residues experimentally identified to influence and/or be influenced by PTX binding. Thus, the amount of literature data has been maximized as much as possible. The region was searched using a 300 × 300 × 270 point grid with 0.25 Å spacing. Autogrid was then used to calculate the potential interactions between the ligand and protein atoms for the proposed grid. Docking was performed using Autodock 4.44 All torsions were allowed for the

Figure 1. Secondary binding site of PTX and residues making numerous contacts with the ligand. (A) The binding regions (containing residues that make contacts with PTX) are colored yellow. They consist of extracellular sections of all four TM helices, the M2−M3 helix loop, and the Cys loop. These values are averages taken from all the simulation data. (B) Average contact data for only the αsubunits. (C) Average contact data for only the β-subunits.

There are some PTX effects that cannot quite be explained by this simple NCA channel block mechanism,27,28 leading to speculation about an additional, minor site of action. Specifically, PTX induces conformational changes in regions of the protein that are distal to the main PTX-binding site.12,29−31 Additionally, the fact that with increasing PTX concentrations there is a finite maximal level of inhibition indicates that it may not be acting solely by a pore occluding mechanism.32 Studies have demonstrated that antagonism by PTX may also have an allosteric, non-steric-blocking component,13,33,34 and that PTX blockage of the GABAR current is mediated by two different mechanisms.35 Theories suggest that this secondary allosteric, inhibitory site may weaken the channel opening equilibrium,28 stabilize a nonconducting (closed or desensitized) state of the receptor,13,32,34,36,37 or negatively modulate channel gating to actually facilitate channel closing.29−31 Data have indicated that this site is located toward the extracellular end of the channel (possibly involving residues 15′ and 17′)12,22,35,38 and may be lipophilic in nature.39 While we acknowledge that the major PTX-binding site exists in the channel pore (our findings also indicate the same), we attempt to characterize a secondary site on the GABAR that may also be modulated by PTX binding. As such, we have conducted computational modeling and simulations that mirror 1445



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ligands as part of a flexible Lamarckian genetic algorithm (LGA)-based docking routine, with 100 GA runs conducted. The protein model was maintained as a rigid structure during the docking protocol. Modes of binding were separated with a 3 Å root-mean-square deviation (rmsd) cutoff. The final docking conformations were selected from those that were most appropriate and had the lowest-energy structure. Following equilibration and ligand docking, the four ligand-bound systems (and their corresponding apo control simulations) were run for 20 ns each, totaling 160 ns. A further control was run in which PTX was just docked to the central pore of each system. These four, single-PTX pore-bound control simulations were also run for 20 ns each, totaling 80 ns. POPC Partitioning Simulation. A simulation was conducted to investigate the depth of partitioning of PTX into a POPC bilayer. A POPC bilayer patch was solvated and equilibrated for 10 ns. Following this, 24 PTX molecules were added into the bulk water at random positions and orientations. This resulting system with PTX present was then simulated for a further 40 ns to observe the equilibration position of the PTX molecules. Simulation Details. All simulations were run using the CHARMM v27 force field45 in NAMD46 with a nonbonded van der Waals cutoff of 12 Å. Production runs were conducted at constant pressure and temperature (NPT). A constant pressure was maintained with a Langevin piston set at 1 atm. A Langevin temperature piston was set at 310 K to maintain a constant temperature, and particle mesh Ewald electrostatics were applied. All simulations were run with SHAKE47 and a 2 fs time step. TIP3P water48 was used. All MD runs were conducted on either the Atlas or Zeus machines at the Livermore Computing Center (Atlas and Zeus are 9216 and 2304 processor AMD Opteron machines, respectively). Using VMD,49 Gromacs,50 and locally written scripts, images were prepared and analysis was done.

Figure 2. PTX-induced kinking of the M2 helices. The M2 helix is divided up into four sections, and the angle between adjacent sections is calculated. The angles measured for the PTX-bound simulations are compared to those measured for the apo simulations to illustrate how the presence of PTX influences the kinking of the M2 helices. While no change in helix kink angle is observed for the α1β2 receptor M2 helices (A), the α6β3 receptor M2 helices undergo kinking toward the C-terminal end of the helices (B).

The reagent reaction rates from substituted cysteine accessibility methods (SCAMs) give a measure of how accessible a residue is to the solvent. We are able to measure the average percentage solvent accessible surface area (SASA) for each residue in M2 (Figures 3D and 4) during our simulations. This reveals a pattern similar to that from SCAM experiments.52 In agreement with general pore trends seen in the recent GluCl23 and GLIC53 structures, these SASAs also indicate that the pore becomes wider toward the extracellular or C-terminal end (Figure 4A). When these data are normalized and illustrated on a representation of the M2 pentamer, the most accessible residues are clearly located on the channel-facing sides of the helices (Figure 4B), in excellent agreement with an equivalent representation compiled from previous experimental data (Figure S1 of the Supporting Information).52,54,55 Thus, several different methods from different groups agree with the calculations from our simulations, which confirms that the structure of our model is biologically relevant. The control docking studies identify the well-established channel-blocking site in the pore of all four models (α1β2γ2 at 2 ns, α6β3δ at 2 ns, α1β2γ2 at 20 ns, and α6β3δ at 20 ns). The binding region identified is consistent with existing experimental work and agrees well with the recent electron density found for PTX in the analogous LGIC GluCl crystal structure23 (Figure S2 of the Supporting Information), with approximately one-third of all β-subunit contacts made to the critical 6′ THR. Thus, with our docking protocol able to determine the established channel-blocking site, we have confidence in the reliability of the docking to the interface pocket. Subunit Specific Ligand-Binding Sites. After our models and docking protocol have been validated, the interface pocket is first characterized by determining if there is any subunit specificity associated with binding. The potential interfacebinding pocket is consistently identified in different models by the ligand docking protocol. This pocket is located at the interface between the TM domain and the LBD and is lined by residues from the Cys loop, the top of the M1 helix, the M2− M3 loop, and the top of the M4 helix (Figure 1). This binding pocket is found within seven of the eight α-subunits, four of the eight β-subunits, and all of the δ/γ-subunits (Figure S3 of the Supporting Information). For our analysis, the δ/γ-subunits are ignored (as there are fewer data for comparison between these subunits), and the results are calculated using the interactions

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RESULTS Validation of Models and Docking Protocol. Before the docking results and subsequent simulations are examined in detail, we validate our systems in two areas. First, both the structural and dynamic behavior of our models is compared to existing experimental data to ensure they are representative of the physiological state of the receptor. Second, our docking protocol is ratified by control docking to the well-established PTX pore-binding site, followed by subsequent simulation and analysis. The apo models are validated by evaluation against experimental data to ensure they are structurally accurate. This is of vital importance, as our models have a relatively low level of sequence homology to our template structures. Initial observations (Figure 2) determined that the extracellular, Cterminal end of the M2 helix is the primary region that displays major PTX-induced changes. Thus, structural experimental validation is especially key in this region. Experimental data available for this region of the GABARs are compared to equivalent measurements calculated from our simulations. The residue−residue distances between the equivalent residues of neighboring helices are found to match the trend observed for a GABAR β3-homopentamer51 (Figure 3A). These published data further indicate that in the β3-homopentamer the M2 “helix” does indeed possess α-helix-like structure up to residue 16′ but is actually more β-like in structure after residue 16′ (Figure 3B). The percent α-helicity of the four TM regions throughout all the apo control simulations show that for the αsubunits, the four TM regions maintain an almost 100% helical structure throughout the simulations (Figure 3C). However, the β-subunits display a marked decrease in helicity in the extracellular third of the M2 helix, which corresponds to a region similar to the experimentally calculated “β-like” section. 1446



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Figure 3. Experimental validation of the structure of the TM M2 helix. (A) Chen et al.51 calculated the M2 residue−residue distances using cysteine substitution and cross-linking of the β3-homopentamer. They obtained values for only residues 13′−20′ (red line). The equivalent distances are averaged over the course of our apo simulations (black line). (B) Visual representation of the secondary structure of the M2 region as measured by Chen et al.51 (C) α-Helical contents of the four TM regions of the α-subunits (red) and β-subunits (orange) averaged over the apo simulations. (D) Available (residues 19′−21′ and 24′−27′) C-terminal M2 residue MTSET+ (methanethiosulfonate-ethyltrimethylammonium) reaction rates (as a measure of residue accessibility) are plotted in gray.52 Calculated average solvent accessible surface areas (SASAs) for the apo simulations (an equivalent measure of residue accessibility) are plotted in black.

Figure 4. Solvent accessible surface areas (SASAs) of M2 residues. (A) The average percentage SASA is measured for the apo M2 residues. The probe used replicates the size of a water molecule. These values are normalized, attributed to a green → red color scale and assembled onto a helix wheel. Five of these helix wheels were arranged in a pentameric manner to reveal the alignment of the residues (B). The positions of these residues match the predictions from experimental data (see Figure S1 of the Supporting Information).

of PTX with the α- and β-subunits. Thus, each model has three or four PTX molecules docked to it at the same relative pocket in each subunit. The only differences in these systems are the compositions of those subunits. These 11 PTX−α/β-subunit interactions total 220 ns of contact data. The first 5 ns of each simulation is ignored as the time it takes to equilibrate the system. The rmsds for all the simulations (PTX-bound and apo) plateau after ∼10 ns to average values of ∼4.5 and 4.8 Å for the apo α6β3δ and α1β2γ2 systems, respectively (Figure S4 of the Supporting Information). The average plateau values for the PTX-bound α6β3δ and α1β2γ2 systems are ∼3.5 and 4.2 Å, respectively. This indicates that the presence of PTX stabilizes both the α6β3δ and α1β2γ2 receptors but appears to have a stronger effect on the β3-containing α6β3δ receptor subtype. During each of the 20 ns simulations, all of the PTX molecules remain bound within the interface pockets, except for one located in the α1-subunit, which drifts out of the binding site after ∼15 ns. The contact data are analyzed to examine both the overall trend for the PTX−protein interactions with all of the α/β-subunits (Figure 1A) and the differences between the α- and β-subunits (Figure 1B,C). The averaged PTX−protein contacts consist of residues from the

top of all four TM helices, as well as the Cys loop. The residues within these regions that make the most consistent contacts with PTX are tyrosines (Y284, Y445, and Y446) and threonine (T225). These residues both pack the aromatic rings against PTX and make specific hydrogen bonds to the oxygens of PTX. This binding characteristic is similar to the ring of threonine residues (T6′) that form the binding site within the pore of the channel.19 Furthermore, this site is in the vicinity of the Glu55Arg216 ion pair. The equivalents of these residues in GABACR directly influence PTX binding.56 GABACRs possess the same architecture as GABAARs but are homopentamers composed of five ρ-subunits. Clear differences exist between the PTX−α-subunit contact pattern (Figure 1B) and the PTX−β-subunit contact pattern (Figure 1C). The average root-mean-square fluctuation (rmsf) of the PTX molecules in the α-pocket is 2.28 Å, compared to only 1.68 Å for the PTX molecules in the β-pocket. Furthermore, the PTX molecules contact 50 different residues in the α-subunits with an average of contacting each residue for just 18% of the simulation time. By contrast, only 27 different residues in the β-subunit are contacted by PTX with an average of 37%. Thus, in the β-subunit, the position of PTX fluctuates less and contacts fewer, more specific residues for a longer 1447



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Figure 5. Distortion of the PTX-bound M2 helix residues relative to the apo simulations. The rmsd of each residue in the PTX-bound M2 helix is calculated relative to its apo equivalent and is shown with respect to time. The residues are colored on a “rainbow” scale from residue 2′ to 27′. The average deviation of each residue over the last 10 ns is also represented on a blue to red color scale on the M2 pentameric bundle. This is calculated separately for the α1β2 (A) and α6β3 (B) receptors.

period of time, showing that PTX has a higher specificity for the β-subunit pocket. PTX-Induced Distortions. Having established that it is the β-subunits that appear to have a more sensitive interface pocket, we examine what distortions take place upon PTX binding. As previously mentioned, the extracellular C-terminal end of the M2 helix exhibits the major differences between the apo and PTX-bound simulations (Figure 2). The rmsds of the Cα atom of each M2 residue of the PTX-bound simulations relative to the apo simulations show that the α1β2 receptor M2 helices do not deviate greatly upon the addition of PTX, with just some fluctuations over time (Figure 5A). However, the α6β3 receptor M2 helices show a distortion in the region of residues 15′−20′ (Figure 5B), a previously identified “flexible area”,51,55 immediately adjacent to the PTX-binding pocket. These distortions increase as the simulation progresses. For both subunit subtypes, little or no deviation at the M2 Nterminus is observed in the vicinity of the PTX channelblocking region. Characterization of M2 Helix Distortions. After determining that the C-terminal end of the M2 helix was undergoing PTX-induced distortions, we characterized those distortions. Initial angle measurements reveal that the M2 helix kinks in this region when PTX is introduced (Figure 2). The average kink increase for all subunits in the α6β3 receptor is ∼11°, and almost 15° for only the β3-subunits (data not shown). However, only minor deviations of 2−3° are observed for the α1β2 receptor subunits. Furthermore, this kinking of the M2 helices is not observed in either receptor for the control simulations in which PTX was just docked to the intracellular region of the pore (Figure S5 of the Supporting Information). In an attempt to further quantify this helix kinking and relate the structure back to earlier experimental validation (Figure 3A), the residue−residue distances between helices are measured. These distances indicate that the helix kinking causes this C-terminal segment of the helices to move closer together (Figure 6). These observations lead us to the hypothesis that in the α6β3 receptor model, PTX causes the helices to kink and/or bend toward the center of the pore. Thus, the change in SASA of the residues along the entire length of the α6β3 receptor M2 helix was calculated (Figure 7A). SASA was chosen because this is a variable that can be validated by experimental comparison. If the C-terminal sections of the helices are moving slightly toward each other into the center of the pore, one would expect the SASA of these pore-facing residues to decrease. The percentage change in SASA indicates that only residues in the

Figure 6. Effect of PTX on M2 helix residue−residue distance. (A) The residue−residue distances for the M2 helix are calculated for the apo (gray) and PTX-bound simulations (black). These results are also represented as a percentage change in the residue−residue distance of the PTX-bound simulations relative to apo simulations (B).

C-terminal half of the helix undergo noteworthy deviation from their apo values. Several residues in the C-terminal half of the M2 helix have their SASA reduced by up to 10%. These SASA results were converted to a color scale and illustrated on a representation of the M2 pentamer (Figure 7B). With the data presented in this fashion, one can see that the residues undergoing SASA reduction (becoming less solvent accessible) are indeed the ones that are oriented toward the pore of the channel. This result supports the hypothesis that the presence of PTX causes the C-terminal ends of the α6β3 receptor M2 helices to bend toward the center of the pore and narrows the channel. The average pore radius during the last 10 ns of the PTX and apo α6β3 receptor simulations also confirms the narrowing of the channel. Figure 8 shows that the only significant change in the profile of the ion channel is a narrowing of the pore at the extracellular, C-terminal end of the M2 helix (in the vicinity of where PTX was docked). This trend is not observed for either the equivalent α1β2 receptor simulations (Figure S6A of the Supporting Information) or the two control pore-bound PTX systems (Figure S6B,C of the Supporting Information). If we compare all the dynamic criteria measured for the M2 helices in our simulations, namely, residue−residue distances, residue−residue contacts, and SASAs (Figure 9), all the deviations in helix behavior originate at residue 15′. There are relatively few helix changes that occur in the N-terminal half of the helix before residue 15′, whereas the majority of helix changes occur in the C-terminal half of the helix after residue 15′. Thus, residue 15′ seemingly acts as a “hinge” point for the helix. 1448



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Figure 7. Change in SASA upon PTX binding. The percent SASA change upon the addition of PTX is calculated (A). These SASA deviations are used to construct another pentameric helix wheel diagram to illustrate the orientation of the residues that underwent the largest changes (B). The red,67 blue,65 and pink66 circles highlighting residues in panels A and B represent experimental results that found either no change (blue) or a decrease in residue accessibility (red and pink) upon PTX binding.

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DISCUSSION Through molecular modeling, docking, and biomolecular simulation, we have characterized a modulatory site on the GABAA receptor using the binding of PTX as an analysis tool. To validate our hypotheses about the behavior of this pocket and its potential mechanism of inhibition, we have, where possible, explicitly related our findings to previous experimental results. First, we compared our results against structural information and then against available dynamical data. We then finally attempted to use our observed PTX-induced dynamics to rationalize experimental evidence that has long been unaccounted for by a simple pore blocking model for PTX action. Validation of Structural Data. Our initial models have had specific criteria measured (Figure 3) that can be directly compared to experimental values of the conformation of the M2 helix region.51,52 These comparisons match the residue− residue distances between neighboring M2 helices, their relative helical secondary structure,51 and the associated periodicity of residue accessibility.52 Thus, our model is comparable to what is seen experimentally. The “interface pocket” binding site is equivalent to one of the previously proposed cavities for insecticides.26 Furthermore, this identified site is also homologous to the binding pocket in GLIC in which inhibitory anesthetics were recently crystallized.57 Thus, this pocket may represent a negative allosteric site in the LGIC family. The binding site is located at the interface of the LBD/TM regions and is fully accessible from the membrane, agreeing with the idea of an additional “lipophilic site” from which PTX may operate.39 Many additional modulators of GABARs are lipophilic in nature and bind in the TM region. For example, anesthetics follow the Meyer−Overton correlation that more lipophilic compounds are more potent anesthetics. Furthermore, the potency of neurosteroids is suggested to be linked to their lipophilicity. By accumulating in the membrane where TM-binding sites are easily accessible, neurosteroids do not need to be high-affinity binders.58,59 To test this accessibility hypothesis, simulations were conducted to determine whether PTX partitions into a POPC bilayer, and to what depth it partitions. A POPC bilayer patch was solvated, and 24 PTX molecules were randomly added to the bulk water. After 20 ns of simulation, all the PTX molecules partition into the bilayer and maintain a constant partitioning depth for the remaining 20

Figure 8. PTX-induced changes to the pore. The pore profile radius is calculated for the last 5 ns of the apo (black line) and PTX-bound (red line) α6β3 simulations (A). It shows that PTX induces a narrowing of the pore at the extracellular end of the M2 helix. The positions of residue 15′ and PTX (green) are also indicated. The depth of partitioning of PTX into a POPC lipid bilayer was measured from 20 ns of simulation (B). The position of PTX (red line) is just below the lipid headgroups in the lipid head/tail interface region. Positions of the lipid phosphate (bronze line) and choline (blue line) groups are also indicated.

Figure 9. Helix changes around residue 15′. The asymmetrical PTXinduced behavior of the M2 TM helix around residue 15′ is demonstrated by three different measurements. The percent change in residue−residue contacts (black circles), residue−residue distances (gray triangles), and residue SASAs (gray squares) of the PTX-bound simulations relative to those of the apo simulations show that helix changes do not occur until after residue 15′. 1449



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blocking mechanism of PTX. Thus, PTX possibly binds to a secondary site to cause these changes. The trends seen for these residues were compared to our calculated change in SASA (red, pink, and blue circles in Figure 7). Our results almost completely replicate what is observed experimentally, with four of the five measured residue accessibility changes (17′ and 19′−21′) showing that our PTX-induced changes in accessibility match the equivalent experimental findings. Q185 participates in hydrophilic interactions that help in stabilizing the closed channel conformation of the GABARs.68 However, there was no significant change in Q185 SASA measured upon PTX docking in either receptor system. Furthermore, some residues within the M2 helix appear to directly influence the antagonizing properties of PTX yet are distal from the pore-blocking site (2′−6′). For example, both residues 17′ and 19′ are thought to be involved somehow in allowing PTX access to the pore-binding site,69 and residue 19′ is involved in the transduction process between PTX binding and its mechanism of action.70 Residue 17′ is also important for PTX modulation of GABARs,55,67 and its mutation alters the GABAR sensitivity to PTX.71 These findings are curious given the lack of proximity of residues 17′ and 19′ to the PTX poreblocking site. One piece of speculation may be that despite their distal nature, they may still undergo conformational changes. However, the recent GluCl crystal structures23 show no difference at all in this region (including residues 17′ and 19′) whether PTX is bound in the pore or not (Figure S8 of the Supporting Information). We found that these two most important residues (17′ and 19′) are the two that are most influenced by PTX binding in the interface pocket. Residue 19′ has the largest decrease in residue−residue distance (Figure 6B), while residue 17′ is distorted (largest rmsd) the most of any residue (Figure 5B) and also has its accessibility reduced by the greatest amount (Figure 7A). This PTX-induced reduction in accessibility is consistent with findings that PTX binding protects residue 17′ from chemically reactive compounds.67 Thus, these two residues that are key to PTX-induced inhibition of GABARs yet are distant from the 2′−6′ binding site are heavily influenced by binding of PTX to the interface pocket. Residue 15′ has long been thought to be a key residue in the GABAR gating process,72 and its mutation can affect both anesthetics and alcohol action to potentiate GABAR responses.69,73,74 Residue 15′ is in a position where it can bind drugs directly or transduce the binding signal and may act by facilitating or hindering the tilting of M2 domains during gating.72 Indeed, evidence suggests gating is mediated by a backbone rearrangement at this midpoint.75−78 As shown in Figure 9, the dynamic behavior of the M2 helix is split by residue 15′. Residue 15′ is acting as a hinge point for the helix. The large dynamic motions only occur in the helix from residue 15′ onward. Furthermore, the importance of 15′ is highlighted by the fact that it is the only amino acid difference between the highly PTX sensitive β3-subunit (ASP) and the PTX-insensitive β1-subunit (SER). Indeed, a β1S15′N mutation will increase NCA responsiveness, while a β3N15′S mutation decreases NCA responsiveness.18 Our results reinforce the notion that residue 15′ is vital for M2 dynamics. Possible Allosteric Mechanism of Inhibition. Having established that our models are validated by both structural and dynamic data and are biologically relevant, we propose a

ns of the simulation. The simulations reveal that the partitioning depth is just below the lipid headgroups in the lipid head−tail interface region and compares very favorably with the equivalent depth of the identified interface pocketbinding site (Figure 8), suggesting that PTX may accumulate at the headgroup region of the membrane, before entering the relative low-affinity pocket. The hypothesis that TM-binding sites may not be of high affinity can also be explored by looking at MD simulations of anesthetics in the GLIC interface pocket.57 These simulations were conducted by Nury et al. (based on the crystal structure coordinates of propofol in GLIC) and show a fluctuation of ∼12 Å relative to the center of the pore, a deviation that is not expected for a high-affinity, tight binding interaction. This ∼12 Å deviation is similar to what we observed for our α6β3 PTX simulations (Figure S7 of the Supporting Information). The recent GluCl crystal structure contains PTX electron density only in the pore of the protein.23 However, because of necessary requirements for crystallization of membrane proteins, detergent molecules already occupy the entrance to the interface pocket. Thus, the question of binding of PTX to this site is not fully addressed. The presence of a crystallographic lipid in this region is also observed in the propofol/ desflurane-bound57 and ketamine-bound60 GLIC structures, as well as a buffer in the equivalent ELIC site,61 indicating that the lipophilic entrance to the pocket may be a “sticky” site. Validation of Dynamic Behavior. Experimental evidence shows that the most PTX sensitive GABAR subunit type is the β-subunit, specifically the β3-subunit.16 Similar subunit dependencies have also been reported for anesthetics,62 again with the β-subunit demonstrating a key importance.63,64 We show that the interface pockets are much more specific for PTX in the βsubunits. When in an α-subunit pocket, PTX fits only “loosely” in the pocket and “rattles” around, contacting many residues fleetingly (Figure 1B). Indeed, one molecule was observed to completely leave the pocket. By comparison, when in a βsubunit pocket, PTX remains in a more consistent orientation, contacting fewer (but more specific) residues for a longer period of time (Figure 1C). Even though the interface pocket of the β-subunits is a more specific PTX-binding site compared to other subunits, only the α6β3 receptor models (containing the β3-subunits) undergo major PTX-induced dynamics. These dynamics occur at the extracellular C-terminal end of helix M2 (Figure 5), where an increase in helix bending and/or kinking takes place (Figure 2), resulting in a narrower channel (Figure 8). Thus, in agreement with current knowledge,14,17 the interface pocket in the β3subunits is the most sensitive (to PTX, within the scope of our simulations). Further experimental data on the dynamic behavior of this region of the protein near the interface site have also been investigated. There are several experiments in which the PTXinduced changes in LGIC M2 residue accessibility have been measured.65−67 These experiments were able to identify four residues (17′ and 20′−22′) that became less accessible to reagents upon PTX binding (only data on these specific residues could be found, and thus, it does not mean that only these residues become less accessible) and one residue (19′) where the accessibility did not change upon PTX binding.65 These residues are not in the proximity of the well-defined pore-blocking site and show no difference between the apo and PTX-bound GluCl structures, and changes in their accessibility cannot be explained by the simple (steric “plugging”) channel 1450



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plausible allosteric mechanism of inhibition via binding into the interface pocket. Using various measurements, we show that binding of PTX to β3-containing GABARs causes bending of the M2 helices toward the center of the pore, thus narrowing the channel. However, could this movement be implicated in a possible inhibitory mechanism? To investigate this, we calculated the average structure of the TM helices of all the β3-subunits during the PTX-bound simulations and their equivalent apo controls. These structures are averaged over the whole simulation and normalized for random motions, so any conformational changes indicate a significant movement of the protein. These structures are compared to the available structural data of the closed ELIC and open GLIC prokaryotic LGICs (Figure 10), Protein Data Bank (PDB)79 entries 2VL080 and 3EHZ,81

Figure 11. Effects of PTX on the dynamics of the M2 helix. The PTXinduced change in M2 residue SASA are calculated from simulations (black line) and compared to the GABA-induced change in M2 residue MTSET+ reaction rate52 (gray line). Both SASA and MTSET+ reaction rates are a measure of residue accessibility, and they show opposite trends upon agonist (GABA) and antagonist (PTX) addition.

extremely sensitive to PTX binding. Residue 19′ is a positively charged arginine that forms a highly conserved charged ring, which has been postulated to help act as a LGIC ion selectivity filter.52,82 The PTX-induced closure of this ring, while not narrowing the region to become the most narrow constriction point, may produce a more densely packed charge region and act as an electrostatic energetic barrier to ion translocation. Furthermore, again upon comparison of the GLIC/ELIC open/closed channels, the M2−M3 region of the interface pocket undergoes the largest movement during the opening dynamics (Figure S9 of the Supporting Information) and is positioned midway along the agonist-induced “conformational wave” that extends from the ligand-binding domain to the gate.83 Thus, the interface pocket may be the ideal position to throw a large molecular “spanner in the works” to slow channel opening. Finally, the calculated fluctuations of the PTX-bound α6β3 receptor M2 helices relative to their apo equivalents show that the C-terminal halves of the helices fluctuate less when PTX is bound (Figure S10 of the Supporting Information). Thus, this C-terminal region (in the proximity of the PTX) is stabilized by the presence of PTX. So, as well as causing the M2 helices to move to a “more closed” conformation, PTX also stabilizes them in that state. This is precisely what was proposed in previous electrophysiological studies of GABARs, that “PTX stabilizes a nonconducting (closed or desensitized) state of the GABAR following binding to an allosteric site”.13,32,34,36,37 In conclusion, we have shown that the subunit specificity of the interface pocket agrees with the existing data for PTX binding (and some anesthetic binding), and the PTX-induced dynamics we observe are consistent with previous results for which a simple pore blocking model could not account. Furthermore, we put forward a mechanism by which negative modulators may inhibit the receptor by causing closure at the extracellular end of the pore. Computer modeling and simulation is an ideal tool with which to direct experimental design in a synergistic manner. Our results for the characterization of this interface pocket, the behavior of PTX within the pocket, and the possible mechanism of antagonism provide new hypotheses that can be tested experimentally. Ultimately, the integration of these two fields of study can provide a better understanding of biological systems than either on its own.

Figure 10. Movement of the M2−M3 loop. (A) Helices M1−M3 from the closed ELIC (PDB entry 2VL0,80 blue) and open GLIC (PDB entry 3EHZ,81 red) prokaryotic channels are superimposed to illustrate the movement of the M2−M3 loop during channel closing and opening. (B) The same helices are shown for the average structure for the β3-subunits from the apo (red) and PTX-bound (blue) simulations of the α6β3 receptor, demonstrating dynamics similar to those of the ELIC/GLIC motion. However, the equivalent α6-subunit comparisons (C) do not exhibit the same movements.

respectively. The changes between the ELIC and GLIC TM regions (Figure 10A) indicate that upon channel closing, the extracellular regions of TM helices M2 and M3 (and the M2− M3 loop) undergo lateral motion and some rotation toward the pore. Similar PTX-induced conformational changes occur in the equivalent M2−M3 region of the α6β3 receptor β3-subunits, albeit of a smaller magnitude (Figure 10B). The same analysis of the α6β3 receptor α6-subunits reveals no substantial movement (Figure 10C). Thus, while GABAR agonists result in this “ratcheting” of the M2 helices away from the pore, PTX, in effect, moves them back slightly in the closed direction. This idea is reinforced by comparing the experimentally calculated GABA-induced changes in M2 residue accessibility52 with the PTX-induced changes in SASA (Figure 11). This comparison shows that almost the exact opposite trends are observed between the (agonist) GABA-induced and (antagonist) PTX-induced changes. The addition of GABA causes a residue to become more accessible, whereas the addition of PTX causes the same residue to become less accessible (Figure 11, residue 20′). These proposed dynamics can explain the findings that PTX induces a conformational change in the M2− M3 loop in the glycine receptor that is not produced by the agonist.66 Additionally, the M2 helix closure does not lead to this region becoming the narrowest part of the pore (Figure 8). However, the specific region of the helix where the pore closes the most is at residue 19′. We have shown that residue 19′ is 1451



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(7) Ernst, M., Brauchart, D., Boresch, S., and Sieghart, W. (2003) Comparative modeling of GABAA receptors: Limits, insights, future developments. Neuroscience 119, 933−943. (8) Storustovu, S. I., and Ebert, B. (2006) Pharmacological characterization of agonists at delta-containing GABAA receptors: Functional selectivity for extrasynaptic receptors is dependent on the absence of γ2. J. Pharmacol. Exp. Ther. 316, 1351−1359. (9) Nusser, Z., and Mody, I. (2002) Selective modulation of tonic and phasic inhibitions in dentate gyrus granule cells. J. Neurophysiol. 87, 2624−2628. (10) Ticku, M. K., and Olsen, R. W. (1978) Interaction of barbiturates with dihydropicrotoxinin binding sites related to the GABA receptor-ionophore system. Life Sci. 22, 1643−1651. (11) Mehta, A. K., and Ticku, M. K. (1986) Comparison of anticonvulsant effect of pentobarbital and phenobarbital against seizures induced by maximal electroshock and picrotoxin in rats. Pharmacol., Biochem. Behav. 25, 1059−1065. (12) Bali, M., and Akabas, M. H. (2007) The location of a closed channel gate in the GABAA receptor channel. J. Gen. Physiol. 129, 145−159. (13) Newland, C. F., and Cull-Candy, S. G. (1992) On the mechanism of action of picrotoxin on GABA receptor channels in dissociated sympathetic neurones of the rat. J. Physiol. 447, 191−213. (14) Ratra, G. S., Kamita, S. G., and Casida, J. E. (2001) Role of human GABAA receptor β3 subunit in insecticide toxicity. Toxicol. Appl. Pharmacol. 172, 233−240. (15) Slany, A., Zezula, J., Tretter, V., and Sieghart, W. (1995) Rat β3 subunits expressed in human embryonic kidney 293 cells form high affinity [35S]t-butylbicyclophosphorothionate binding sites modulated by several allosteric ligands of γ-aminobutyric acid type A receptors. Mol. Pharmacol. 48, 385−391. (16) Chen, L., Durkin, K. A., and Casida, J. E. (2006) Structural model for γ-aminobutyric acid receptor noncompetitive antagonist binding: Widely diverse structures fit the same site. Proc. Natl. Acad. Sci. U.S.A. 103, 5185−5190. (17) Ratra, G. S., and Casida, J. E. (2001) GABA receptor subunit composition relative to insecticide potency and selectivity. Toxicol. Lett. 122, 215−222. (18) Chen, L., Xue, L., Giacomini, K. M., and Casida, J. E. (2011) GABAA receptor open-state conformation determines non-competitive antagonist binding. Toxicol. Appl. Pharmacol. 250, 221−228. (19) Gurley, D., Amin, J., Ross, P. C., Weiss, D. S., and White, G. (1995) Point mutations in the M2 region of the α, β, or γ subunit of the GABAA channel that abolish block by picrotoxin. Recept. Channels 3, 13−20. (20) Wang, T. L., Hackam, A. S., Guggino, W. B., and Cutting, G. R. (1995) A single amino acid in γ-aminobutyric acid ρ1 receptors affects competitive and noncompetitive components of picrotoxin inhibition. Proc. Natl. Acad. Sci. U.S.A. 92, 11751−11755. (21) Zhang, D., Pan, Z.-H., Brideau, A. D., and Lipton, S. A. (1995) Cloning of a γ-aminobutyric acid type C receptor subunit in rat retina with a methionine residue critical for picrotoxin channel block. Proc. Natl. Acad. Sci. U.S.A. 92, 11756−11760. (22) Dibas, M. I., Gonzales, E. B., Das, P., Bell-Horner, C. L., and Dillon, G. H. (2002) Identification of a novel residue within the second transmembrane domain that confers use-facilitated block by picrotoxin in glycine α1 receptors. J. Biol. Chem. 277, 9112−9117. (23) Hibbs, R. E., and Gouaux, E. (2011) Principles of activation and permeation in an anion-selective Cys-loop receptor. Nature 474, 54− 60. (24) Ticku, M. K., Ban, M., and Olsen, R. W. (1978) Binding of [3H]-α-dihydropicrotoxinin, a γ-aminobutyric acid synaptic antagonist, to rat brain membranes. Mol. Pharmacol. 14, 391−402. (25) Enna, S. J., and Snyder, S. H. (1975) Properties of γaminobutyric acid (GABA) receptor binding in rat brain synaptic membrane fractions. Brain Res. 100, 81−97. (26) Law, R. J., and Lightstone, F. C. (2008) GABA receptor insecticide non-competitive antagonists may bind at allosteric modulator sites. Int. J. Neurosci. 118, 705−734.

ASSOCIATED CONTENT

S Supporting Information *

Percent SASAs for the M2 helix residues in apo simulations, density of PTX in the pore of the α6β3 receptor, distribution of PTX molecules in the various system setups, rmsd values for all the apo and PTX-bound simulations, measure of M2 helix kinking in control simulations, average pore profiles for the α1β2 systems and the control simulations, distribution of distances from PTX to the pore center, rmsds between the two GluCl (apo and PTX-bound) crystal structures, linear interpolation between the ELIC and GLIC crystal structures, and rmsfs of the PTX-bound M2 helix residues compared to apo simulations. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Telephone: (925) 423-8657. Author Contributions

T.S.C. and E.Y.L. performed the simulations and analyzed data. F.C.L. formulated the research plan and oversaw the project. Funding

We thank Laboratory Directed Research and Development 12SI-004 for funding. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC5207NA27344, LLNL-JRNL-611112. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank Livermore Institutional Grand Challenge for the computing time. ABBREVIATIONS GABA, γ-aminobutyric acid; GABAR, GABA receptor; LGIC, ligand-gated ion channel; LBD, ligand-binding domain; TMD, transmembrane domain; PTX, picrotoxinin; NCA, noncompetitive antagonist; POPC, palmitoyloleoylphosphatidylcholine; rmsd, root-mean-square deviation; rmsf, root-mean-square fluctuation; SCAM, substituted cysteine accessibility method; SASA, solvent accessible surface area

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REFERENCES

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