A Pore-Facing Glycan Determines GABAA Receptor Subunit Stoichiometry and Gating Behavior | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A Pore-Facing Glycan Determines GABAA Receptor Subunit Stoichiometry and Gating Behavior Jing Li, Amin Akbari Ahangar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7743743/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted You are reading this latest preprint version Abstract The assembly and gating of γ-aminobutyric acid type A receptors (GABA A Rs) are tightly regulated by their hetero-pentameric subunit composition, yet the molecular determinants governing the pentameric form remain elusive. Here, we demonstrate that a conserved N -linked glycan on α subunits, uniquely positioned within the central pore of the extracellular domain, acts as a structural gatekeeper limiting α subunit incorporation. Using a total of 28 µs of molecular dynamics simulations across native and putative GABA A Rs assemblies, we show that introducing a third pore-facing glycan or positioning two glycans on adjacent subunits disrupts key interfacial salt bridges and hydrogen bonds, particularly at the β+/α– interface that hosts the GABA binding site. These disruptions propagate allosterically, reduce internal loop flexibility, and alter extracellular-to-transmembrane domain coupling, ultimately leading to deep closure of the activation and desensitization gates in the transmembrane domain. Systems containing three glycans consistently shift toward dehydrated, non-conductive conformations. In contrast, native form with two pore-facing glycans preserved native interfacial networks and pore radius. Our findings provide a mechanistic insight for the long-observed α-limiting assembly pattern and identify glycan-mediated steric hindrance as a critical factor of receptor gating. These insights bridge evolutionary conservation, N -glycosylation, and dynamic structure-function relationships, highlighting pore-facing glycosylation as a key determinant of GABA A Rs architecture and function. Biological sciences/Biophysics/Computational biophysics Biological sciences/Biophysics/Permeation and transport Biological sciences/Chemical biology/Glycobiology GABAA receptor pentameric ligand-gated ion channel N-glycosylation hetero oligomeric complexes molecular dynamics simulation neurotransmitter Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 INTRODUCTION γ-Aminobutyric acid type A receptors (GABA A Rs) are integral to the central nervous system (CNS), functioning as chloride ion-selective channels that mediate inhibitory neurotransmission 1 – 5 . These GABA A Rs play critical roles in modulating neuronal inhibition, synaptic plasticity, and homeostatic control 6 , 7 . GABA A Rs dysfunction has been implicated in a wide range of neurological and psychiatric disorders, including epilepsy, schizophrenia, anxiety disorders, depression, and substance abuse 4 , 8 – 14 . As pentameric ligand-gated ion channels (pLGICs), GABA A Rs assemble into pentamers from a diverse pool of 19 subunits (α1–6, β1–3, γ1–3, ρ1–3, δ, ε, π, and θ) 4,15,16 . Each subunit comprises a bulky extracellular domain (ECD) that forms the orthosteric binding sites for GABA and other ligands and four transmembrane helices that constitute the transmembrane domain (TMD), wherein the activation gate and desensitization gates of the channel are located 17 – 20 . Although the extensive repertoire of subunits could lead to a theoretical array of ~ 490,000 possible pentameric combinations, only a limited number of assemblies are observed in vivo 21 , 22 . Among the possible compositions, the αβγ is identified as the most predominant GABA A Rs assembly in the brain 21 , 23 . For instance, over 60% of synaptic GABA A Rs are composed of the α1β2γ2 subunit composition 6 , 18 , 21 , 23 , 24 while the α2β3γ2 isoform accounts approximately 13% of the total GABA A Rs population 11 . Overall, the β-α-β-α-γ is believed to be the most abundant form of this channel 25 , 26 . The physiology and pharmacology of GABA A Rs are shaped by their pentameric subunit composition 2 – 4 , 6 , 22 , 25 , 27 , which dictates receptor trafficking, ligand binding, drug responses, gating properties, and distinct forms of neuronal inhibition or cellular signalling 3 , 9 , 22 , 25 , 28 , 29 . Different subunit combinations target receptors to specific subcellular compartments. For example, γ2-containing receptors predominantly localize to synapses, whereas δ-containing receptors are primarily extrasynaptic, mediating phasic and tonic inhibition respectively 24 . Different assemblies also form unique subunit interfaces, enabling diverse ligand/drug binding and functional responses 22 . For instance, the GABA-binding site is located at the β+/α- interface, while the histamine-binding site is situated at the β+/β- interface 22 . Another example of the significance of subunit composition is that γ2 containing GABA A Rs (e.g., α1β2γ2, α2β3γ2, α3β3γ2) are benzodiazepine-sensitive, while δ-containing receptors (e.g., α4β2δ, α6β3δ) are benzodiazepine-insensitive but highly responsive to neurosteroids like allopregnanolone 25 , 30 . The assembly rules and molecular determinants governing native GABA A Rs remain largely unknown, representing a fundamental challenge in understanding the biophysics and pharmacology of the GABA A receptors. Extensive research has been conducted to elucidate the subunit composition of GABA receptors using biochemical, electrophysiological, and structural techniques. Experiments using concatenated constructs have revealed certain assembly patterns governing receptor stoichiometry, localization, subunit-specific preferential interactions, and probable/non-probable structure compositions 26 , 31 – 33 . High-resolution cryo-EM studies have uncovered representative subunit assemblies, revealing structural differences that shape receptor function and drug-binding properties 3 , 22 , 25 , 34 – 36 . These studies have identified a number of distinct native GABA A R pentamers, including canonical and non-canonical subunit assemblies. Among all available GABA A R structures, most of these subunit assemblies follow an XαXαX assembly pattern, with no native pentamers containing more than two α subunits or two adjacent α subunits. However, the underlying mechanisms behind this puzzling phenomenon remain unclear. N -linked glycosylation of GABA A Rs has been hypothesized to affect the XαXαX assembly pattern 37 , but it has not yet been investigated as a potential molecular determinant for receptor assembly. Among post-translational modifications, N -linked glycosylation is a critical regulator of protein folding, trafficking, and function in ligand-gated ion channels 38 , 39 . In GABA A Rs, glycosylation can be seen either as pore-facing glycans or surface glycans, influencing receptor biogenesis, gating, and assembly 40 – 42 . Glycosylation of GABA A Rs are mostly emphasized for their impact on potential subunit interactions and shielding of ligand-binding sites 37 , 40 , 43 , while fewer studies have investigated whether glycosylation alters receptor subunit assembly pattern. Cryo-EM studies have characterized these important glycan structures, including a Man-8 structure at N123 in the extracellular domain (ECD) of the α subunits, positioned centrally within the receptor’s pore 22 , 34 , 37 , 44 , 45 . This pore-facing glycan is of particular interest owing to its spatial location, which is hypothesized to impact pentameric composition, structural stability, or ion permeability 37 , 45 , 46 . Interestingly, any resolved structure that involves an α homomeric structure has been subjected to extensive modifications that would disrupt the natural pore-glycosylation on α subunits 47 , 48 . Despite the glycan’s critical location, the molecular mechanisms by which pore-facing glycans affect channel composition and gating remain largely unexplored. We hypothesize that the presence of pore-facing glycans at α1N123 likely prevents the formation of pentamers with more than two α subunits or with two adjacent α subunits, due to steric clashes. This steric constraint may promote the incorporation of β and γ subunits, thereby favoring the canonical XαXαX assembly pattern. In this context, this pore-facing glycan may serve as a molecular determinant guiding subunit composition and spatial arrangement for receptor assembly. To test our hypothesis, we investigate the structural and functional implications of high-mannose glycosylation at N123 of the α1 subunit using molecular modeling and molecular dynamics (MD) simulations. Different glycosylated and non-glycosylated systems and putative assemblies of the channel were investigated. Based on the detailed analysis of MD trajectories, we characterized the impact of these structural variations on the subunit interface, their allosteric effects on TMDs, and the coupling mechanisms underlying signal propagation. MATERIAL AND METHODS Molecular Dynamics Simulation System setup : All atomic models of GABA A R were constructed (Fig. 1 ) based on the wild-type (WT) cryo-EM structure (Fig. 1 A) 44 (PDB ID: 6X3Z) with and without the pore-facing glycans. Putative assemblies of the channel were constructed by structural alignment of appropriate subunits on the cryo-EM structure using VMD’s 49,50 MultiSeq 51 . For all the MD simulations, the channel comprising different assemblies was embedded in a 115x115 Å bilayer composed of POPC lipids after the assignment of its orientation through the PPM 2.0 server 52 and solvated in 150 mM NaCl using the web service CHARMM-GUI 53 , 54 . Most residues were assigned their default protonation state at pH 7.0 based on the PROPKA3 55 prediction obtained. The GABA molecule was protonated using CHARMM Ligand Reader & Modeler 56 . The man8 structures were constructed and attached to both α1N138 residues in CHARMM-GUI Glycan Reader & Modeler 57 – 59 . Disulfide bonds were introduced at α B, D 166–180, β A, C 160 − 74, and γ E 190–204 to conserve the integral Cys-loop structure. The total number of atoms in each system was approximately 165,000. Simulation protocol The CHARMM36m force field for protein 60 – 62 , lipids 63 , ions 64 , and glycans 65 were used. Explicit water was described with the TIP3P model 66 . All the simulations were performed under constant number of particles N, pressure P, and temperature T (NPT) conditions using the Nosé−Hoover Langevin piston method to maintain the pressure at 1 atm and a Langevin thermostat to maintain the temperature at 310 K 67 . The oscillation period of the piston was set at 100 fs and the damping time scale at 50 fs. Long-range electrostatic interactions were calculated using the particle mesh Ewald algorithm 68 with a grid spacing of 1 Å. All simulations were performed under tetragonal periodic boundary conditions to the simulation box to overcome finite-size effects and mimic bulk-like properties. Long-range electrostatic interactions were calculated using the particle mesh Ewald algorithm 68 . Short-range nonbonded interactions were calculated with a cutoff of 12 Å, and the application of a smoothing decay started to take effect at 10 Å. The simulations used the SHAKE algorithm 69 to fix bond distances involving hydrogen atoms and applied hydrogen mass repartitioning 70 to reweight hydrogen atoms, allowing for a 4 fs time step for MD simulations. After 5000 steps of minimization and equilibrations for 2 ns with harmonic positional restraints (k = 1 kcal/mol/Ų), each equilibrated system was simulated for at least 2 µs using NAMD2.14 71 and NAMD3 72 on expanse or Anton3 resulting in a total simulation time of 28 µs. Trajectories were then analyzed using VMD 50 and Python scripts. Production simulations on Anton3 73 were performed under the NPT conditions using Desmond 74 with the Multigrator integrator 75 . Semi-isotropic pressure control was applied using a Monte Carlo barostat and the antithetic thermostat 75 , 76 to maintain a pressure of 1.0 atm and a temperature of 310 K. A 2.5 fs time step was used with RESPA 77 for multiple time-scale integration. Electrostatic interactions were computed using the u-series method and Midtown splines 78 , 79 . Nonbonded interactions were tapered using a force-shift scheme with a 12 Å cutoff. Analysis and Visualization Salt Bridge Network Analysis To assess the salt bridge network at the subunit interfaces, we monitored the distance between oppositely charged residues over time throughout the simulations. A salt bridge was defined as the presence of the terminal carbon atom of glutamate or aspartate side chain within 4 Å of either the terminal carbon of an arginine or the terminal nitrogen of a lysine, within a given frame. The analysis was conducted across all independent simulation runs for the same construct. The distances were standardized and averaged, and standard errors were calculated. Salt-bridge pairs were included in the comparison between systems only if the occupancy difference exceeded 10%. This strategy enabled a detailed and comprehensive assessment of inter-subunit salt bridge networks. Hydrogen Bond Analysis The hydrogen bonds at the interface were analyzed using the Hydrogen Bond module in VMD. Polar atoms (N, O, S, F) were evaluated with a distance cutoff of 3.5 Å and a donor-hydrogen-acceptor angle threshold of 20°. The occupancy of each hydrogen bond pair was calculated as the percentage of frames in which the bond was present across the simulation trajectories, averaged over all frames, and the standard error was computed on the basis of multiple independent runs. Only hydrogen bond pairs with an occupancy difference greater than 10% between systems were included in the final comparison. ECD expansion analysis Expansion of the protein's ECD was assessed by tracking the 2D (on XY plane) center of mass (COM) of the ECD for each subunit throughout each simulation trajectory using MDAnalysis 80 . For each frame, the area enclosed by these COM points was determined using the ConvexHull function in python library SciPy 81 . The resulting area values were averaged across simulation replicas and compared between different conditions to evaluate differences in ECD expansion. Internal Loop RMSD Analysis : The flexibility of internal loops was assessed by calculating the root-mean-square deviation (RMSD) of the backbone atoms for the equivalent loop in each subunit (α: residue 130–143, β: 124–137, γ: 154–167) for every frame, using the first frame as the reference. The RMSD values were averaged across trajectories and compared between different conditions to evaluate the flexibility of the internal loop. Glycan distribution analysis The distribution and orientation of glycans were measured by tracking coordinates of the Cα of each glycosylated asparagine (αN138, γN162) and the terminal mannose residue of each glycan for every frame. This approach allowed for tracking glycan movement and orientation throughout the simulations. Pore radius analysis : The pore diameter along the z-axis (vector [0,0,1]) was analyzed using the HOLE2 module 82 of the MDAnalysis package (version 2.6.1) 83 to quantify changes in pore radius. The central reference point in each simulation was determined as the collective center of mass (COM) of Cα residues forming the activation gate. The end radius for the HOLE analysis was set to 25 Å, and the pore radius at regions of interest was tracked throughout each simulation replica. Three distinct gate regions were specifically analyzed: 1) the activation gate (AG) located at position 9′ 84 , the second hydrophobic constriction site (2nd HCS), corresponding to residue α1V257, and the homologous position in other subunits, crucial for maintaining the structural integrity of the pore lining, proper packing of the channel-forming helices, and overall channel function 85 , 86 , and the desensitization gate (DG) at -2′ 84 . Water occupancy analysis Water occupancy was assessed by tracking water molecules within a 5×5 Å 2 area along the z-axis at the central pore. The position of each water molecule was determined based on the coordinates of its oxygen atom. Water distribution along the channel pore was quantified by counting water molecules within 2 Å bins along the z-axis throughout the simulation trajectory. These values were averaged across independent simulation runs. To evaluate water permeability as a proxy for channel functionality, we used a representative water molecule radius of 1.25Å 87 for cutoff, classifying regions as permeable (radius > 1.25 Å) or non-permeable (radius ≤ 1.25 Å). The number of permeable versus non-permeable pore in each region was recorded accordingly. Statistical significance was evaluated using the chi-squared test, complemented by a sensitivity test to assess robustness, using Scipy and statsmodels. Allosteric coupling analysis To characterize the allosteric coupling between the ECD and transmembrane domain (TMD), we performed dynamical network analysis using simulation trajectories. The analysis involved multiple steps, including contact map generation, network construction, and pathway extraction to identify the coupling pathway and key residues mediating structural communication within the protein. Network configuration included the protein and glycan, with hydrogen atoms excluded. Network nodes were defined as backbone Cα atoms for the protein and O5 atoms for the glycans. To avoid artificially short paths, edges between nodes representing neighboring residues (e.g., residue i and i + 1 ) were excluded to eliminate trivial correlations arising from backbone adjacency, allowing the analysis to focus on long-range communication within the system. Network analysis was executed using VMD’s NetworkView package 88 , which processed contact maps from each independent run. The shortest paths between key functional residues were extracted using suboptimal path algorithm 88 . The algorithm computed frequent residue paths, identifying highly connected residues that serve as communication hubs. The betweenness centrality of each node was computed to rank residues based on their importance in information transfer. The most frequently visited residues in each path were extracted. Residues appearing in multiple independent runs were considered conserved network hubs contributing to allosteric signaling. VMD, along with Python 89 packages Numpy 90 , Pandas 91 , and Matplotlib 92 , were used to visualize the data from all of the analyses. RESULTS Evolutionary Conservation and Specificity of the Pore-Facing Glycan in the α Subunits of GABA A Rs A survey of 85 available 3D structures of GABA A R in the PDB database (till 2025-02-22) shows the dominance of the αβγ stoichiometry (Fig. 2 ). The majority of the entries in this category take a βαβαγ configuration 22 , 34 , 36 , 44 , 45 , 93 – 97 , with recent structures highlighting the possibility of incorporating different α subunits within the same assembly 34 . Interestingly, a few structures are reported with more than two α subunits (Fig. 2 A). However, such structures undergo substantial modifications at the extracellular domain that remove native N -glycosylation sites, resulting in ECDs that differ significantly from natural α subunits. Notably, in all available structures with a native α subunits, the first few N-acetylgalactosamine (GalNAc) residues of the high mannose glycan are observed, whereas these glycans are entirely absent in the ECD-modified α homomeric assemblies or ααααγ forms. This points toward the possibility for the pore-facing glycans to hold the key to GABA A R assembly pattern. Multiple sequence alignment of human GABA A R subunits revealed that the pore-facing N -glycosylation site at α1N138, is highly conserved across all α subunits (Fig. 3 ). Positioned centrally within the ECD pore, this hallmark glycosylation site is uniquely observed in the α subunits of GABA A R (Fig. 3 ). This glycosylation sequon lies within the loop A-E linker region. Both the sequon and the loop itself show high evolutionarily conservation among different α subunits across various species (Fig. 3 C). Interestingly, the pore-facing glycan appears unique to vertebrates, including birds, fish, reptiles, and mammals, whereas more evolutionarily distant GABA A R α like subunits found in fruit flies lack the asparagine residue necessary for N -glycosylation (Fig. 3 D). Notably, this pore-facing glycosylation site is absent in any other GABA A R subunits (Fig. 3 B) and any other known member of the pLGIC superfamily (Fig. 3 D). Sequence analysis also identified a tryptophan residue (γ2W162) occupying the homologous glycosylation site in the γ2 subunit (Fig. 3 B). Phylogenetic analysis indicates closer evolutionary relatedness between γ and α subunits than other GABA A R subunit classes (Fig. 3 A), suggesting γ2W162 as a promising target for engineering a comparable pore-facing glycosylation site. Mutating γ2W162 to asparagine would introduce the sequon for N -glycosylation to attach a third glycan in the central pore without significantly altering the native channel structure. The native, mutated, and putative models to test the structural roles of pore-facing glycans Atomic models of GABA A R were constructed (Fig. 1 ) based on the WT cryo-EM structure (Fig. 1 A) 44 (PDB ID: 6X3Z) with and without the glycans (βα G βα G γ, βαβαγ). Mutation W162N was introduced at the homologous position of α1N123 on the γ2 subunit of the βα G βα G γ* G system (Fig. 1 D), to explore the channel's ability to accommodate a third glycan without significantly disrupting the native structure. Putative assemblies with three α subunits and three pore-facing glycans (βα G βα G α G , Fig. 1 E), or with two adjacent α subunits bearing glycans (βα G α G βγ,Fig. 1 F), were also constructed to probe their structural stability. Non-glycosylated counterparts (βαβαα and βααβγ) served as controls. All these putative assembly models were generated by structural alignment of equivalent subunits to the cryo-EM structure using VMD’s MultiSeq 51 . Each assembly was simulated for at least 2 µs to investigate the structural impacts of the pore-facing glycans across different pentameric configurations. The additional pore-facing glycan disrupts key native inter-subunit contacts in the ECD of βα G βα G γ* G The incorporation of the third glycan at γ E ECD in the engineered central pore in βα G βα G γ* G leads to altered glycan localization and the disruption of native inter-subunit salt bridges and hydrogen bonds. Both βα G βα G γ* G and βα G βα G γ were simulated in four independent 2-µs runs (Fig. 1 C&D). Comparison of these trajectories revealed reproducible patterns in the structural impacts of the three pore-facing glycans. Firstly, this additional glycan significantly ( p = 0.036) reduces the conformational flexibility of the glycan attached to α D in the βα G βα G γ* G (RMSF:4.14 ± 0.45) compared to the βα G βα G γ (RMSF:6.59 ± 0.93) system (SFig. 1). The flexibility of α B glycan is also reduced, but this effect is not statistically significant ( p = 0.22). The visualization of the terminal glycans shows that the additional γ E -attached glycan forces the α D -attached glycan to be concentrated at the α B - β C and β C - α D interface (Fig. 4 A), sterically repulsing those subunits away from each other. This structural rearrangement changes the native contacts at the subunit interfaces, resulting in a substantial reduction (> 10%) in native salt-bridge occupancy for most affected pairs (Fig. 4 B). This reduced salt bridge occupancy is particularly pronounced at the GABA binding site located at the β C - α D interface (Fig. 4 C), whereas the β A - α B binding site is less affected (Fig. 4 B). This result aligns with the observation that the α D -attached glycan repulse the α B - β C and β C - α D interface. Notably, several disrupted interactions, such as β A K126 - α B D90, α B K132 - β c D72, β c K126 - α D D90, and γ E K156-β A D72, are altered at nearly symmetrical locations across the subunit interfaces (Fig. 4 E). In each of these pairs, the lysine residues occupy homologous positions (Fig. 4 F), whereas the aspartates are situated in similar locations within adjacent β sheets (Fig. 3 F, Supplementary Fig. 1), in proximity to different orthosteric binding sites. Among these, two pairs (β c K126 - α D D90 and α B K132 - β c D72) near the glycan-concentrated region exhibited reduced salt-bridge occupancy, whereas the other two pairs (γ E K156 - β A D72 and β A K126 - α B D90), located away from this region showed increased salt bridge occupancy (Fig. 4 B, E). Although most disruptions occurred within the ECD subunit interface, several important changes in other key regions were observed, including α B K306 - β C E76 at the ECD-TMD interface (Supplementary Fig. 1) and α D K339 - γ E D299 within internal regions of TMD ( Supplementary Fig. 1). Subunit rearrangements were also associated with altered hydrogen bonds at subunit interfaces which clustered into three primary regions, i.e., ECD, ECD-TMD interface, and TMD. (Fig. 5 B, SFig. 2). At the ECD region, these re-arrangements were mostly observed around the discussed glycan-concentrated region, orthosteric and allosteric ligand-binding sites. At the β C –α D interface, located behind the GABA binding site (Fig. 5 A), several hydrogen bonds exhibited increased occupancy, including β C D125–α D H137 and β C T120–α D T140, whereas others, such as β C D119–α D N114, showed reduced occupancy. A similar pattern was observed at the α D –γ E interface, which comprises the benzodiazepine binding site (Fig. 5 A,E). In this region, hydrogen bonds such as α D F128–γ E H163 and α D S134–γ E T164 increased in frequency, whereas interactions including α D D125–γ E T164, α D F128–γ E H161, and α D T126–γ E T164 showed decreased occupancy. Overall, this analysis indicates that increased glycan-subunit interactions in βα G βα G γ* G drive subunits separation at the upper surface of the ECD, while promoting closer contacts among residues in the lower, internal regions and loops. Interestingly, at nearly all subunit interfaces except β A –α B , a hydrogen bond between two highly conserved threonine residues (Fig. 5 G,H) was either significantly strengthened or significantly weakened (Fig. 5 A). This threonine pair is located directly behind the orthosteric ligand-binding sites for GABA, benzodiazepine, and histamine. The second threonine in the α subunits contributes to the N -glycosylation sequon (Fig. 5 G). Thus, alterations in this conserved hydrogen bond are likely affected by the presence of glycans and may have a direct structural impact on the ECD domain. At the ECD–TMD interface, a second cluster of altered hydrogen bonds was identified, primarily involving the TM2–TM3 linkers and upper TMD regions (Supplementary Fig. 2). The most significantly affected interface in this region was γ E –β A , a potential binding site for steroid analogues and lipids (Supplementary Fig. 2). Structurally homologous positions at the propofol binding site in β A –α B , as well as β C –α D interfaces, also exhibited disruption in their upper TMD regions. A third cluster of disrupted hydrogen bonds was located at the intracellular side of the TMD adjacent to TM1–TM2 linkers, regions known to bind neurosteroids, cholesterol, and other lipids (Supplementary Fig. 2). The impact of the additional glycan extends beyond the disruption of native inter-subunit contacts. In the ECD, it also alters glycan interactions with important internal loops. Notably, the simulated pore-facing glycan of the γ subunit is positioned in close proximity to the functionally important A-E linker (Supplementary Fig. 1F), which contains the glycosylation sequon on the α subunit and is located behind the GABA binding site. RMSF analysis reveals a general decrease in loop flexibility, with the most pronounced reductions observed in the β C and γ E (SFig. 1F). This diminished internal loop flexibility provides an additional mechanism by which the third glycan may impair channel function. Presence of three pore-facing glycans in βαβαγ* lead to TMD closure at the activation gate The primary difference between the βα G βα G γ* G and βα G βα G γ systems in the TMD are at the activation gate. Tracking the pore radius along the z-axis using HOLE analysis revealed a rapid closure of the AG where the pore radius is significantly (χ² = 4717.44, p < 0.001) reduced from 1.38 Å in βα G βα G γ to 1.19 Å in βα G βα G γ* G (Fig. 6 A, B; SFig. 4). This increases the probability of channel closure (1.25 Å as the threshold) from 30.2% in βα G βα G γ to 59.8% in βα G βα G γ* G . Consistently, the βα G βα G γ system maintained a continuous water wire through the gate for nearly 43% of the simulation time, whereas in βα G βα G γ* G , this number dropped to 11% (Fig. 6 C, D). This shift toward impermeable conformations likely results from a structural transition to a resting-like or deep desensitized conformation. The hallmark of this transition is the closure of the activation gate within the TMD, occurring at the crossover of key residues: α B,D L291 β A,C L283, and γ E L313 (Fig. 6 C). Interestingly, the βα G βα G γ* G activation gate exhibited a distinct rapid-switching behavior, characterized by repeated transitions between a narrowed pore radius of ~ 1.25 Å and a fully sealed state (~ 0.6 Å) (Fig. 6 A). This two-state-like switching behavior was consistently observed across all four βα G βα G γ* G replicas. In contrast, the βα G βα G γ system predominantly maintained a pore radius above 1.25 Å. Furthermore, in a βα G βα G γ* with the same γ2W162 mutation without the glycosylation presence, the pore radius at AG remains similar (1.35 Å) to that of the βα G βα G γ system (1.38 Å) (SFig. 4), suggesting that the the observed dynamic behavior at this gate is driven by the glycan itself, rather than the mutation. Eliminating all pore-facing glycans in the alternative pentameric configuration, βαβαγ, did not result in significant structural changes in either the ECD or the TMD, aside from modest rearrangements at the subunit interfaces (SFig. 3). The convex hull of the ECD remained stable, and the pore radius in this region was comparable to that of the βα G βα G γ. Changes in internal loop flexibility were minor and lacked a consistent pattern. Water-occupancy patterns of βαβαγ remained comparable to those observed in βα G βα G γ at the activation gate with only a subtle decrease at desensitization gate consistent with the latter's minor decrease in pore radius at DG (SFig. 3, 4). Overall, in the absence of pore-facing glycans, the channel βαβαγ maintains structural and dynamic properties similar to those of βα G βα G γ , without substantial alterations in dynamic behavior. An Allosteric Network Coupling ECD Disruption to Activation Gate Closure The highly reproducible conformational changes observed in both the ECD and TMD across all βα G βα G γ* G trajectories, particularly disruptions of native contacts in the ECD and activation-gate closure in the TMD, strongly suggest the presence of an allosteric coupling that transmits the structural effects of the additional glycan from the ECD to the TMD. Dynamical network analysis within each subunit revealed a consistent pathway originating from charged residues at the GABA binding site and extending to the activation-gate in the TMD (Fig. 7 ). These pathways commonly traverse the Cys-loop interface and the TM2-TM3 linker at the ECD-TMD junction, highlighting their role as key conduits for allosteric communication. Within subunits approximately 93.9% of the observed residue-residue pairs exhibited correlation coefficients exceeding a threshold of |C i ⱼ| ≥ 0.5, with a mean correlation of 0.718 (Supplementary Tables 3 and 4) indicating a strong and functionally meaningful coupling between structural elements 88 . This high correlation is strong evidence that the identified allosteric pathways are not artifacts of stochastic fluctuations, but instead reflect robust structural communication. These pathways consistently extend from the GABA binding site—located near the glycan attachment region—toward the activation gate, suggesting a directional and functionally relevant allosteric network. Notably, this network appears to be significantly modulated by glycan presence, reinforcing the role of glycosylation in shaping long-range signal propagation within the receptor. Excluding the start and end residues, 12 out of 15 residues in the α subunit pathways appeared in both α B and α D subunits (Fig. 7 A). Moreover, α B shows higher occupancy conservation with 7 out of 12 residues appearing in more than 75% of trajectories, whereas α D demonstrates greater pathway diversity and lower conservation at the ECD, with only 3 out of 13 residues conserved above the 75% threshold. This variability in α D is attributed to its proximity to the glycan localization site, where glycan-induced displacement of subunits broadens the explored conformational space. In β subunits, 11 out of 16 residues were observed between both subunits across different pathways (Fig. 7 ). Within these subunits, β A has 4 out of 14 residues with over 75% recurrence, whereas β C has 3 out of 13 residues with repeated observation. Additionally, 7 residues (excluding AG residues) between α and homologous β subunit positions consistently appeared across all pathways, highlighting significant cross-subunit consistency in signal propagation (Fig. 7 A). Overall, pathways demonstrate higher conservation within the TMD, while the ECD displays more diverse and dispersed pathway exploration. Analysis of the protein–glycan interface edges reveal distinct interaction patterns among different glycans (SFig. 2). The α D -attached glycan (CARB), which exhibits the lowest fluctuations and strongest spatial localization at the β C -α D interface, forms the highest number of contact edges with protein. Although CARB frequently contacts residues at the β C -α D interface, the associated correlation values are generally lower than those observed in the β A and α B contact edges with other glycans. This suggests that allosteric pathways near CARB may be more diverse and potentially more sensitive to local structural fluctuations (SFig. 2, Supplementary Table 2). In contrast, α B and β A form fewer glycan–protein contact edges with α B -attached glycan (CARA), but those interactions are more strongly correlated, indicating more consistent and direct communication. Therefore, pathways near the glycan localization site in β C and α D exhibit greater disruption in allosteric coupling compared to β A and α B . The introduction of the third glycan diversifies subunit connectivity around the glycan site, causing subunit displacement and altering communication pathways more prominently in β C and α D . Three α subunits lead to substantial rearrangements and closure of TMD in βα G βα G α G The βα G βα G α G system with three pore-facing glycans exhibited a similar disruption of ECD subunit interface and substantial rearrangements within the TMD as βα G βα G γ* G , ultimately leading to closure in the lower regions of the TMD that renders the channel non-functional. By the end of the simulation, the modeled α D -α E interface retained over 90% similarity to previously reported α-homomeric interfaces (PDB ID: 8BHQ), supporting the validity of the system's construction. In contrast, other subunit interfaces showed a significant reduction in the occupancy for previously identified salt bridges (e.g., α B K132 - β C D72) and even a complete loss of other contacts (Fig. 8 A). Similarly, hydrogen bond analysis showed a drastic rearrangement at the β A - α B and β C - α D interfaces (Fig. 8 B). Similar to βα G βα G γ* G , the glycan localization at the β C - α D interface in βα G βα G α G and the steric clash of glycans likely contributes to the observed structural effects and the subtle yet notable 21.66 Ų increase in convex volume of the ECD (SFig. 5) compared to βα G βα G γ. The TMD of βα G βα G α G undergoes significant rearrangement within the first 200 ns of simulation (SFig. 5F). This rearrangement is characterized by a 2.61 Å inward displacement of α E TM2, disrupting its five-fold symmetry of TMD (SFig. 5G). This shift leads to a substantial reduction in pore radius at the 2nd HCS, where the pore radius decreased from 2.03 Å to 1.48 Å (p-value < 0.001), and the desensitization gate goes from 1.94 Å to 1.74 Å (Fig. 8 C, SFig. 5). In contrast, the change in pore radius at AG is negligible. This narrowing in the lower pore region corresponds with a marked reduction in water occupancy within the lower TMD (Fig. 8 D). By comparison, a structurally similar pentamer without glycosylation (βαβαα) maintained significantly larger pore radii across the three TMD regions of interest (AG: 2.31 Å, 2nd HCS: 2.19 Å, DG: 1.87 Å). These findings indicate that the presence of three pore-facing glycans in the βα G βα G α G system produced substantial structural perturbations in both the ECD and TMD, showing significant disruption to channel architecture that likely renders the channel non-functional. This is consistent with our observations in the βα G βα G γ* G system, which also contains three pore-facing glycans. Two adjacent α subunits facilitate channel closure in βα G α G βγ The disruption of natural interfaces and steric clashes between glycans in βα G α G βγ propagate to the TMD, leading to significant closure at the AG and DG. The modeled α B - α C and β D -γ E interfaces retained over 90% similarity to previously reported structures (PDB ID: 7QNA, 8BHQ) by the end of the simulation, confirming the validity of the system’s construction. The adjacency of the glycan creates a steric clash at the glycan core, increasing the overall structural fluctuation of glycan and the internal loops they are attached to (SFig. 3). At the ECD, salt bridge occupancy mostly increases at the β A -α B and γ E -β A interfaces (Fig. 9 A). Hydrogen bond analysis follows a similar trend of increase in occupancy. However, the salt bridge β A D187 - α B R112 and the conserved hydrogen bond β A T120 - α B T140—located close to the GABA binding site—showing a notable decrease in occupancy (Fig. 9 A&B). These structural rearrangements at the ECD propagate to the TMD, culminating in a 5.86 Å inward movement of α C and 5.95 Å outward movement of α B at the desensitization gate (SFig. 6). This shift leads to significant tightening at the AG, 2nd HCS, and DG (all p-values < 0.001), which becomes more pronounced as the simulation progresses (Fig. 9 , SFig. 6E). Interestingly, a similar reduction in pore radius is not observed in a βααβγ system without glycosylation (SFig. 6F). Water occupancy analysis in βα G α G βγ further reflects this trend, with a marked reduction in water molecules in the lower TMD similar to βα G βα G α G (Fig. 9 D). Therefore, the rearrangement of the ECD interface drives the progressive closure of both the activation and desensitization gates in βα G α G βγ. The cumulative effects at both the ECD and TMD indicate a considerable disruption in channel activity for βα G α G βγ, which would likely render the channel non-functional. DISCUSSION Our study suggested that the pore-facing N‐linked glycan on GABA A R α subunits plays a crucial role in proper pentameric assembly and channel gating. MD simulations reveal that the introduction of additional or neighboring glycans disrupts native salt bridges and hydrogen bond networks at key β + /α – subunit interfaces. This disruption translates into permanent closure of the TMD at the activation or desensitization gates. This observation is not only in line with the previous structural hypothesis that steric hindrance from pore-facing glycans prevents the formation of a pentameric receptor with more than 2 α subunits 37 , but also provide a mechanistic explanation as to how additional or neighboring α subunits alter channel structure and function. To date, direct experimental evidence supporting the determinant role of pore-facing glycans in GABA A Rs assembly pattern remains limited. However, the importance of the α subunit in subunit arrangement is supported by experimental studies suggesting two clusters of residues on the α subunit to be essential for recruiting and stabilizing the interface with the β subunit 32 . These clusters include the majority of the rearranged salt bridges identified in our simulations, indicating that the additional glycan, by destabilizing native inter-subunit interactions, may impair subunit recruitment or channel activity. Earlier homology modeling studies proposed a symmetrical salt bridge network at the subunit interface 98 , hypothesized to be critical for structural and functional stability. Although more recent structural data shows that several of these proposed salt bridges are spatially distant 45 , 96 , 99 , our analysis reveals an alternative salt bridge network that plays an equivalent structural role. This network is primarily located at the lower part of the ECD and extends across the ECD–TMD interface and associated loops (Fig. 4 E). Many disrupted salt bridges and hydrogen bonded residues represent critical nodes for channel function and their mutations are associated with diseases. Notably, the β K126 - α D90, α K132 - β D72, and γ K156 - β D72 interactions form a conserved framework at the β+/α–, α+/β–, and β+/γ– interfaces (Fig. 4 )). The residue D90 in the α subunit emerges as a key node, forming salt bridges with β subunits. Pathogenic mutations at this site—such as D90N and D90Y—have been linked to Juvenile Myoclonic Epilepsy and Idiopathic Generalized Epilepsy 100 , underscoring its essential role in subunit coupling and gating. Likewise, the D72Y in the β subunit plays a hub role in this intersubunit salt-bridge network. Its mutation is primarily associated with prostate cancer 100 , indicating that this residue may have broader functional significance. Additionally, mutations such as R112Q 101 , H137T 100 , and D125N 102 in the α subunit, as well as D119H 100 and N327K 102 in the β subunit, are reported in various forms of epilepsy, cancer, and intellectual disability. Importantly, α K306 (SFig. 1), located along a suggested allosteric pathway 103 for pLGIC, shows disease relevance through the K306T mutation that is implicated in developmental and epileptic encephalopathy 101 . Collectively, the overlap between intersubunit interaction networks and disease-associated mutations highlights the critical structural role of these bonds and their potential vulnerability to glycosylation-induced structural rearrangement. Previous investigations on GLIC gating identified D32 as a critical molecular "switch" at the ECD–TMD interface 103 . The breaking of the D32–R192 salt bridge is among the initial events triggering structural rearrangements that lead to pore collapse and channel closure. Once freed from R192, D32 engages K248, directly linking ECD rearrangements to TMD movements critical for gating. Similarly, in our study we observed consistent disruption of the homologous salt bridge between α B E76 (equivalent to D32) and β C K306—with occupancy reduced by over 10% across all replicas. Dynamical network analysis also revealed rerouting of allosteric pathways, effectively bypassing the E76 hub, pushing the system toward novel interactions that lead to pronounced TMD closure. Together, these results confirm the conserved, critical role of this salt-bridge interaction in coupling extracellular conformational changes to channel gating in pLGIC. Comparative analysis of the A–E (β4–β5) linker dynamics reveals that the loop's deviation from its optimal flexibility—either increased or decreased—can impair channel gating. Previous work by Venkatachalan and Czajkowski 104 showed that increasing the flexibility of this loop through the insertion of glycines disrupted gating, with modifications in the β subunit producing a substantial increase in GABA EC₅₀ and slower channel opening compared to equivalent insertions in the α-subunit. However, other structural alterations were not examined. Our simulations show that additional pore-facing N -linked glycans reduce A–E loop flexibility, particularly in the β C and γ E subunits, which correlates with activation-gate closure in the TMD. Together, these findings indicate that both excessive flexibility and increased rigidity of the A–E loop can disrupt its role in coupling agonist binding to channel opening, defining a narrow dynamic range essential for efficient gating. Our simulations reveal that pore-facing glycans exert a significant influence on the structural integrity of both the activation gate (9′), the desensitization gate (− 2′) and 2nd HCS (2′) within the TMD of the GABA A R. In the βα G βα G γ, the average pore radii at 9′, 2′, and − 2′ positions were 1.38 Å, 2.03 Å, and 1.96 Å, respectively—values consistent with a semi-desensitized or pre-active state, yet notably narrower than the radii suggested in open-state models, where the 9′ gate reaches ~ 4 Å and the − 2′ gate opens to ~ 3 Å in a computational study 105 . βα G βα G γ* G with three pore-facing glycans exhibited a pronounced constriction at the 9′ gate (1.19 Å) and moderate reductions at the 2′ (1.86 Å) and − 2′ (2.05 Å) positions in addition to exhibiting a rapid switching behavior of the AG at 9′ between 0.6 Å and 1.25 Å. This is indicative of a closed-like state. This narrowing becomes more severe in βα G βα G α G , particularly at 2′ (1.48 Å) and − 2′ (1.74 Å), with the 9′ gate measuring 1.37 Å. The βα G α G βγ showed the most constricted profile, with pore radii falling to 0.88 Å (9′), 1.63 Å (2′), and 0.84 Å (− 2′), values well below the thresholds required for chloride conduction. Compared to literature-reported states stabilized by modulators such as etomidate or propofol—where AG opens widely (4.2–5.2 Å) but DG remains collapsed (~ 1.4–1.6 Å) 34,44 —our glycan-containing mutants consistently show closure at both gates, suggesting a shift toward a non-conductive conformation. Notably, channel closure does not correlate with GABA dissociation, as it does not necessarily occur before or after GABA dissociation, indicating that the observed constrictions at AG, 2nd HCS, and DG are not a consequence of GABA dissociation. The glycosylation site is conserved across all GABA A R α subunits and may represent a recent evolutionary gain-of-glycosylation event. This site is unique to α subunits, as this sequon is absent in other GABA A R subunits or other members of the pLGIC family. Notably, the functional importance of this region extends beyond the conserved N-glycosylation site. For instance, in the β subunit, the homologous extracellular β4–β5 loop—although not glycosylated—plays a key role in receptor activation 104 . Furthermore, the evolutionary conservation of a threonine residue (Fig. 5 G) located two positions downstream of the glycosylation site highlights its role as a structural "priming" element that facilitates the emergence of glycosylation sites 106 . Glycosylated asparagine residues are subject to strong purifying selection pressure and thus evolve more slowly 107 . However, sequence analyses have shown that most newly acquired N -glycosylation sites arise from the introduction of asparagine into pre-existing motifs already containing a conserved threonine at the + 2 position (Fig. 2 B&C) 106,108 . These latent motifs, maintained by genetic drift or bias, serve as evolutionary placeholders—structurally stable regions poised for rapid functional enhancement upon acquiring a glycosylation-competent sequon 109 . A well-documented example of this mechanism is found in primate thyroglobulin evolution, where a threonine residue conserved across mammals was complemented by a human-specific asparagine mutation at position 76, generating an N -glycosylation site (N-X-T) that significantly improved thyroxine production 106 . Similarly, in GABA A Rs, conserved threonine residues may act as evolutionary precursors for glycosylation, contributing to structural integrity while enabling future regulation of channel assembly and function. While our computational findings implicate the determinant role of pore-facing glycans in subunit composition to prevent three or neighboringα subunits, experimental validation of this mechanism remains underexplored and challenging. Previous structural studies that resolved GABA A R α homomers involved substantial modification to the ECD, particularly at the pore-facing N-glycosylation site. For example, one study employed a cell line with incomplete glycan expression, combined with a neutralizing mutation at N123 on the α1 subunit to prevent glycosylation 47 . Another replaced the GABA A R ECD with that of the ELIC’s 48 or β subunits 110 , thereby eliminating the native pore-facing glycosylation. Several studies have proposed an α–α interface using concatenated constructs designed to enforce specific subunit arrangement 26 . However, these findings remain controversial, as no naturally resolved structure has confirmed such configurations, and it is argued that forced assembly may yield non-native, potentially deleterious receptor builds 111 . A more rigorous approach to validate the role of glycosylation in subunit arrangement would be to resolve the structure of a fully concatenated construct encoding all five subunits, accompanied by detailed glyco-profiling using mass spectrometry. It is noted that there are several limitations to the current study. First, the structure of the pore-facing glycan modeled in our simulations may not fully reflect its native composition. Although, current cryo-EM structures show that the pore‐facing glycan on the α subunit adopts a high‐mannose form 21 , 25 , 37 , 44 , with one structure displaying a Man8 configuration 44 , additional studies are needed to clarify the extent of terminal mannose trimming. This uncertainty stems from the inherent variability in glycosylation processing by enzymes in the endoplasmic reticulum and cis ‐Golgi 112 , 113 . If the pore-facing glycans are more extended in vivo , their structural and functional impact could be greater than what we observe in our present study. Furthermore, N‐linked glycosylation composition can vary across tissues and species 112 . Future in-depth glycomic profiling of GABA A Rs may reveal additional insights into their regulation by glycosylation. Secondly, this study specifically examines the effects of pore‐facing glycosylation on the structure and dynamics of the assembled GABA A Rs. However, we do not address its potential role in the assembly process. Given that these N-linked glycans are known to influence protein expression, assembly, and trafficking 46 ; this remains an important yet unexplored aspect beyond the scope of our simulation study. Further studies are needed to investigate how glycosylation affects receptor biosynthesis and maturation. CONCLUSION Our study reveals that pore-facing N-linked glycans on GABA A receptor α subunits play a critical role in determining pentameric assembly patterns and modulating channel gating. Through integrative structural survey, sequence analysis, and molecular dynamics simulations, we demonstrate that introducing two neighboring pore-facing glycans disrupts conserved interfacial networks—specifically salt bridges and hydrogen bonds—at key β+/α– subunit interfaces within the ECD. These disruptions propagate allosterically from the ECD to the TMD, leading to altered internal loop flexibility, loss of coordinated gating motions, and premature closure of the activation or desensitization gates. This structural rearrangement results in a shift toward non-conductive channel conformations. These computational insights are consistent with prior structural hypotheses and help explain functional consequences of disease-associated mutations located near glycan-sensitive regions or along the ECD-TMD allosteric coupling pathway. Importantly, our findings underscore the evolutionary uniqueness and functional importance of the α subunit-attached pore-facing N-glycosylation site, suggesting it acts as a molecular determinant of subunit composition and channel function. Although our models provide mechanistic clarity, experimental validation remains essential. Together, our findings reveal the underappreciated yet critical role of pore-facing glycans in shaping GABA A R architecture and function. This work lays the foundation for glycan-aware strategies in receptor modulation and opens new avenues for developing selective therapeutics targeting glycosylation-mediated control of ion channel activity. Declarations Acknowledgment The authors gratefully acknowledge discussions with Dr. Claudio Grosman and Dr. Joshua Sharp. We also thank Laila Aiad for her early involvement in the project. Research reported in this publication was supported by a National Science Foundation CAREER grant under award number 2439983, an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under award number P20GM130460, and the National Institute of General Medical Sciences of the National Institutes of Health under Award Number R35GM160133. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Computer resources came from a Maximize ACCESS allocation through project BIO210015, an allocation (MCB200085P) on Anton2/Anton3 at the Pittsburgh Supercomputing Center, provided by the National Center for Multiscale Modeling of Biological Systems through National Institutes of Health grant P41GM103712-1, and from a loan from D. E. Shaw Research. The authors also thank the Computational Chemistry and Bioinformatics Research Core within the University of Mississippi’s Glycoscience Center of Research Excellence (NIH Project Number 5P20GM130460-04) for use of their computers and assistance with software installation. References Tretter, V., Moss, S.J.: GABA(A) receptor dynamics and constructing GABAergic synapses. Front. Mol. Neurosci. 1 , 7 (2008) Scott, S., Aricescu, A.R.: A structural perspective on GABAA receptor pharmacology. Curr. Opin. Struct. Biol. 54 , 189–197 (2019) Kim, J.J., Hibbs, R.E.: Direct structural insights into GABAA receptor pharmacology. Trends Biochem. Sci. 46 , 502–517 (2021) Sigel, E., Steinmann, M.E.: Structure, function, and modulation of GABA(A) receptors. J. Biol. Chem. 287 , 40224–40231 (2012) Davies, C.H., Davies, S.N., Collingridge, G.L.: Paired-pulse depression of monosynaptic GABA-mediated inhibitory postsynaptic responses in rat hippocampus. J. Physiol. 424 , 513–531 (1990) Ghit, A., Assal, D., Al-Shami, A.S., Hussein, D.E.: E. GABAA receptors: structure, function, pharmacology, and related disorders. J. Genet. Eng. Biotechnol. 19, 123 (2021) Luscher, B., Fuchs, T., Kilpatrick, C.L.: GABAA receptor trafficking-mediated plasticity of inhibitory synapses. Neuron. 70 , 385–409 (2011) Harris, R.A., Allan, A.M.: Functional coupling of gamma-aminobutyric acid receptors to chloride channels in brain membranes. Science. 228 , 1108–1110 (1985) Kittler, J.T., McAinsh, K., Moss, S.J.: Mechanisms of GABAA receptor assembly and trafficking: implications for the modulation of inhibitory neurotransmission. Mol. Neurobiol. 26 , 251–268 (2002) Richardson, R.J., Petrou, S., Bryson, A.: Established and emerging GABAA receptor pharmacotherapy for epilepsy. Front. Pharmacol. 15 , 1341472 (2024) Enoch, M.-A.: The role of GABAA receptors in the development of alcoholism. Pharmacol. Biochem. Behav. 90 , 95–104 (2008) Thompson, S.M.: Modulators of GABAA receptor-mediated inhibition in the treatment of neuropsychiatric disorders: past, present, and future. Neuropsychopharmacology. 49 , 83–95 (2024) Hernandez, C.C., Macdonald, R.L.: A structural look at GABAA receptor mutations linked to epilepsy syndromes. Brain Res. 1714 , 234–247 (2019) Maljevic, S., Møller, R.S., Reid, C.A., Pérez-Palma, E., Lal, D., May, P., Lerche, H.: Spectrum of GABAA receptor variants in epilepsy. Curr. Opin. Neurol. 32 , 183–190 (2019) Angelotti, T.P., Macdonald, R.L.: Assembly of GABAA receptor subunits: alpha 1 beta 1 and alpha 1 beta 1 gamma 2S subunits produce unique ion channels with dissimilar single-channel properties. J. Neurosci. 13 , 1429–1440 (1993) Engin, E.: GABAA receptor subtypes and benzodiazepine use, misuse, and abuse. Front. Psychiatry. 13 , 1060949 (2022) Fan, C., Cowgill, J., Howard, R.J., Lindahl, E.: Divergent mechanisms of steroid inhibition in the human ρ1 GABAA receptor. Nat. Commun. 15 , 7795 (2024) Goetz, T., Arslan, A., Wisden, W., Wulff, P.: GABA(A) receptors: structure and function in the basal ganglia. Prog Brain Res. 160 , 21–41 (2007) Gielen, M., Barilone, N., Corringer, P.J.: The desensitization pathway of GABAA receptors, one subunit at a time. Nat. Commun. 11 , (2020) Cowgill, J., Fan, C., Steyaert, J., Howard, R.J., Lindahl, E.: Structural basis for activation and potentiation in a human α5β3 GABAA receptor. bioRxiv. (2025). 10.1101/2025.01.27.635004 Chua, H.C., Chebib, M.G.A.B.A.A.: Receptors and the Diversity in their Structure and Pharmacology. Adv. Pharmacol. 79 , 1–34 (2017) Sente, A., Desai, R., Naydenova, K., Malinauskas, T., Jounaidi, Y., Miehling, J., Zhou, X., Masiulis, S., Hardwick, S.W., Chirgadze, D.Y., Miller, K.W., Aricescu, A.R.: Differential assembly diversifies GABAA receptor structures and signalling. Nature. 604 , 190–194 (2022) Feng, H.-J., Forman, S.A.: Comparison of αβδ and αβγ GABAA receptors: Allosteric modulation and identification of subunit arrangement by site-selective general anesthetics. Pharmacol. Res. 133 , 289–300 (2018) Olsen, R.W., Sieghart, W.: GABA A receptors: subtypes provide diversity of function and pharmacology. Neuropharmacology. 56 , 141–148 (2009) Sun, C., Zhu, H., Clark, S., Gouaux, E.: Cryo-EM structures reveal native GABAA receptor assemblies and pharmacology. Nature. 622 , 195–201 (2023) Botzolakis, E.J., Gurba, K.N., Lagrange, A.H., Feng, H.-J., Stanic, A.K., Hu, N., Macdonald, R.L.: Comparison of γ-aminobutyric acid, type A (GABAA), receptor αβγ and αβδ expression using flow cytometry and electrophysiology: EVIDENCE FOR ALTERNATIVE SUBUNIT STOICHIOMETRIES AND ARRANGEMENTS. J. Biol. Chem. 291 , 20440–20461 (2016) Sieghart, W.: Structure, pharmacology, and function of GABAA receptor subtypes. Adv. Pharmacol. 54 , 231–263 (2006) Goldschen-Ohm, M.P.: Benzodiazepine modulation of GABAA receptors: A mechanistic perspective. Biomolecules. 12 , 1784 (2022) Knoflach, F., Bertrand, D.: Pharmacological modulation of GABAA receptors. Curr. Opin. Pharmacol. 59 , 3–10 (2021) Crunkhorn, S.: Understanding GABAA receptor pharmacology. Nat. Rev. Drug Discov. 22 , 873 (2023) Martenson, J.S., Yamasaki, T., Chaudhury, N.H., Albrecht, D., Tomita, S.: Assembly rules for GABAA receptor complexes in the brain. Elife 6 , (2017) Bollan, K., King, D., Robertson, L.A., Brown, K., Taylor, P.M., Moss, S.J., Connolly, C.: N. GABA(A) receptor composition is determined by distinct assembly signals within alpha and beta subunits. J. Biol. Chem. 278 , 4747–4755 (2003) Baumann, S.W., Baur, R., Sigel, E.: Forced subunit assembly in alpha1beta2gamma2 GABAA receptors. Insight into the absolute arrangement. J. Biol. Chem. 277 , 46020–46025 (2002) Zhou, J., Noviello, C.M., Teng, J., Moore, H., Lega, B., Hibbs, R.E.: Resolving native GABAA receptor structures from the human brain. Nature. 638 , 562–568 (2025) Chojnacka, W., Teng, J., Kim, J.J., Jensen, A.A., Hibbs, R.E.: Structural insights into GABAA receptor potentiation by Quaalude. Nat. Commun. 15 , 5244 (2024) Zhu, S., Sridhar, A., Teng, J., Howard, R.J., Lindahl, E., Hibbs, R.E.: Structural and dynamic mechanisms of GABAA receptor modulators with opposing activities. Nature Communications 2022 13:1 13, 1–13 (2022) Phulera, S., Zhu, H., Yu, J., Claxton, D.P., Yoder, N., Yoshioka, C., Gouaux, E.: Cryo-EM structure of the benzodiazepine-sensitive α1β1γ2S tri-heteromeric GABAA receptor in complex with GABA. Elife. 7 , e39383 (2018) Ohtsubo, K., Marth, J.D.: Glycosylation in cellular mechanisms of health and disease. Cell. 126 , 855–867 (2006) Scott, H., Panin, V.M.: The role of protein N-glycosylation in neural transmission. Glycobiology. 24 , 407–417 (2014) Mueller, T.M., Haroutunian, V., Meador-Woodruff, J.H.: N-Glycosylation of GABAA receptor subunits is altered in Schizophrenia. Neuropsychopharmacology. 39 , 528–537 (2014) Lo, W.-Y., Lagrange, A.H., Hernandez, C.C., Harrison, R., Dell, A., Haslam, S.M., Sheehan, J.H., Macdonald, R.L.: Glycosylation of {beta}2 subunits regulates GABAA receptor biogenesis and channel gating. J. Biol. Chem. 285 , 31348–31361 (2010) Tanaka, M., Olsen, R.W., Medina, M.T., Schwartz, E., Alonso, M.E., Duron, R.M., Castro-Ortega, R., Martinez-Juarez, I.E., Pascual-Castroviejo, I., Machado-Salas, J., Silva, R., Bailey, J.N., Bai, D., Ochoa, A., Jara-Prado, A., Pineda, G., Macdonald, R.L.: Delgado-Escueta, A. V. Hyperglycosylation and reduced GABA currents of mutated GABRB3 polypeptide in remitting childhood absence epilepsy. Am. J. Hum. Genet. 82 , 1249–1261 (2008) Tsai, Y.-X., Chang, N.-E., Reuter, K., Chang, H.-T., Yang, T.-J., von Bülow, S., Sehrawat, V., Zerrouki, N., Tuffery, M., Gecht, M., Grothaus, I.L., Ciacchi, C., Wang, L., Hsu, Y.-S., Khoo, M.-F., Hummer, K.-H., Hsu, G., Hanus, S.-T.D., C., Sikora, M.: Rapid simulation of glycoprotein structures by grafting and steric exclusion of glycan conformer libraries. Cell. 187 , 1296–1311e26 (2024) Kim, J.J., Gharpure, A., Teng, J., Zhuang, Y., Howard, R.J., Zhu, S., Noviello, C.M., Walsh, R.M., Jr, Lindahl, E., Hibbs, R.E.: Shared structural mechanisms of general anaesthetics and benzodiazepines. Nature. 585 , 303–308 (2020) Zhu, S., Noviello, C.M., Teng, J., Walsh, R.M., Jr, Kim, J.J., Hibbs, R.E.: Structure of a human synaptic GABAA receptor. Nature. 559 , 67–72 (2018) Buller, A.L., Hastings, G.A., Kirkness, E.F., Fraser, C.M.: Site-directed mutagenesis of N-linked glycosylation sites on the gamma-aminobutyric acid type A receptor alpha 1 subunit. Mol. Pharmacol. 46 , 858–865 (1994) Kasaragod, V.B., Malinauskas, T., Wahid, A.A., Lengyel, J., Knoflach, F., Hardwick, S.W., Jones, C.F., Chen, W.-N., Lucas, X., El Omari, K., Chirgadze, D.Y., Aricescu, A.R., Cecere, G., Hernandez, M.-C., Miller, P.S.: The molecular basis of drug selectivity for α5 subunit-containing GABAA receptors. Nat. Struct. Mol. Biol. 30 , 1936–1946 (2023) Chen, Q., Wells, M.M., Arjunan, P., Tillman, T.S., Cohen, A.E., Xu, Y., Tang, P.: Structural basis of neurosteroid anesthetic action on GABAA receptors. Nat. Commun. 9 , 1–10 (2018) Stone, J.E.: An efficient library for parallel ray tracing and animation. at (1998). https://scholarsmine.mst.edu/masters_theses/1747/ Humphrey, W., Dalke, A., Schulten, K.: VMD: Visual molecular dynamics. J. Mol. Graph. 14 , 33–38 (1996) Roberts, E., Eargle, J., Wright, D.: Luthey-Schulten, Z. MultiSeq: unifying sequence and structure data for evolutionary analysis. BMC Bioinform. 7 , 382 (2006) Lomize, M.A., Pogozheva, I.D., Joo, H., Mosberg, H.I., Lomize, A.L.: OPM database and PPM web server: resources for positioning of proteins in membranes. Nucleic Acids Res. 40 , D370–D376 (2012) Jo, S., Kim, T., Iyer, V.G., Im, W.: CHARMM-GUI: a web-based graphical user interface for CHARMM. J. Comput. Chem. 29 , 1859–1865 (2008) Jo, S., Lim, J.B., Klauda, J.B., Im, W.: CHARMM-GUI Membrane Builder for mixed bilayers and its application to yeast membranes. Biophys. J. 97 , 50–58 (2009) Olsson, M.H.M., SØndergaard, C.R., Rostkowski, M., Jensen, J.H.: PROPKA3: Consistent treatment of internal and surface residues in empirical p K a predictions. J. Chem. Theory Comput. 7 , 525–537 (2011) Kim, S., Lee, J., Jo, S., Brooks, C.L. 3rd, Lee, H.S., Im, W.: CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules. J. Comput. Chem. 38 , 1879–1886 (2017) Park, S.-J., Lee, J., Qi, Y., Kern, N.R., Lee, H.S., Jo, S., Joung, I., Joo, K., Lee, J., Im, W.: CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates. Glycobiology. 29 , 320–331 (2019) Park, S.-J., Lee, J., Patel, D.S., Ma, H., Lee, H.S., Jo, S., Im, W.: Glycan Reader is improved to recognize most sugar types and chemical modifications in the Protein Data Bank. Bioinformatics. 33 , 3051–3057 (2017) Jo, S., Song, K.C., Desaire, H., MacKerell, A.D. Jr., Im, W.: Glycan Reader: automated sugar identification and simulation preparation for carbohydrates and glycoproteins. J. Comput. Chem. 32 , 3135–3141 (2011) Huang, J., Rauscher, S., Nawrocki, G., Ran, T., Feig, M., de Groot, B.L., Grubmüller, H., MacKerell, A.D.: Jr. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat. Methods. 14 , 71–73 (2017) MacKerell, A.D., Bashford, D., Bellott, M., Dunbrack, R.L., Evanseck, J.D., Field, M.J., Fischer, S., Gao, J., Guo, H., Ha, S., Joseph-McCarthy, D., Kuchnir, L., Kuczera, K., Lau, F.T., Mattos, C., Michnick, S., Ngo, T., Nguyen, D.T., Prodhom, B., Reiher, W.E., Roux, B., Schlenkrich, M., Smith, J.C., Stote, R., Straub, J., Watanabe, M., Wiórkiewicz-Kuczera, J., Yin, D., Karplus, M.: All-atom empirical potential for molecular modeling and dynamics studies of proteins. J. Phys. Chem. B. 102 , 3586–3616 (1998) MacKerell, A.D. Jr., Feig, M., Brooks, C.L.: Improved treatment of the protein backbone in empirical force fields. J. Am. Chem. Soc. 126 , 698–699 (2004). 3rd Klauda, J.B., Venable, R.M., Freites, J.A., O’Connor, J.W., Tobias, D.J., Mondragon-Ramirez, C., Vorobyov, I., MacKerell, A.D. Jr., Pastor, R.W.: Update of the CHARMM all-atom additive force field for lipids: validation on six lipid types. J. Phys. Chem. B. 114 , 7830–7843 (2010) Beglov, D., Roux, B.: Finite representation of an infinite bulk system: solvent boundary potential for computer simulations. J. Chem. Phys. 100 , 9050–9063 (1994) Guvench, O., Mallajosyula, S.S., Raman, E.P., Hatcher, E., Vanommeslaeghe, K., Foster, T.J., Jamison, F.W. I. I., MacKerell, A.D.: Jr. CHARMM Additive All-Atom Force Field for Carbohydrate Derivatives and Its Utility in Polysaccharide and Carbohydrate–Protein Modeling. J. Chem. Theory Comput. 7, 3162–3180 (2011) Jorgensen, W.L., Chandrasekhar, J., Madura, J.D.: Comparison of simple potential functions for simulating liquid water. The Journal of at (1983). https://pubs.aip.org/aip/jcp/article-abstract/79/2/926/776316 Feller, S.E., Zhang, Y., Pastor, R.W., Brooks, B.R.: Constant pressure molecular dynamics simulation: The Langevin piston method. J. Chem. Phys. 103 , 4613–4621 (1995) Darden, T., York, D., Pedersen, L.: Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems. J. Chem. Phys. 98 , 10089–10092 (1993) Deuflhard, P., Hermans, J., Leimkuhler, B., Mark, A.E., Reich, S., Skeel, R.D.: Computational Molecular Dynamics: Challenges, Methods, Ideas: Proceeding of the 2nd International Symposium on Algorithms for Macromolecular Modelling, Berlin, May 21–24 ,. (Springer Science & Business Media, 2012). at (1997). https://play.google.com/store/books/details?id=ZRX2CAAAQBAJ Gao, Y., Lee, J., Smith, I.P.S., Lee, H., Kim, S., Qi, Y., Klauda, J.B., Widmalm, G., Khalid, S., Im, W.: CHARMM-GUI Supports Hydrogen Mass Repartitioning and Different Protonation States of Phosphates in Lipopolysaccharides. J. Chem. Inf. Model. 61 , 831–839 (2021) Kalé, L., Skeel, R., Bhandarkar, M., Brunner, R., Gursoy, A., Krawetz, N., Phillips, J., Shinozaki, A., Varadarajan, K., Schulten, K.: NAMD2: Greater scalability for parallel molecular dynamics. J. Comput. Phys. 151 , 283–312 (1999) Phillips, J.C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R.D., Kalé, L., Schulten, K.: Scalable molecular dynamics with NAMD. J. Comput. Chem. 26 , 1781–1802 (2005) Shaw, D.E., Adams, P.J., Azaria, A., Bank, J.A., Batson, B., Bell, A., Bergdorf, M., Bhatt, J., Butts, J.A., Correia, T., Dirks, R.M., Dror, R.O., Eastwood, M.P., Edwards, B., Even, A., Feldmann, P., Fenn, M., Fenton, C.H., Forte, A., Gagliardo, J., Gill, G., Gorlatova, M., Greskamp, B., Grossman, J.P., Gullingsrud, J., Harper, A., Hasenplaugh, W., Heily, M., Heshmat, B.C., Hunt, J., Ierardi, D.J., Iserovich, L., Jackson, B.L., Johnson, N.P., Kirk, M.M., Klepeis, J.L., Kuskin, J.S., Mackenzie, K.M., Mader, R.J., McGowen, R., McLaughlin, A., Moraes, M.A., Nasr, M.H., Nociolo, L.J., O’Donnell, L., Parker, A., Peticolas, J.L., Pocina, G., Predescu, C., Quan, T., Salmon, J.K., Schwink, C., Shim, K.S., Siddique, N., Spengler, J., Szalay, T., Tabladillo, R., Tartler, R., Taube, A.G., Theobald, M., Towles, B., Vick, W., Wang, S.C., Wazlowski, M., Weingarten, M.J., Williams: J. M. & Yuh, K. A. Anton 3. in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis ACM, (2021). 10.1145/3458817.3487397 Bowers, K.J., Chow, E., Xu, H., Dror, R.O., Eastwood, M.P., Gregersen, B.A., Klepeis, J.L., Kolossvary, I., Moraes, M.A., Sacerdoti, F.D., Salmon, J.K., Shan, Y., Shaw, D.E.: Scalable algorithms for molecular dynamics simulations on commodity clusters. in Proceedings of the ACM/IEEE Conference on Supercomputing, SC’06 (2006). (2006). 10.1145/1188455.1188544 Lippert, R.A., Predescu, C., Ierardi, D.J., Mackenzie, K.M., Eastwood, M.P., Dror, R.O., Shaw, D.E.: Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure. J. Chem. Phys. 139 , 164106 (2013) Åqvist, J., Wennerström, P., Nervall, M., Bjelic, S., Brandsdal, B.O.: Molecular dynamics simulations of water and biomolecules with a Monte Carlo constant pressure algorithm. Chem. Phys. Lett. 384 , 288–294 (2004) Tuckerman, M., Berne, B.J., Martyna, G.J.: Reversible multiple time scale molecular dynamics. J. Chem. Phys. 97 , 1990–2001 (1992) Predescu, C., Lerer, A.K., Lippert, R.A., Towles, B., Grossman, J.P., Dirks, R.M., Shaw, D.E.: The u-series: A separable decomposition for electrostatics computation with improved accuracy. J. Chem. Phys. 152 , 084113 (2020) Predescu, C., Bergdorf, M., Shaw, D.E.: Midtown splines: An optimal charge assignment for electrostatics calculations. J. Chem. Phys. 153 , 224117 (2020) Michaud-Agrawal, N., Denning, E.J., Woolf, T.B., Beckstein, O.: MDAnalysis: A toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. 32 , 2319–2327 (2011) Virtanen, P., Gommers, R., Oliphant, T.E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S.J., Brett, M., Wilson, J., Millman, K.J., Mayorov, N., Nelson, A.R.J., Jones, E., Kern, R., Larson, E., Carey, C.J., Polat, İ., Feng, Y., Moore, E.W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E.A., Harris, C.R., Archibald, A.M., Ribeiro, A.H., Pedregosa, F., van Mulbregt, P., Vijaykumar, A., Bardelli, A.P., Rothberg, A., Hilboll, A., Kloeckner, A., Scopatz, A., Lee, A., Rokem, A., Woods, C.N., Fulton, C., Masson, C., Häggström, C., Fitzgerald, C., Nicholson, D.A., Hagen, D.R., Pasechnik, D.V., Olivetti, E., Martin, E., Wieser, E., Silva, F., Lenders, F., Wilhelm, F., Young, G., Price, G.A., Ingold, G.L., Allen, G.E., Lee, G.R., Audren, H., Probst, I., Dietrich, J.P., Silterra, J., Webber, J.T., Slavič, J., Nothman, J., Buchner, J., Kulick, J., Schönberger, J.L., de Miranda Cardoso, J.V., Reimer, J., Harrington, J., Rodríguez, J.L.C., Nunez-Iglesias, J., Kuczynski, J., Tritz, K., Thoma, M., Newville, M., Kümmerer, M., Bolingbroke, M., Tartre, M., Pak, M., Smith, N.J., Nowaczyk, N., Shebanov, N., Pavlyk, O., Brodtkorb, P.A., Lee, P., McGibbon, R.T., Feldbauer, R., Lewis, S., Tygier, S., Sievert, S., Vigna, S., Peterson, S., More, S., Pudlik, T., Oshima, T., Pingel, T.J., Robitaille, T.P., Spura, T., Jones, T.R., Cera, T., Leslie, T., Zito: T., Krauss, T., Upadhyay, U., Halchenko, Y. O. & Vázquez-Baeza, Y. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat. Methods 17, 261–272 (2020) Smart, O.S., Neduvelil, J.G., Wang, X., Wallace, B.A., Sansom, M.S.: P. HOLE: A program for the analysis of the pore dimensions of ion channel structural models. J. Mol. Graph. 14 , 354–360 (1996) Gowers, R.J., Linke, M., Barnoud, J., Reddy, T.J.E., Melo, M.N., Seyler, S.L., Domański, J., Dotson, D.L., Buchoux, S., Kenney, I.M., Beckstein, O.: MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations. Proceedings of the 15th Python in Science Conference 98–105 (2016). 10.25080/MAJORA-629E541A-00E Bali, M., Akabas, M.H.: The location of a closed channel gate in the GABAA receptor channel. J. Gen. Physiol. 129 , 145–159 (2007) Xu, M., Akabas, M.H.: Identification of channel-lining residues in the M2 membrane-spanning segment of the GABA(A) receptor alpha1 subunit. J. Gen. Physiol. 107 , 195–205 (1996) Goren, E.N., Reeves, D.C., Akabas, M.H.: Loose protein packing around the extracellular half of the GABA(A) receptor beta1 subunit M2 channel-lining segment. J. Biol. Chem. 279 , 11198–11205 (2004) Gong, H., Porter, L.L., Rose, G.D.: Counting peptide-water hydrogen bonds in unfolded proteins. Protein Sci. 20 , 417–427 (2011) Sethi, A., Eargle, J., Black, A.A., Luthey-Schulten, Z.: Dynamical networks in tRNA:protein complexes. Proc. Natl. Acad. Sci. U. S. A. 106, 6620–6625 (2009) Van Rossum, G., Drake, F.L.: Python 3 Reference Manual; CreateSpace. Scotts Valley, CA 242 at (2009). https://www.python.org/ Harris, C.R., Millman, K.J., van der Walt, S.J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N.J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M.H., Brett, M., Haldane, A., del Río, J.F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C.: Oliphant, T. E. Array programming with NumPy. Nature. 585 , 357–362 (2020) Team, T.P.: D. pandas-dev/pandas: Pandas. (2023). 10.5281/ZENODO.7979740 Hunter, J.D., Matplotlib: A 2D graphics environment. Comput. Sci. Eng. 9 , 90–95 (2007) Lyu, Q., Xue, W., Liu, R., Ma, Q., Kasaragod, V.B., Sun, S., Li, Q., Chen, Y., Yuan, M., Yang, Y., Zhang, B., Nie, A., Jia, S., Shen, C., Gao, P., Rong, W., Yu, C., Bi, Y., Zhang, C., Nan, F., Ning, G., Rao, Z., Yang, X., Wang, J., Wang, W.: A brain-to-gut signal controls intestinal fat absorption. Nature. 634 , 936–943 (2024) Legesse, D.H., Fan, C., Teng, J., Zhuang, Y., Howard, R.J., Noviello, C.M., Lindahl, E., Hibbs, R.E.: Structural insights into opposing actions of neurosteroids on GABAA receptors. Nat. Commun. 14 , 5091 (2023) Noviello, C.M., Kreye, J., Teng, J., Prüss, H., Hibbs, R.E.: Structural mechanisms of GABAA receptor autoimmune encephalitis. Cell. 185 , 2469–2477e13 (2022) Laverty, D., Desai, R., Uchański, T., Masiulis, S., Stec, W.J., Malinauskas, T., Zivanov, J., Pardon, E., Steyaert, J., Miller, K.W., Aricescu, A.R.: Cryo-EM structure of the human α1β3γ2 GABAA receptor in a lipid bilayer. Nature. 565 , 516–520 (2019) Masiulis, S., Desai, R., Uchański, T., Martin, S., Laverty, I., Karia, D., Malinauskas, D., Zivanov, T., Pardon, J., Kotecha, E., Steyaert, A., Miller, J., K. W., Aricescu, A.: R. GABAA receptor signalling mechanisms revealed by structural pharmacology. Nature. 565 , 454–459 (2019) Venkatachalan, S.P., Czajkowski, C.: A conserved salt bridge critical for GABA(A) receptor function and loop C dynamics. Proc. Natl. Acad. Sci. U. S. A. 105, 13604–13609 (2008) Kasaragod, V.B., Mortensen, M., Hardwick, S.W., Wahid, A.A., Dorovykh, V., Chirgadze, D.Y., Smart, T.G., Miller, P.S.: Mechanisms of inhibition and activation of extrasynaptic αβ GABAA receptors. Nature. 602 , 529–533 (2022) UniProt Consortium: UniProt: The universal protein knowledgebase in 2023. Nucleic Acids Res. 51 , D523–D531 (2023) Carvill, G.L., Weckhuysen, S., McMahon, J.M., Hartmann, C., Møller, R.S., Hjalgrim, H., Cook, J., Geraghty, E., O’Roak, B.J., Petrou, S., Clarke, A., Gill, D., Sadleir, L.G., Muhle, H., von Spiczak, S., Nikanorova, M., Hodgson, B.L., Gazina, E.V., Suls, A., Shendure, J., Dibbens, L.M., De Jonghe, P., Helbig, I., Berkovic, S.F., Scheffer, I.E., Mefford, H.: C. GABRA1 and STXBP1: novel genetic causes of Dravet syndrome. Neurology. 82 , 1245–1253 (2014) Nykamp, K., Anderson, M., Powers, M., Garcia, J., Herrera, B., Ho, Y.-Y., Kobayashi, Y., Patil, N., Thusberg, J., Westbrook, M., Invitae Clinical Genomics Group, Topper, S.: Sherloc: a comprehensive refinement of the ACMG-AMP variant classification criteria. Genet. Med. 19, 1105–1117 (2017) Lev, B., Murail, S., Poitevin, F., Cromer, B.A., Baaden, M., Delarue, M., Allen, T.W.: String method solution of the gating pathways for a pentameric ligand-gated ion channel. Proc. Natl. Acad. Sci. U. S. A. 114, E4158–E4167 (2017) Venkatachalan, S.P., Czajkowski, C.: Structural link between γ-aminobutyric acid type A (GABAA) receptor agonist binding site and inner β-sheet governs channel activation and allosteric drug modulation. J. Biol. Chem. 287 , 6714–6724 (2012) Haloi, N., Lidbrink, E., Howard, S., R. J., Lindahl, E.: Adaptive sampling-based structural prediction reveals opening of a GABAA receptor through the αβ interface. Sci. Adv. 11 , eadq3788 (2025) Kim, D.S., Hahn, Y.: The acquisition of novel N-glycosylation sites in conserved proteins during human evolution. BMC Bioinform. 16 , 29 (2015) Park, C., Zhang, J.: Genome-wide evolutionary conservation of N-glycosylation sites. Mol. Biol. Evol. 28 , 2351–2357 (2011) Kim, D.S., Choi, D., Hahn, Y.: Loss of ancestral N-glycosylation sites in conserved proteins during human evolution. Int. J. Mol. Med. 36 , 1685–1692 (2015) Williams, R., Ma, X., Schott, R.K., Mohammad, N., Ho, C.Y., Li, C.F., Chang, B.S.W., Demetriou, M., Dennis, J.W.: Encoding asymmetry of the N-glycosylation motif facilitates glycoprotein evolution. PLoS One. 9 , e86088 (2014) Miller, P.S., Scott, S., Masiulis, S., De Colibus, L., Pardon, E., Steyaert, J., Aricescu, A.R.: Structural basis for GABAA receptor potentiation by neurosteroids. Nat. Struct. Mol. Biol. 24 , 986–992 (2017) Liao, V.W.Y., Chua, H.C., Kowal, N.M., Chebib, M., Balle, T., Ahring, P.K.: Concatenated γ-aminobutyric acid type A receptors revisited: Finding order in chaos. J. Gen. Physiol. 151 , 798–819 (2019) Varki, A., Cummings, R.D., Esko, J.D., Stanley, P., Hart, G.W., Aebi, M., Mohnen, D., Kinoshita, T., Packer, N.H., Prestegard, J.H., Schnaar, R.L., Seeberger, P.H.: Essentials of Glycobiology. Cold Spring Harbor Laboratory Press (2022). 10.1101/9781621824213 Fadda, E.: Molecular simulations of complex carbohydrates and glycoconjugates. Curr. Opin. Chem. Biol. 69 , 102175 (2022) Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryMaterials.docx Supplementary Materials for A Pore-Facing Glycan Determines GABAA Receptor Subunit Stoichiometry and Gating Behavior Cite Share Download PDF Status: Under Review Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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13:44:41","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":286178,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/f8b97d38760118dd81c962d0.html"},{"id":93783123,"identity":"03ce94d4-faa1-44cb-9cfb-79cb9b5238e1","added_by":"auto","created_at":"2025-10-17 13:36:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":840300,"visible":true,"origin":"","legend":"\u003cp\u003eProposed systems for investigating the effect of the pore-facing \u003cem\u003eN\u003c/em\u003e-glycosylation on GABA\u003csub\u003eA\u003c/sub\u003eR Gating and their controls with no pore-facing glycans. A) The high mannose structure of the pore-facing glycan. B) Top view of the PDB structure used for modeling the systems with man-8 structure in the middle, C) wild-type system with two pore-facing glycans (βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ) and the same pentameric form without pore-facing glycans (βαβαγ), D) The mutant (W162N in γ subunit) with three pore-facing glycans (βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e) and the glycan-free equivalent form (βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*). E) system with three α subunits and three pore-facing glycans (βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e) and the glycan-free form (βαβαα). F) system with two α subunits adjacent to each other and two pore-facing glycans (βα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003eβγ) and the glycan-free form (βααβγ).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/283ce814a79088b2d476cbb3.png"},{"id":93783122,"identity":"608a3fa0-a1da-4058-9a3b-263285bb4f8d","added_by":"auto","created_at":"2025-10-17 13:36:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1536308,"visible":true,"origin":"","legend":"\u003cp\u003eStructural survey of the available 3D structures of GABA\u003csub\u003eA\u003c/sub\u003eRs. A) Examples of previously resolved GABA\u003csub\u003eA\u003c/sub\u003eR structures, color coded based on subunits (Green: β, Blue: γ, Red: α, Orange: π, Yellow: ρ, Orange: δ) in complex with different small molecules (ABU: GABA, FYP: Flumazenil, QI0: Basmisanil, HSM: Histamine, EPE: HEPES, VZA: TPMPA) B) A survey of composition frequency of GABA\u003csub\u003eA\u003c/sub\u003eR’s resolved structures. *The pore-facing glycosylation sites are mutated in these structures.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/99cfc468faa6a3253a54f4e8.png"},{"id":93783124,"identity":"ff0a363e-c883-4556-b9ee-2605abd6979e","added_by":"auto","created_at":"2025-10-17 13:36:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1122142,"visible":true,"origin":"","legend":"\u003cp\u003eSequence analysis of the GABA\u003csub\u003eA\u003c/sub\u003eRs. A) Phylogenetic tree of GABA\u003csub\u003eA\u003c/sub\u003eRs subunits, highlighting the close evolutionary relationship between γ and α subunits. B) Multiple sequence alignment (MSA) of different subunits within human GABA\u003csub\u003eA\u003c/sub\u003eRs. C) MSA of α subunits across different species. D) MSA of the different members of the pLGIC family that can form homomers.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/c37ad8851d7fd43637a24450.png"},{"id":93784551,"identity":"d1321794-2cd4-4e8e-ab65-d8f8596da287","added_by":"auto","created_at":"2025-10-17 13:52:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2152778,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of additional glycosylation in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG \u003c/sup\u003eon salt bridges at ECD subunit interface. A) Distribution of terminal mannoses in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e and βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ (Blue: CARA attached to α\u003csub\u003eB\u003c/sub\u003e, Orange: CARB attached to α\u003csub\u003eD\u003c/sub\u003e, Green: CARC attached to γ\u003csub\u003eE\u003c/sub\u003e). B) The subunit interface salt bridges significantly altered between βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e and βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ. C) Disrupted salt bridges at GABA-binding site located at β\u003csub\u003eC\u003c/sub\u003e - α\u003csub\u003eD\u003c/sub\u003e interface. D) The disrupted salt bridge at the α+/β- interface. E) The altered salt bridges by the additional glycan at similar locations in the lower parts of ECD. F) Multiple sequence alignment shows several affected salt bridges are located at equivalent positions at the lower ECD.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/8ff28af326f1df3bac90952f.png"},{"id":93784212,"identity":"642d272e-0dc8-4d0f-a723-c44248c4f900","added_by":"auto","created_at":"2025-10-17 13:44:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2301464,"visible":true,"origin":"","legend":"\u003cp\u003eRearranged hydrogen bond due to the introduction of the third glycan in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e. A) Hydrogen bond occupancy comparison between βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e and βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ at ECD. B) The overall view of altered hydrogen bond clusters in the structure, C) Zoom in view of affected residue pairs at γ\u003csub\u003eE\u003c/sub\u003e-β\u003csub\u003eA\u003c/sub\u003e interface, D) at α\u003csub\u003eB\u003c/sub\u003e-β\u003csub\u003eC\u003c/sub\u003e interface, E) GABA binding site, and F) the benzodiazepine binding site. G) MSA of hGABA\u003csub\u003eA\u003c/sub\u003eR showcasing the conservation of the identified threonines involved in critical hydrogen bonds. H) Top view of the threonines with significant change in hydrogen bond occupancy.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/7caf2bd125c8044287a146d0.png"},{"id":93783129,"identity":"39c99739-6899-4890-a054-4c35ee449c28","added_by":"auto","created_at":"2025-10-17 13:36:41","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1525019,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of the third glycan in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG \u003c/sup\u003eon the TMD and gating dynamics. A) AG pore radius over time showing dynamic switching between closed and constricted states in the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e. B) Average AG radius across four independent simulations. C ) Representative water wire continuity at the activation gate in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG \u003c/sup\u003eversus\u003csup\u003e \u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ. D) Water occupancy at the AG is lower across trajectories in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/3bea5e6c6d668ec01204658d.png"},{"id":93784214,"identity":"7dc2cbb7-3d3e-4843-82d5-b5130dad6e6f","added_by":"auto","created_at":"2025-10-17 13:44:41","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1421732,"visible":true,"origin":"","legend":"\u003cp\u003eAllosteric coupled pathway connecting GABA binding site to AG. A) The pathways in each subunit and the corresponding recurrence in independent runs mapped on α - β MSA. pathway from each independent run (green, orange, blue, red) is visualized within B) β\u003csub\u003eC\u003c/sub\u003e subunit and C) α\u003csub\u003eD\u003c/sub\u003e subunit, with black spheres representing the residues with 75% recurrence. The thickness of the edges corresponds to the correlation value between the nodes.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/c2e25108d44979a2a7d5f664.png"},{"id":93784213,"identity":"aa7e6356-6d68-44f3-aac3-5c8fbc18d657","added_by":"auto","created_at":"2025-10-17 13:44:41","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":990176,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of additional α subunit with three pore-facing glycosylations in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e. A) Changes in salt bridges at the native interfaces. B) changes in hydrogen bonds at native interfaces. C) pore radius comparison at AG, 2\u003csup\u003end\u003c/sup\u003e HCS, and DG. D) Reduction in water occupancy in lower parts of TMD in the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e system compared with βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/e971822bc04632aab5f08bcd.png"},{"id":93784554,"identity":"f31e3fe0-050c-4146-9697-c3629a96b097","added_by":"auto","created_at":"2025-10-17 13:52:41","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":992700,"visible":true,"origin":"","legend":"\u003cp\u003eEffect of glycosylation on adjacent α subunits in βα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003eβγ. A) Changes in salt bridges at the native interfaces. B) changes in hydrogen bonds at native interfaces. C) pore radius comparison at AG, 2\u003csup\u003end\u003c/sup\u003e HCS, and DG. D) Reduction in water occupancy in lower parts of TMD in the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e system compared with βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/7723592aacb497c7b34c715e.png"},{"id":93785564,"identity":"2d489afe-0543-448d-930a-e786f6bdd416","added_by":"auto","created_at":"2025-10-17 14:00:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":14200207,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/c4a6f994-295f-4176-912d-01789b0ad3fe.pdf"},{"id":93783130,"identity":"37f80bff-99ec-4ae0-a491-3a6f4280a44b","added_by":"auto","created_at":"2025-10-17 13:36:41","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":11776651,"visible":true,"origin":"","legend":"Supplementary Materials for A Pore-Facing Glycan Determines GABAA Receptor Subunit Stoichiometry and Gating Behavior","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7743743/v1/038fbd46519e39c964676776.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"A Pore-Facing Glycan Determines GABAA Receptor Subunit Stoichiometry and Gating Behavior","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eγ-Aminobutyric acid type A receptors (GABA\u003csub\u003eA\u003c/sub\u003eRs) are integral to the central nervous system (CNS), functioning as chloride ion-selective channels that mediate inhibitory neurotransmission\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. These GABA\u003csub\u003eA\u003c/sub\u003eRs play critical roles in modulating neuronal inhibition, synaptic plasticity, and homeostatic control\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. GABA\u003csub\u003eA\u003c/sub\u003eRs dysfunction has been implicated in a wide range of neurological and psychiatric disorders, including epilepsy, schizophrenia, anxiety disorders, depression, and substance abuse\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12 CR13\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAs pentameric ligand-gated ion channels (pLGICs), GABA\u003csub\u003eA\u003c/sub\u003eRs assemble into pentamers from a diverse pool of 19 subunits (α1\u0026ndash;6, β1\u0026ndash;3, γ1\u0026ndash;3, ρ1\u0026ndash;3, δ, ε, π, and θ)\u003csup\u003e4,15,16\u003c/sup\u003e. Each subunit comprises a bulky extracellular domain (ECD) that forms the orthosteric binding sites for GABA and other ligands and four transmembrane helices that constitute the transmembrane domain (TMD), wherein the activation gate and desensitization gates of the channel are located\u003csup\u003e\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Although the extensive repertoire of subunits could lead to a theoretical array of ~\u0026thinsp;490,000 possible pentameric combinations, only a limited number of assemblies are observed \u003cem\u003ein vivo\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e. Among the possible compositions, the αβγ is identified as the most predominant GABA\u003csub\u003eA\u003c/sub\u003eRs assembly in the brain\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. For instance, over 60% of synaptic GABA\u003csub\u003eA\u003c/sub\u003eRs are composed of the α1β2γ2 subunit composition\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e while the α2β3γ2 isoform accounts approximately 13% of the total GABA\u003csub\u003eA\u003c/sub\u003eRs population\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Overall, the β-α-β-α-γ is believed to be the most abundant form of this channel\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe physiology and pharmacology of GABA\u003csub\u003eA\u003c/sub\u003eRs are shaped by their pentameric subunit composition\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, which dictates receptor trafficking, ligand binding, drug responses, gating properties, and distinct forms of neuronal inhibition or cellular signalling\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Different subunit combinations target receptors to specific subcellular compartments. For example, γ2-containing receptors predominantly localize to synapses, whereas δ-containing receptors are primarily extrasynaptic, mediating phasic and tonic inhibition respectively\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Different assemblies also form unique subunit interfaces, enabling diverse ligand/drug binding and functional responses\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. For instance, the GABA-binding site is located at the β+/α- interface, while the histamine-binding site is situated at the β+/β- interface\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Another example of the significance of subunit composition is that γ2 containing GABA\u003csub\u003eA\u003c/sub\u003eRs (e.g., α1β2γ2, α2β3γ2, α3β3γ2) are benzodiazepine-sensitive, while δ-containing receptors (e.g., α4β2δ, α6β3δ) are benzodiazepine-insensitive but highly responsive to neurosteroids like allopregnanolone\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe assembly rules and molecular determinants governing native GABA\u003csub\u003eA\u003c/sub\u003eRs remain largely unknown, representing a fundamental challenge in understanding the biophysics and pharmacology of the GABA\u003csub\u003eA\u003c/sub\u003e receptors. Extensive research has been conducted to elucidate the subunit composition of GABA receptors using biochemical, electrophysiological, and structural techniques. Experiments using concatenated constructs have revealed certain assembly patterns governing receptor stoichiometry, localization, subunit-specific preferential interactions, and probable/non-probable structure compositions\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. High-resolution cryo-EM studies have uncovered representative subunit assemblies, revealing structural differences that shape receptor function and drug-binding properties\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. These studies have identified a number of distinct native GABA\u003csub\u003eA\u003c/sub\u003eR pentamers, including canonical and non-canonical subunit assemblies. Among all available GABA\u003csub\u003eA\u003c/sub\u003eR structures, most of these subunit assemblies follow an XαXαX assembly pattern, with no native pentamers containing more than two α subunits or two adjacent α subunits. However, the underlying mechanisms behind this puzzling phenomenon remain unclear.\u003c/p\u003e\u003cp\u003e\u003cem\u003eN\u003c/em\u003e-linked glycosylation of GABA\u003csub\u003eA\u003c/sub\u003eRs has been hypothesized to affect the XαXαX assembly pattern\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, but it has not yet been investigated as a potential molecular determinant for receptor assembly. Among post-translational modifications, \u003cem\u003eN\u003c/em\u003e-linked glycosylation is a critical regulator of protein folding, trafficking, and function in ligand-gated ion channels\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. In GABA\u003csub\u003eA\u003c/sub\u003eRs, glycosylation can be seen either as pore-facing glycans or surface glycans, influencing receptor biogenesis, gating, and assembly\u003csup\u003e\u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Glycosylation of GABA\u003csub\u003eA\u003c/sub\u003eRs are mostly emphasized for their impact on potential subunit interactions and shielding of ligand-binding sites\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e, while fewer studies have investigated whether glycosylation alters receptor subunit assembly pattern. Cryo-EM studies have characterized these important glycan structures, including a Man-8 structure at N123 in the extracellular domain (ECD) of the α subunits, positioned centrally within the receptor\u0026rsquo;s pore\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. This pore-facing glycan is of particular interest owing to its spatial location, which is hypothesized to impact pentameric composition, structural stability, or ion permeability\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Interestingly, any resolved structure that involves an α homomeric structure has been subjected to extensive modifications that would disrupt the natural pore-glycosylation on α subunits\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Despite the glycan\u0026rsquo;s critical location, the molecular mechanisms by which pore-facing glycans affect channel composition and gating remain largely unexplored.\u003c/p\u003e\u003cp\u003eWe hypothesize that the presence of pore-facing glycans at α1N123 likely prevents the formation of pentamers with more than two α subunits or with two adjacent α subunits, due to steric clashes. This steric constraint may promote the incorporation of β and γ subunits, thereby favoring the canonical XαXαX assembly pattern. In this context, this pore-facing glycan may serve as a molecular determinant guiding subunit composition and spatial arrangement for receptor assembly. To test our hypothesis, we investigate the structural and functional implications of high-mannose glycosylation at N123 of the α1 subunit using molecular modeling and molecular dynamics (MD) simulations. Different glycosylated and non-glycosylated systems and putative assemblies of the channel were investigated. Based on the detailed analysis of MD trajectories, we characterized the impact of these structural variations on the subunit interface, their allosteric effects on TMDs, and the coupling mechanisms underlying signal propagation.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMolecular Dynamics Simulation\u003c/h2\u003e\u003cp\u003e\u003cem\u003eSystem setup\u003c/em\u003e: All atomic models of GABA\u003csub\u003eA\u003c/sub\u003eR were constructed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) based on the wild-type (WT) cryo-EM structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA)\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e (PDB ID: 6X3Z) with and without the pore-facing glycans. Putative assemblies of the channel were constructed by structural alignment of appropriate subunits on the cryo-EM structure using VMD\u0026rsquo;s\u003csup\u003e49,50\u003c/sup\u003e MultiSeq\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. For all the MD simulations, the channel comprising different assemblies was embedded in a 115x115 \u0026Aring; bilayer composed of POPC lipids after the assignment of its orientation through the PPM 2.0 server\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e and solvated in 150 mM NaCl using the web service CHARMM-GUI\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Most residues were assigned their default protonation state at pH 7.0 based on the PROPKA3\u003csup\u003e55\u003c/sup\u003e prediction obtained. The GABA molecule was protonated using CHARMM Ligand Reader \u0026amp; Modeler\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. The man8 structures were constructed and attached to both α1N138 residues in CHARMM-GUI Glycan Reader \u0026amp; Modeler\u003csup\u003e\u003cspan additionalcitationids=\"CR58\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Disulfide bonds were introduced at α\u003csub\u003eB, D\u003c/sub\u003e 166\u0026ndash;180, β\u003csub\u003eA, C\u003c/sub\u003e 160\u0026thinsp;\u0026minus;\u0026thinsp;74, and γ\u003csub\u003eE\u003c/sub\u003e 190\u0026ndash;204 to conserve the integral Cys-loop structure. The total number of atoms in each system was approximately 165,000.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eSimulation protocol\u003c/strong\u003e\u003cp\u003eThe CHARMM36m force field for protein\u003csup\u003e\u003cspan additionalcitationids=\"CR61\" citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e, lipids\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e, ions\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e, and glycans \u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e were used. Explicit water was described with the TIP3P model\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. All the simulations were performed under constant number of particles N, pressure P, and temperature T (NPT) conditions using the Nos\u0026eacute;\u0026minus;Hoover Langevin piston method to maintain the pressure at 1 atm and a Langevin thermostat to maintain the temperature at 310 K\u003csup\u003e67\u003c/sup\u003e. The oscillation period of the piston was set at 100 fs and the damping time scale at 50 fs. Long-range electrostatic interactions were calculated using the particle mesh Ewald algorithm\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e with a grid spacing of 1 \u0026Aring;. All simulations were performed under tetragonal periodic boundary conditions to the simulation box to overcome finite-size effects and mimic bulk-like properties. Long-range electrostatic interactions were calculated using the particle mesh Ewald algorithm\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. Short-range nonbonded interactions were calculated with a cutoff of 12 \u0026Aring;, and the application of a smoothing decay started to take effect at 10 \u0026Aring;. The simulations used the SHAKE algorithm\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e to fix bond distances involving hydrogen atoms and applied hydrogen mass repartitioning\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e to reweight hydrogen atoms, allowing for a 4 fs time step for MD simulations. After 5000 steps of minimization and equilibrations for 2 ns with harmonic positional restraints (k\u0026thinsp;=\u0026thinsp;1 kcal/mol/\u0026Aring;\u0026sup2;), each equilibrated system was simulated for at least 2 \u0026micro;s using NAMD2.14\u003csup\u003e71\u003c/sup\u003e and NAMD3\u003csup\u003e72\u003c/sup\u003e on expanse or Anton3 resulting in a total simulation time of 28 \u0026micro;s. Trajectories were then analyzed using VMD\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e and Python scripts.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eProduction simulations on Anton3\u003csup\u003e73\u003c/sup\u003e were performed under the NPT conditions using Desmond\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e with the Multigrator integrator\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. Semi-isotropic pressure control was applied using a Monte Carlo barostat and the antithetic thermostat\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e,\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e to maintain a pressure of 1.0 atm and a temperature of 310 K. A 2.5 fs time step was used with RESPA\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e for multiple time-scale integration. Electrostatic interactions were computed using the u-series method and Midtown splines\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e,\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. Nonbonded interactions were tapered using a force-shift scheme with a 12 \u0026Aring; cutoff.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAnalysis and Visualization\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eSalt Bridge Network Analysis\u003c/strong\u003e\u003cp\u003eTo assess the salt bridge network at the subunit interfaces, we monitored the distance between oppositely charged residues over time throughout the simulations. A salt bridge was defined as the presence of the terminal carbon atom of glutamate or aspartate side chain within 4 \u0026Aring; of either the terminal carbon of an arginine or the terminal nitrogen of a lysine, within a given frame. The analysis was conducted across all independent simulation runs for the same construct. The distances were standardized and averaged, and standard errors were calculated. Salt-bridge pairs were included in the comparison between systems only if the occupancy difference exceeded 10%. This strategy enabled a detailed and comprehensive assessment of inter-subunit salt bridge networks.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eHydrogen Bond Analysis\u003c/strong\u003e\u003cp\u003eThe hydrogen bonds at the interface were analyzed using the Hydrogen Bond module in VMD. Polar atoms (N, O, S, F) were evaluated with a distance cutoff of 3.5 \u0026Aring; and a donor-hydrogen-acceptor angle threshold of 20\u0026deg;. The occupancy of each hydrogen bond pair was calculated as the percentage of frames in which the bond was present across the simulation trajectories, averaged over all frames, and the standard error was computed on the basis of multiple independent runs. Only hydrogen bond pairs with an occupancy difference greater than 10% between systems were included in the final comparison.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eECD expansion analysis\u003c/strong\u003e\u003cp\u003eExpansion of the protein's ECD was assessed by tracking the 2D (on XY plane) center of mass (COM) of the ECD for each subunit throughout each simulation trajectory using MDAnalysis\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. For each frame, the area enclosed by these COM points was determined using the ConvexHull function in python library SciPy\u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. The resulting area values were averaged across simulation replicas and compared between different conditions to evaluate differences in ECD expansion.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eInternal Loop RMSD Analysis\u003c/em\u003e: The flexibility of internal loops was assessed by calculating the root-mean-square deviation (RMSD) of the backbone atoms for the equivalent loop in each subunit (α: residue 130\u0026ndash;143, β: 124\u0026ndash;137, γ: 154\u0026ndash;167) for every frame, using the first frame as the reference. The RMSD values were averaged across trajectories and compared between different conditions to evaluate the flexibility of the internal loop.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eGlycan distribution analysis\u003c/strong\u003e\u003cp\u003eThe distribution and orientation of glycans were measured by tracking coordinates of the Cα of each glycosylated asparagine (αN138, γN162) and the terminal mannose residue of each glycan for every frame. This approach allowed for tracking glycan movement and orientation throughout the simulations.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003ePore radius analysis\u003c/em\u003e: The pore diameter along the z-axis (vector [0,0,1]) was analyzed using the HOLE2 module\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e of the MDAnalysis package (version 2.6.1)\u003csup\u003e83\u003c/sup\u003e to quantify changes in pore radius. The central reference point in each simulation was determined as the collective center of mass (COM) of Cα residues forming the activation gate. The end radius for the HOLE analysis was set to 25 \u0026Aring;, and the pore radius at regions of interest was tracked throughout each simulation replica. Three distinct gate regions were specifically analyzed: 1) the activation gate (AG) located at position 9\u0026prime;\u003csup\u003e84\u003c/sup\u003e, the second hydrophobic constriction site (2nd HCS), corresponding to residue α1V257, and the homologous position in other subunits, crucial for maintaining the structural integrity of the pore lining, proper packing of the channel-forming helices, and overall channel function\u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e,\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/sup\u003e, and the desensitization gate (DG) at -2\u0026prime;\u003csup\u003e84\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eWater occupancy analysis\u003c/strong\u003e\u003cp\u003eWater occupancy was assessed by tracking water molecules within a 5\u0026times;5 \u0026Aring;\u003csup\u003e2\u003c/sup\u003e area along the z-axis at the central pore. The position of each water molecule was determined based on the coordinates of its oxygen atom. Water distribution along the channel pore was quantified by counting water molecules within 2 \u0026Aring; bins along the z-axis throughout the simulation trajectory. These values were averaged across independent simulation runs. To evaluate water permeability as a proxy for channel functionality, we used a representative water molecule radius of 1.25\u0026Aring;\u003csup\u003e\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e for cutoff, classifying regions as permeable (radius\u0026thinsp;\u0026gt;\u0026thinsp;1.25 \u0026Aring;) or non-permeable (radius\u0026thinsp;\u0026le;\u0026thinsp;1.25 \u0026Aring;). The number of permeable versus non-permeable pore in each region was recorded accordingly. Statistical significance was evaluated using the chi-squared test, complemented by a sensitivity test to assess robustness, using Scipy and statsmodels.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAllosteric coupling analysis\u003c/strong\u003e\u003cp\u003eTo characterize the allosteric coupling between the ECD and transmembrane domain (TMD), we performed dynamical network analysis using simulation trajectories. The analysis involved multiple steps, including contact map generation, network construction, and pathway extraction to identify the coupling pathway and key residues mediating structural communication within the protein. Network configuration included the protein and glycan, with hydrogen atoms excluded. Network nodes were defined as backbone Cα atoms for the protein and O5 atoms for the glycans. To avoid artificially short paths, edges between nodes representing neighboring residues (e.g., residue \u003cem\u003ei\u003c/em\u003e and \u003cem\u003ei\u0026thinsp;+\u0026thinsp;1\u003c/em\u003e) were excluded to eliminate trivial correlations arising from backbone adjacency, allowing the analysis to focus on long-range communication within the system. Network analysis was executed using VMD\u0026rsquo;s NetworkView package\u003csup\u003e\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e, which processed contact maps from each independent run. The shortest paths between key functional residues were extracted using suboptimal path algorithm\u003csup\u003e\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e. The algorithm computed frequent residue paths, identifying highly connected residues that serve as communication hubs. The betweenness centrality of each node was computed to rank residues based on their importance in information transfer. The most frequently visited residues in each path were extracted. Residues appearing in multiple independent runs were considered conserved network hubs contributing to allosteric signaling. VMD, along with Python\u003csup\u003e\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e\u003c/sup\u003e packages Numpy\u003csup\u003e\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e\u003c/sup\u003e, Pandas\u003csup\u003e\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e, and Matplotlib\u003csup\u003e\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u003c/sup\u003e, were used to visualize the data from all of the analyses.\u003c/p\u003e\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eEvolutionary Conservation and Specificity of the Pore-Facing Glycan in the α Subunits of GABA\u003csub\u003eA\u003c/sub\u003eRs\u003c/h2\u003e\u003cp\u003eA survey of 85 available 3D structures of GABA\u003csub\u003eA\u003c/sub\u003eR in the PDB database (till 2025-02-22) shows the dominance of the αβγ stoichiometry (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The majority of the entries in this category take a βαβαγ configuration\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan additionalcitationids=\"CR94 CR95 CR96\" citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e, with recent structures highlighting the possibility of incorporating different α subunits within the same assembly\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Interestingly, a few structures are reported with more than two α subunits (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). However, such structures undergo substantial modifications at the extracellular domain that remove native \u003cem\u003eN\u003c/em\u003e-glycosylation sites, resulting in ECDs that differ significantly from natural α subunits. Notably, in all available structures with a native α subunits, the first few N-acetylgalactosamine (GalNAc) residues of the high mannose glycan are observed, whereas these glycans are entirely absent in the ECD-modified α homomeric assemblies or ααααγ forms. This points toward the possibility for the pore-facing glycans to hold the key to GABA\u003csub\u003eA\u003c/sub\u003eR assembly pattern.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eMultiple sequence alignment of human GABA\u003csub\u003eA\u003c/sub\u003eR subunits revealed that the pore-facing \u003cem\u003eN\u003c/em\u003e-glycosylation site at α1N138, is highly conserved across all α subunits (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Positioned centrally within the ECD pore, this hallmark glycosylation site is uniquely observed in the α subunits of GABA\u003csub\u003eA\u003c/sub\u003eR (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). This glycosylation sequon lies within the loop A-E linker region. Both the sequon and the loop itself show high evolutionarily conservation among different α subunits across various species (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Interestingly, the pore-facing glycan appears unique to vertebrates, including birds, fish, reptiles, and mammals, whereas more evolutionarily distant GABA\u003csub\u003eA\u003c/sub\u003eR α\u003csub\u003elike\u003c/sub\u003e subunits found in fruit flies lack the asparagine residue necessary for \u003cem\u003eN\u003c/em\u003e-glycosylation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Notably, this pore-facing glycosylation site is absent in any other GABA\u003csub\u003eA\u003c/sub\u003eR subunits (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and any other known member of the pLGIC superfamily (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Sequence analysis also identified a tryptophan residue (γ2W162) occupying the homologous glycosylation site in the γ2 subunit (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Phylogenetic analysis indicates closer evolutionary relatedness between γ and α subunits than other GABA\u003csub\u003eA\u003c/sub\u003eR subunit classes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), suggesting γ2W162 as a promising target for engineering a comparable pore-facing glycosylation site. Mutating γ2W162 to asparagine would introduce the sequon for \u003cem\u003eN\u003c/em\u003e-glycosylation to attach a third glycan in the central pore without significantly altering the native channel structure.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eThe native, mutated, and putative models to test the structural roles of pore-facing glycans\u003c/h3\u003e\n\u003cp\u003eAtomic models of GABA\u003csub\u003eA\u003c/sub\u003eR were constructed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) based on the WT cryo-EM structure (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA)\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e (PDB ID: 6X3Z) with and without the glycans (βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ, βαβαγ). Mutation W162N was introduced at the homologous position of α1N123 on the γ2 subunit of the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e system (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD), to explore the channel's ability to accommodate a third glycan without significantly disrupting the native structure. Putative assemblies with three α subunits and three pore-facing glycans (βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE), or with two adjacent α subunits bearing glycans (βα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003eβγ,Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF), were also constructed to probe their structural stability. Non-glycosylated counterparts (βαβαα and βααβγ) served as controls. All these putative assembly models were generated by structural alignment of equivalent subunits to the cryo-EM structure using VMD\u0026rsquo;s MultiSeq\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Each assembly was simulated for at least 2 \u0026micro;s to investigate the structural impacts of the pore-facing glycans across different pentameric configurations.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eThe additional pore-facing glycan disrupts key native inter-subunit contacts in the ECD of βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e\u003c/h2\u003e\u003cp\u003eThe incorporation of the third glycan at γ\u003csub\u003eE\u003c/sub\u003e ECD in the engineered central pore in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e leads to altered glycan localization and the disruption of native inter-subunit salt bridges and hydrogen bonds. Both βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e and βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ were simulated in four independent 2-\u0026micro;s runs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC\u0026amp;D). Comparison of these trajectories revealed reproducible patterns in the structural impacts of the three pore-facing glycans. Firstly, this additional glycan significantly (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036) reduces the conformational flexibility of the glycan attached to α\u003csub\u003eD\u003c/sub\u003e in the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e (RMSF:4.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45) compared to the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ (RMSF:6.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93) system (SFig. 1). The flexibility of α\u003csub\u003eB\u003c/sub\u003e glycan is also reduced, but this effect is not statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.22). The visualization of the terminal glycans shows that the additional γ\u003csub\u003eE\u003c/sub\u003e-attached glycan forces the α\u003csub\u003eD\u003c/sub\u003e-attached glycan to be concentrated at the α\u003csub\u003eB\u003c/sub\u003e - β\u003csub\u003eC\u003c/sub\u003e and β\u003csub\u003eC\u003c/sub\u003e - α\u003csub\u003eD\u003c/sub\u003e interface (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA), sterically repulsing those subunits away from each other.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThis structural rearrangement changes the native contacts at the subunit interfaces, resulting in a substantial reduction (\u0026gt;\u0026thinsp;10%) in native salt-bridge occupancy for most affected pairs (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). This reduced salt bridge occupancy is particularly pronounced at the GABA binding site located at the β\u003csub\u003eC\u003c/sub\u003e - α\u003csub\u003eD\u003c/sub\u003e interface (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), whereas the β\u003csub\u003eA\u003c/sub\u003e - α\u003csub\u003eB\u003c/sub\u003e binding site is less affected (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). This result aligns with the observation that the α\u003csub\u003eD\u003c/sub\u003e-attached glycan repulse the α\u003csub\u003eB\u003c/sub\u003e - β\u003csub\u003eC\u003c/sub\u003e and β\u003csub\u003eC\u003c/sub\u003e - α\u003csub\u003eD\u003c/sub\u003e interface. Notably, several disrupted interactions, such as β\u003csub\u003eA\u003c/sub\u003e K126 - α\u003csub\u003eB\u003c/sub\u003e D90, α\u003csub\u003eB\u003c/sub\u003e K132 - β\u003csub\u003ec\u003c/sub\u003e D72, β\u003csub\u003ec\u003c/sub\u003e K126 - α\u003csub\u003eD\u003c/sub\u003e D90, and γ\u003csub\u003eE\u003c/sub\u003e K156-β\u003csub\u003eA\u003c/sub\u003e D72, are altered at nearly symmetrical locations across the subunit interfaces (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). In each of these pairs, the lysine residues occupy homologous positions (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF), whereas the aspartates are situated in similar locations within adjacent β sheets (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF, Supplementary Fig.\u0026nbsp;1), in proximity to different orthosteric binding sites. Among these, two pairs (β\u003csub\u003ec\u003c/sub\u003e K126 - α\u003csub\u003eD\u003c/sub\u003e D90 and α\u003csub\u003eB\u003c/sub\u003e K132 - β\u003csub\u003ec\u003c/sub\u003e D72) near the glycan-concentrated region exhibited reduced salt-bridge occupancy, whereas the other two pairs (γ\u003csub\u003eE\u003c/sub\u003e K156 - β\u003csub\u003eA\u003c/sub\u003e D72 and β\u003csub\u003eA\u003c/sub\u003e K126 - α\u003csub\u003eB\u003c/sub\u003e D90), located away from this region showed increased salt bridge occupancy (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, E). Although most disruptions occurred within the ECD subunit interface, several important changes in other key regions were observed, including α\u003csub\u003eB\u003c/sub\u003e K306 - β\u003csub\u003eC\u003c/sub\u003e E76 at the ECD-TMD interface (Supplementary Fig.\u0026nbsp;1) and α\u003csub\u003eD\u003c/sub\u003e K339 - γ\u003csub\u003eE\u003c/sub\u003e D299 within internal regions of TMD ( Supplementary Fig.\u0026nbsp;1).\u003c/p\u003e\u003cp\u003eSubunit rearrangements were also associated with altered hydrogen bonds at subunit interfaces which clustered into three primary regions, i.e., ECD, ECD-TMD interface, and TMD. (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, SFig. 2). At the ECD region, these re-arrangements were mostly observed around the discussed glycan-concentrated region, orthosteric and allosteric ligand-binding sites. At the β\u003csub\u003eC\u003c/sub\u003e\u0026ndash;α\u003csub\u003eD\u003c/sub\u003e interface, located behind the GABA binding site (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), several hydrogen bonds exhibited increased occupancy, including β\u003csub\u003eC\u003c/sub\u003e D125\u0026ndash;α\u003csub\u003eD\u003c/sub\u003e H137 and β\u003csub\u003eC\u003c/sub\u003e T120\u0026ndash;α\u003csub\u003eD\u003c/sub\u003e T140, whereas others, such as β\u003csub\u003eC\u003c/sub\u003e D119\u0026ndash;α\u003csub\u003eD\u003c/sub\u003e N114, showed reduced occupancy. A similar pattern was observed at the α\u003csub\u003eD\u003c/sub\u003e\u0026ndash;γ\u003csub\u003eE\u003c/sub\u003e interface, which comprises the benzodiazepine binding site (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA,E). In this region, hydrogen bonds such as α\u003csub\u003eD\u003c/sub\u003e F128\u0026ndash;γ\u003csub\u003eE\u003c/sub\u003e H163 and α\u003csub\u003eD\u003c/sub\u003e S134\u0026ndash;γ\u003csub\u003eE\u003c/sub\u003e T164 increased in frequency, whereas interactions including α\u003csub\u003eD\u003c/sub\u003e D125\u0026ndash;γ\u003csub\u003eE\u003c/sub\u003e T164, α\u003csub\u003eD\u003c/sub\u003e F128\u0026ndash;γ\u003csub\u003eE\u003c/sub\u003e H161, and α\u003csub\u003eD\u003c/sub\u003e T126\u0026ndash;γ\u003csub\u003eE\u003c/sub\u003e T164 showed decreased occupancy. Overall, this analysis indicates that increased glycan-subunit interactions in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e drive subunits separation at the upper surface of the ECD, while promoting closer contacts among residues in the lower, internal regions and loops.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eInterestingly, at nearly all subunit interfaces except β\u003csub\u003eA\u003c/sub\u003e\u0026ndash;α\u003csub\u003eB\u003c/sub\u003e, a hydrogen bond between two highly conserved threonine residues (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG,H) was either significantly strengthened or significantly weakened (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). This threonine pair is located directly behind the orthosteric ligand-binding sites for GABA, benzodiazepine, and histamine. The second threonine in the α subunits contributes to the \u003cem\u003eN\u003c/em\u003e-glycosylation sequon (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). Thus, alterations in this conserved hydrogen bond are likely affected by the presence of glycans and may have a direct structural impact on the ECD domain.\u003c/p\u003e\u003cp\u003eAt the ECD\u0026ndash;TMD interface, a second cluster of altered hydrogen bonds was identified, primarily involving the TM2\u0026ndash;TM3 linkers and upper TMD regions (Supplementary Fig.\u0026nbsp;2). The most significantly affected interface in this region was γ\u003csub\u003eE\u003c/sub\u003e\u0026ndash;β\u003csub\u003eA\u003c/sub\u003e, a potential binding site for steroid analogues and lipids (Supplementary Fig.\u0026nbsp;2). Structurally homologous positions at the propofol binding site in β\u003csub\u003eA\u003c/sub\u003e\u0026ndash;α\u003csub\u003eB\u003c/sub\u003e, as well as β\u003csub\u003eC\u003c/sub\u003e\u0026ndash;α\u003csub\u003eD\u003c/sub\u003e interfaces, also exhibited disruption in their upper TMD regions. A third cluster of disrupted hydrogen bonds was located at the intracellular side of the TMD adjacent to TM1\u0026ndash;TM2 linkers, regions known to bind neurosteroids, cholesterol, and other lipids (Supplementary Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003eThe impact of the additional glycan extends beyond the disruption of native inter-subunit contacts. In the ECD, it also alters glycan interactions with important internal loops. Notably, the simulated pore-facing glycan of the γ subunit is positioned in close proximity to the functionally important A-E linker (Supplementary Fig.\u0026nbsp;1F), which contains the glycosylation sequon on the α subunit and is located behind the GABA binding site. RMSF analysis reveals a general decrease in loop flexibility, with the most pronounced reductions observed in the β\u003csub\u003eC\u003c/sub\u003e and γ\u003csub\u003eE\u003c/sub\u003e (SFig. 1F). This diminished internal loop flexibility provides an additional mechanism by which the third glycan may impair channel function.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePresence of three pore-facing glycans in βαβαγ* lead to TMD closure at the activation gate\u003c/h3\u003e\n\u003cp\u003eThe primary difference between the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e and βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ systems in the TMD are at the activation gate. Tracking the pore radius along the z-axis using HOLE analysis revealed a rapid closure of the AG where the pore radius is significantly (χ\u0026sup2; = 4717.44, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) reduced from 1.38 \u0026Aring; in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ to 1.19 \u0026Aring; in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA, B; SFig. 4). This increases the probability of channel closure (1.25 \u0026Aring; as the threshold) from 30.2% in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ to 59.8% in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e. Consistently, the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ system maintained a continuous water wire through the gate for nearly 43% of the simulation time, whereas in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e, this number dropped to 11% (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC, D). This shift toward impermeable conformations likely results from a structural transition to a resting-like or deep desensitized conformation. The hallmark of this transition is the closure of the activation gate within the TMD, occurring at the crossover of key residues: α\u003csub\u003eB,D\u003c/sub\u003e L291 β\u003csub\u003eA,C\u003c/sub\u003e L283, and γ\u003csub\u003eE\u003c/sub\u003e L313 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Interestingly, the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e activation gate exhibited a distinct rapid-switching behavior, characterized by repeated transitions between a narrowed pore radius of ~\u0026thinsp;1.25 \u0026Aring; and a fully sealed state (~\u0026thinsp;0.6 \u0026Aring;) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). This two-state-like switching behavior was consistently observed across all four βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e replicas. In contrast, the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ system predominantly maintained a pore radius above 1.25 \u0026Aring;. Furthermore, in a βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ* with the same γ2W162 mutation without the glycosylation presence, the pore radius at AG remains similar (1.35 \u0026Aring;) to that of the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ system (1.38 \u0026Aring;) (SFig. 4), suggesting that the the observed dynamic behavior at this gate is driven by the glycan itself, rather than the mutation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eEliminating all pore-facing glycans in the alternative pentameric configuration, βαβαγ, did not result in significant structural changes in either the ECD or the TMD, aside from modest rearrangements at the subunit interfaces (SFig. 3). The convex hull of the ECD remained stable, and the pore radius in this region was comparable to that of the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ. Changes in internal loop flexibility were minor and lacked a consistent pattern. Water-occupancy patterns of βαβαγ remained comparable to those observed in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003e\u003cem\u003eγ\u003c/em\u003e at the activation gate with only a subtle decrease at desensitization gate consistent with the latter's minor decrease in pore radius at DG (SFig. 3, 4). Overall, in the absence of pore-facing glycans, the channel βαβαγ maintains structural and dynamic properties similar to those of βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003e\u003cem\u003eγ\u003c/em\u003e, without substantial alterations in dynamic behavior.\u003c/p\u003e\n\u003ch3\u003eAn Allosteric Network Coupling ECD Disruption to Activation Gate Closure\u003c/h3\u003e\n\u003cp\u003eThe highly reproducible conformational changes observed in both the ECD and TMD across all βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e trajectories, particularly disruptions of native contacts in the ECD and activation-gate closure in the TMD, strongly suggest the presence of an allosteric coupling that transmits the structural effects of the additional glycan from the ECD to the TMD. Dynamical network analysis within each subunit revealed a consistent pathway originating from charged residues at the GABA binding site and extending to the activation-gate in the TMD (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). These pathways commonly traverse the Cys-loop interface and the TM2-TM3 linker at the ECD-TMD junction, highlighting their role as key conduits for allosteric communication.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eWithin subunits approximately 93.9% of the observed residue-residue pairs exhibited correlation coefficients exceeding a threshold of |C\u003csub\u003ei\u003c/sub\u003eⱼ| \u0026ge; 0.5, with a mean correlation of 0.718 (Supplementary Tables\u0026nbsp;3 and 4) indicating a strong and functionally meaningful coupling between structural elements\u003csup\u003e\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u003c/sup\u003e. This high correlation is strong evidence that the identified allosteric pathways are not artifacts of stochastic fluctuations, but instead reflect robust structural communication. These pathways consistently extend from the GABA binding site\u0026mdash;located near the glycan attachment region\u0026mdash;toward the activation gate, suggesting a directional and functionally relevant allosteric network. Notably, this network appears to be significantly modulated by glycan presence, reinforcing the role of glycosylation in shaping long-range signal propagation within the receptor.\u003c/p\u003e\u003cp\u003eExcluding the start and end residues, 12 out of 15 residues in the α subunit pathways appeared in both α\u003csub\u003eB\u003c/sub\u003e and α\u003csub\u003eD\u003c/sub\u003e subunits (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Moreover, α\u003csub\u003eB\u003c/sub\u003e shows higher occupancy conservation with 7 out of 12 residues appearing in more than 75% of trajectories, whereas α\u003csub\u003eD\u003c/sub\u003e demonstrates greater pathway diversity and lower conservation at the ECD, with only 3 out of 13 residues conserved above the 75% threshold. This variability in α\u003csub\u003eD\u003c/sub\u003e is attributed to its proximity to the glycan localization site, where glycan-induced displacement of subunits broadens the explored conformational space. In β subunits, 11 out of 16 residues were observed between both subunits across different pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Within these subunits, β\u003csub\u003eA\u003c/sub\u003e has 4 out of 14 residues with over 75% recurrence, whereas β\u003csub\u003eC\u003c/sub\u003e has 3 out of 13 residues with repeated observation. Additionally, 7 residues (excluding AG residues) between α and homologous β subunit positions consistently appeared across all pathways, highlighting significant cross-subunit consistency in signal propagation (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Overall, pathways demonstrate higher conservation within the TMD, while the ECD displays more diverse and dispersed pathway exploration.\u003c/p\u003e\u003cp\u003eAnalysis of the protein\u0026ndash;glycan interface edges reveal distinct interaction patterns among different glycans (SFig. 2). The α\u003csub\u003eD\u003c/sub\u003e-attached glycan (CARB), which exhibits the lowest fluctuations and strongest spatial localization at the β\u003csub\u003eC\u003c/sub\u003e-α\u003csub\u003eD\u003c/sub\u003e interface, forms the highest number of contact edges with protein. Although CARB frequently contacts residues at the β\u003csub\u003eC\u003c/sub\u003e-α\u003csub\u003eD\u003c/sub\u003e interface, the associated correlation values are generally lower than those observed in the β\u003csub\u003eA\u003c/sub\u003e and α\u003csub\u003eB\u003c/sub\u003e contact edges with other glycans. This suggests that allosteric pathways near CARB may be more diverse and potentially more sensitive to local structural fluctuations (SFig. 2, Supplementary Table\u0026nbsp;2). In contrast, α\u003csub\u003eB\u003c/sub\u003e and β\u003csub\u003eA\u003c/sub\u003e form fewer glycan\u0026ndash;protein contact edges with α\u003csub\u003eB\u003c/sub\u003e-attached glycan (CARA), but those interactions are more strongly correlated, indicating more consistent and direct communication. Therefore, pathways near the glycan localization site in β\u003csub\u003eC\u003c/sub\u003e and α\u003csub\u003eD\u003c/sub\u003e exhibit greater disruption in allosteric coupling compared to β\u003csub\u003eA\u003c/sub\u003e and α\u003csub\u003eB\u003c/sub\u003e. The introduction of the third glycan diversifies subunit connectivity around the glycan site, causing subunit displacement and altering communication pathways more prominently in β\u003csub\u003eC\u003c/sub\u003e and α\u003csub\u003eD\u003c/sub\u003e.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eThree α subunits lead to substantial rearrangements and closure of TMD in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e\u003c/h2\u003e\u003cp\u003eThe βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e system with three pore-facing glycans exhibited a similar disruption of ECD subunit interface and substantial rearrangements within the TMD as βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e, ultimately leading to closure in the lower regions of the TMD that renders the channel non-functional. By the end of the simulation, the modeled α\u003csub\u003eD\u003c/sub\u003e-α\u003csub\u003eE\u003c/sub\u003e interface retained over 90% similarity to previously reported α-homomeric interfaces (PDB ID: 8BHQ), supporting the validity of the system's construction. In contrast, other subunit interfaces showed a significant reduction in the occupancy for previously identified salt bridges (e.g., α\u003csub\u003eB\u003c/sub\u003e K132 - β\u003csub\u003eC\u003c/sub\u003e D72) and even a complete loss of other contacts (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). Similarly, hydrogen bond analysis showed a drastic rearrangement at the β\u003csub\u003eA\u003c/sub\u003e - α\u003csub\u003eB\u003c/sub\u003e and β\u003csub\u003eC\u003c/sub\u003e - α\u003csub\u003eD\u003c/sub\u003e interfaces (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Similar to βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e, the glycan localization at the β\u003csub\u003eC\u003c/sub\u003e - α\u003csub\u003eD\u003c/sub\u003e interface in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e and the steric clash of glycans likely contributes to the observed structural effects and the subtle yet notable 21.66 \u0026Aring;\u0026sup2; increase in convex volume of the ECD (SFig. 5) compared to βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe TMD of βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e undergoes significant rearrangement within the first 200 ns of simulation (SFig. 5F). This rearrangement is characterized by a 2.61 \u0026Aring; inward displacement of α\u003csub\u003eE\u003c/sub\u003e TM2, disrupting its five-fold symmetry of TMD (SFig. 5G). This shift leads to a substantial reduction in pore radius at the 2nd HCS, where the pore radius decreased from 2.03 \u0026Aring; to 1.48 \u0026Aring; (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the desensitization gate goes from 1.94 \u0026Aring; to 1.74 \u0026Aring; (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC, SFig. 5). In contrast, the change in pore radius at AG is negligible. This narrowing in the lower pore region corresponds with a marked reduction in water occupancy within the lower TMD (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eD). By comparison, a structurally similar pentamer without glycosylation (βαβαα) maintained significantly larger pore radii across the three TMD regions of interest (AG: 2.31 \u0026Aring;, 2nd HCS: 2.19 \u0026Aring;, DG: 1.87 \u0026Aring;). These findings indicate that the presence of three pore-facing glycans in the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e system produced substantial structural perturbations in both the ECD and TMD, showing significant disruption to channel architecture that likely renders the channel non-functional. This is consistent with our observations in the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e system, which also contains three pore-facing glycans.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eTwo adjacent α subunits facilitate channel closure in βα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003eβγ\u003c/h2\u003e\u003cp\u003eThe disruption of natural interfaces and steric clashes between glycans in βα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003eβγ propagate to the TMD, leading to significant closure at the AG and DG. The modeled α\u003csub\u003eB\u003c/sub\u003e - α\u003csub\u003eC\u003c/sub\u003e and β\u003csub\u003eD\u003c/sub\u003e-γ\u003csub\u003eE\u003c/sub\u003e interfaces retained over 90% similarity to previously reported structures (PDB ID: 7QNA, 8BHQ) by the end of the simulation, confirming the validity of the system\u0026rsquo;s construction. The adjacency of the glycan creates a steric clash at the glycan core, increasing the overall structural fluctuation of glycan and the internal loops they are attached to (SFig. 3). At the ECD, salt bridge occupancy mostly increases at the β\u003csub\u003eA\u003c/sub\u003e-α\u003csub\u003eB\u003c/sub\u003e and γ\u003csub\u003eE\u003c/sub\u003e-β\u003csub\u003eA\u003c/sub\u003e interfaces (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA). Hydrogen bond analysis follows a similar trend of increase in occupancy. However, the salt bridge β\u003csub\u003eA\u003c/sub\u003e D187 - α\u003csub\u003eB\u003c/sub\u003e R112 and the conserved hydrogen bond β\u003csub\u003eA\u003c/sub\u003e T120 - α\u003csub\u003eB\u003c/sub\u003e T140\u0026mdash;located close to the GABA binding site\u0026mdash;showing a notable decrease in occupancy (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA\u0026amp;B).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThese structural rearrangements at the ECD propagate to the TMD, culminating in a 5.86 \u0026Aring; inward movement of α\u003csub\u003eC\u003c/sub\u003e and 5.95 \u0026Aring; outward movement of α\u003csub\u003eB\u003c/sub\u003e at the desensitization gate (SFig. 6). This shift leads to significant tightening at the AG, 2nd HCS, and DG (all p-values\u0026thinsp;\u0026lt;\u0026thinsp;0.001), which becomes more pronounced as the simulation progresses (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, SFig. 6E). Interestingly, a similar reduction in pore radius is not observed in a βααβγ system without glycosylation (SFig. 6F). Water occupancy analysis in βα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003eβγ further reflects this trend, with a marked reduction in water molecules in the lower TMD similar to βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eD). Therefore, the rearrangement of the ECD interface drives the progressive closure of both the activation and desensitization gates in βα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003eβγ. The cumulative effects at both the ECD and TMD indicate a considerable disruption in channel activity for βα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003eβγ, which would likely render the channel non-functional.\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur study suggested that the pore-facing N‐linked glycan on GABA\u003csub\u003eA\u003c/sub\u003eR α subunits plays a crucial role in proper pentameric assembly and channel gating. MD simulations reveal that the introduction of additional or neighboring glycans disrupts native salt bridges and hydrogen bond networks at key β\u003csup\u003e+\u003c/sup\u003e/α\u003csup\u003e\u0026ndash;\u003c/sup\u003e subunit interfaces. This disruption translates into permanent closure of the TMD at the activation or desensitization gates. This observation is not only in line with the previous structural hypothesis that steric hindrance from pore-facing glycans prevents the formation of a pentameric receptor with more than 2 α subunits\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, but also provide a mechanistic explanation as to how additional or neighboring α subunits alter channel structure and function.\u003c/p\u003e\u003cp\u003eTo date, direct experimental evidence supporting the determinant role of pore-facing glycans in GABA\u003csub\u003eA\u003c/sub\u003eRs assembly pattern remains limited. However, the importance of the α subunit in subunit arrangement is supported by experimental studies suggesting two clusters of residues on the α subunit to be essential for recruiting and stabilizing the interface with the β subunit \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. These clusters include the majority of the rearranged salt bridges identified in our simulations, indicating that the additional glycan, by destabilizing native inter-subunit interactions, may impair subunit recruitment or channel activity. Earlier homology modeling studies proposed a symmetrical salt bridge network at the subunit interface\u003csup\u003e\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u003c/sup\u003e, hypothesized to be critical for structural and functional stability. Although more recent structural data shows that several of these proposed salt bridges are spatially distant\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e,\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e, our analysis reveals an alternative salt bridge network that plays an equivalent structural role. This network is primarily located at the lower part of the ECD and extends across the ECD\u0026ndash;TMD interface and associated loops (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003eMany disrupted salt bridges and hydrogen bonded residues represent critical nodes for channel function and their mutations are associated with diseases. Notably, the β K126 - α D90, α K132 - β D72, and γ K156 - β D72 interactions form a conserved framework at the β+/α\u0026ndash;, α+/β\u0026ndash;, and β+/γ\u0026ndash; interfaces (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e)). The residue D90 in the α subunit emerges as a key node, forming salt bridges with β subunits. Pathogenic mutations at this site\u0026mdash;such as D90N and D90Y\u0026mdash;have been linked to Juvenile Myoclonic Epilepsy and Idiopathic Generalized Epilepsy\u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e, underscoring its essential role in subunit coupling and gating. Likewise, the D72Y in the β subunit plays a hub role in this intersubunit salt-bridge network. Its mutation is primarily associated with prostate cancer\u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e, indicating that this residue may have broader functional significance. Additionally, mutations such as R112Q\u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e, H137T\u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e, and D125N\u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e in the α subunit, as well as D119H\u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e and N327K\u003csup\u003e\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u003c/sup\u003e in the β subunit, are reported in various forms of epilepsy, cancer, and intellectual disability. Importantly, α K306 (SFig. 1), located along a suggested allosteric pathway\u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e\u003c/sup\u003e for pLGIC, shows disease relevance through the K306T mutation that is implicated in developmental and epileptic encephalopathy\u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e. Collectively, the overlap between intersubunit interaction networks and disease-associated mutations highlights the critical structural role of these bonds and their potential vulnerability to glycosylation-induced structural rearrangement.\u003c/p\u003e\u003cp\u003ePrevious investigations on GLIC gating identified D32 as a critical molecular \"switch\" at the ECD\u0026ndash;TMD interface\u003csup\u003e\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e\u003c/sup\u003e. The breaking of the D32\u0026ndash;R192 salt bridge is among the initial events triggering structural rearrangements that lead to pore collapse and channel closure. Once freed from R192, D32 engages K248, directly linking ECD rearrangements to TMD movements critical for gating. Similarly, in our study we observed consistent disruption of the homologous salt bridge between α\u003csub\u003eB\u003c/sub\u003e E76 (equivalent to D32) and β\u003csub\u003eC\u003c/sub\u003e K306\u0026mdash;with occupancy reduced by over 10% across all replicas. Dynamical network analysis also revealed rerouting of allosteric pathways, effectively bypassing the E76 hub, pushing the system toward novel interactions that lead to pronounced TMD closure. Together, these results confirm the conserved, critical role of this salt-bridge interaction in coupling extracellular conformational changes to channel gating in pLGIC.\u003c/p\u003e\u003cp\u003eComparative analysis of the A\u0026ndash;E (β4\u0026ndash;β5) linker dynamics reveals that the loop's deviation from its optimal flexibility\u0026mdash;either increased or decreased\u0026mdash;can impair channel gating. Previous work by Venkatachalan and Czajkowski \u003csup\u003e\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e showed that increasing the flexibility of this loop through the insertion of glycines disrupted gating, with modifications in the β subunit producing a substantial increase in GABA EC₅₀ and slower channel opening compared to equivalent insertions in the α-subunit. However, other structural alterations were not examined. Our simulations show that additional pore-facing \u003cem\u003eN\u003c/em\u003e-linked glycans reduce A\u0026ndash;E loop flexibility, particularly in the β\u003csub\u003eC\u003c/sub\u003e and γ\u003csub\u003eE\u003c/sub\u003e subunits, which correlates with activation-gate closure in the TMD. Together, these findings indicate that both excessive flexibility and increased rigidity of the A\u0026ndash;E loop can disrupt its role in coupling agonist binding to channel opening, defining a narrow dynamic range essential for efficient gating.\u003c/p\u003e\u003cp\u003eOur simulations reveal that pore-facing glycans exert a significant influence on the structural integrity of both the activation gate (9\u0026prime;), the desensitization gate (\u0026minus;\u0026thinsp;2\u0026prime;) and 2nd HCS (2\u0026prime;) within the TMD of the GABA\u003csub\u003eA\u003c/sub\u003eR. In the βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ, the average pore radii at 9\u0026prime;, 2\u0026prime;, and \u0026minus;\u0026thinsp;2\u0026prime; positions were 1.38 \u0026Aring;, 2.03 \u0026Aring;, and 1.96 \u0026Aring;, respectively\u0026mdash;values consistent with a semi-desensitized or pre-active state, yet notably narrower than the radii suggested in open-state models, where the 9\u0026prime; gate reaches\u0026thinsp;~\u0026thinsp;4 \u0026Aring; and the \u0026minus;\u0026thinsp;2\u0026prime; gate opens to ~\u0026thinsp;3 \u0026Aring; in a computational study\u003csup\u003e\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e\u003c/sup\u003e. βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eγ*\u003csup\u003eG\u003c/sup\u003e with three pore-facing glycans exhibited a pronounced constriction at the 9\u0026prime; gate (1.19 \u0026Aring;) and moderate reductions at the 2\u0026prime; (1.86 \u0026Aring;) and \u0026minus;\u0026thinsp;2\u0026prime; (2.05 \u0026Aring;) positions in addition to exhibiting a rapid switching behavior of the AG at 9\u0026prime; between 0.6 \u0026Aring; and 1.25 \u0026Aring;. This is indicative of a closed-like state. This narrowing becomes more severe in βα\u003csup\u003eG\u003c/sup\u003eβα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003e, particularly at 2\u0026prime; (1.48 \u0026Aring;) and \u0026minus;\u0026thinsp;2\u0026prime; (1.74 \u0026Aring;), with the 9\u0026prime; gate measuring 1.37 \u0026Aring;. The βα\u003csup\u003eG\u003c/sup\u003eα\u003csup\u003eG\u003c/sup\u003eβγ showed the most constricted profile, with pore radii falling to 0.88 \u0026Aring; (9\u0026prime;), 1.63 \u0026Aring; (2\u0026prime;), and 0.84 \u0026Aring; (\u0026minus;\u0026thinsp;2\u0026prime;), values well below the thresholds required for chloride conduction. Compared to literature-reported states stabilized by modulators such as etomidate or propofol\u0026mdash;where AG opens widely (4.2\u0026ndash;5.2 \u0026Aring;) but DG remains collapsed (~\u0026thinsp;1.4\u0026ndash;1.6 \u0026Aring;)\u003csup\u003e34,44\u003c/sup\u003e\u0026mdash;our glycan-containing mutants consistently show closure at both gates, suggesting a shift toward a non-conductive conformation. Notably, channel closure does not correlate with GABA dissociation, as it does not necessarily occur before or after GABA dissociation, indicating that the observed constrictions at AG, 2nd HCS, and DG are not a consequence of GABA dissociation.\u003c/p\u003e\u003cp\u003eThe glycosylation site is conserved across all GABA\u003csub\u003eA\u003c/sub\u003eR α subunits and may represent a recent evolutionary gain-of-glycosylation event. This site is unique to α subunits, as this sequon is absent in other GABA\u003csub\u003eA\u003c/sub\u003eR subunits or other members of the pLGIC family. Notably, the functional importance of this region extends beyond the conserved N-glycosylation site. For instance, in the β subunit, the homologous extracellular β4\u0026ndash;β5 loop\u0026mdash;although not glycosylated\u0026mdash;plays a key role in receptor activation\u003csup\u003e\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e. Furthermore, the evolutionary conservation of a threonine residue (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG) located two positions downstream of the glycosylation site highlights its role as a structural \"priming\" element that facilitates the emergence of glycosylation sites\u003csup\u003e\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u003c/sup\u003e. Glycosylated asparagine residues are subject to strong purifying selection pressure and thus evolve more slowly\u003csup\u003e\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e\u003c/sup\u003e. However, sequence analyses have shown that most newly acquired \u003cem\u003eN\u003c/em\u003e-glycosylation sites arise from the introduction of asparagine into pre-existing motifs already containing a conserved threonine at the +\u0026thinsp;2 position (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u0026amp;C)\u003csup\u003e106,108\u003c/sup\u003e. These latent motifs, maintained by genetic drift or bias, serve as evolutionary placeholders\u0026mdash;structurally stable regions poised for rapid functional enhancement upon acquiring a glycosylation-competent sequon\u003csup\u003e\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e\u003c/sup\u003e. A well-documented example of this mechanism is found in primate thyroglobulin evolution, where a threonine residue conserved across mammals was complemented by a human-specific asparagine mutation at position 76, generating an \u003cem\u003eN\u003c/em\u003e-glycosylation site (N-X-T) that significantly improved thyroxine production\u003csup\u003e\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u003c/sup\u003e. Similarly, in GABA\u003csub\u003eA\u003c/sub\u003eRs, conserved threonine residues may act as evolutionary precursors for glycosylation, contributing to structural integrity while enabling future regulation of channel assembly and function.\u003c/p\u003e\u003cp\u003eWhile our computational findings implicate the determinant role of pore-facing glycans in subunit composition to prevent three or neighboringα subunits, experimental validation of this mechanism remains underexplored and challenging. Previous structural studies that resolved GABA\u003csub\u003eA\u003c/sub\u003eR α homomers involved substantial modification to the ECD, particularly at the pore-facing N-glycosylation site. For example, one study employed a cell line with incomplete glycan expression, combined with a neutralizing mutation at N123 on the α1 subunit to prevent glycosylation\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Another replaced the GABA\u003csub\u003eA\u003c/sub\u003eR ECD with that of the ELIC\u0026rsquo;s\u003csup\u003e48\u003c/sup\u003e or β subunits\u003csup\u003e\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e\u003c/sup\u003e, thereby eliminating the native pore-facing glycosylation. Several studies have proposed an α\u0026ndash;α interface using concatenated constructs designed to enforce specific subunit arrangement\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. However, these findings remain controversial, as no naturally resolved structure has confirmed such configurations, and it is argued that forced assembly may yield non-native, potentially deleterious receptor builds\u003csup\u003e\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e\u003c/sup\u003e. A more rigorous approach to validate the role of glycosylation in subunit arrangement would be to resolve the structure of a fully concatenated construct encoding all five subunits, accompanied by detailed glyco-profiling using mass spectrometry.\u003c/p\u003e\u003cp\u003eIt is noted that there are several limitations to the current study. First, the structure of the pore-facing glycan modeled in our simulations may not fully reflect its native composition. Although, current cryo-EM structures show that the pore‐facing glycan on the α subunit adopts a high‐mannose form\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, with one structure displaying a Man8 configuration\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, additional studies are needed to clarify the extent of terminal mannose trimming. This uncertainty stems from the inherent variability in glycosylation processing by enzymes in the endoplasmic reticulum and \u003cem\u003ecis\u003c/em\u003e‐Golgi \u003csup\u003e\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e,\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e\u003c/sup\u003e. If the pore-facing glycans are more extended \u003cem\u003ein vivo\u003c/em\u003e, their structural and functional impact could be greater than what we observe in our present study. Furthermore, N‐linked glycosylation composition can vary across tissues and species\u003csup\u003e\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u003c/sup\u003e. Future in-depth glycomic profiling of GABA\u003csub\u003eA\u003c/sub\u003eRs may reveal additional insights into their regulation by glycosylation. Secondly, this study specifically examines the effects of pore‐facing glycosylation on the structure and dynamics of the assembled GABA\u003csub\u003eA\u003c/sub\u003eRs. However, we do not address its potential role in the assembly process. Given that these N-linked glycans are known to influence protein expression, assembly, and trafficking\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e; this remains an important yet unexplored aspect beyond the scope of our simulation study. Further studies are needed to investigate how glycosylation affects receptor biosynthesis and maturation.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOur study reveals that pore-facing N-linked glycans on GABA\u003csub\u003eA\u003c/sub\u003e receptor α subunits play a critical role in determining pentameric assembly patterns and modulating channel gating. Through integrative structural survey, sequence analysis, and molecular dynamics simulations, we demonstrate that introducing two neighboring pore-facing glycans disrupts conserved interfacial networks\u0026mdash;specifically salt bridges and hydrogen bonds\u0026mdash;at key β+/α\u0026ndash; subunit interfaces within the ECD. These disruptions propagate allosterically from the ECD to the TMD, leading to altered internal loop flexibility, loss of coordinated gating motions, and premature closure of the activation or desensitization gates. This structural rearrangement results in a shift toward non-conductive channel conformations. These computational insights are consistent with prior structural hypotheses and help explain functional consequences of disease-associated mutations located near glycan-sensitive regions or along the ECD-TMD allosteric coupling pathway. Importantly, our findings underscore the evolutionary uniqueness and functional importance of the α subunit-attached pore-facing N-glycosylation site, suggesting it acts as a molecular determinant of subunit composition and channel function. Although our models provide mechanistic clarity, experimental validation remains essential. Together, our findings reveal the underappreciated yet critical role of pore-facing glycans in shaping GABA\u003csub\u003eA\u003c/sub\u003eR architecture and function. This work lays the foundation for glycan-aware strategies in receptor modulation and opens new avenues for developing selective therapeutics targeting glycosylation-mediated control of ion channel activity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgment\u003c/h2\u003e\u003cp\u003eThe authors gratefully acknowledge discussions with Dr. Claudio Grosman and Dr. Joshua Sharp. We also thank Laila Aiad for her early involvement in the project. Research reported in this publication was supported by a National Science Foundation CAREER grant under award number 2439983, an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under award number P20GM130460, and the National Institute of General Medical Sciences of the National Institutes of Health under Award Number R35GM160133. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Computer resources came from a Maximize ACCESS allocation through project BIO210015, an allocation (MCB200085P) on Anton2/Anton3 at the Pittsburgh Supercomputing Center, provided by the National Center for Multiscale Modeling of Biological Systems through National Institutes of Health grant P41GM103712-1, and from a loan from D. E. Shaw Research. The authors also thank the Computational Chemistry and Bioinformatics Research Core within the University of Mississippi\u0026rsquo;s Glycoscience Center of Research Excellence (NIH Project Number 5P20GM130460-04) for use of their computers and assistance with software installation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTretter, V., Moss, S.J.: GABA(A) receptor dynamics and constructing GABAergic synapses. Front. Mol. Neurosci. \u003cb\u003e1\u003c/b\u003e, 7 (2008)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScott, S., Aricescu, A.R.: A structural perspective on GABAA receptor pharmacology. Curr. Opin. Struct. Biol. \u003cb\u003e54\u003c/b\u003e, 189\u0026ndash;197 (2019)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim, J.J., Hibbs, R.E.: Direct structural insights into GABAA receptor pharmacology. Trends Biochem. Sci. \u003cb\u003e46\u003c/b\u003e, 502\u0026ndash;517 (2021)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSigel, E., Steinmann, M.E.: Structure, function, and modulation of GABA(A) receptors. J. Biol. Chem. \u003cb\u003e287\u003c/b\u003e, 40224\u0026ndash;40231 (2012)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDavies, C.H., Davies, S.N., Collingridge, G.L.: Paired-pulse depression of monosynaptic GABA-mediated inhibitory postsynaptic responses in rat hippocampus. J. Physiol. \u003cb\u003e424\u003c/b\u003e, 513\u0026ndash;531 (1990)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGhit, A., Assal, D., Al-Shami, A.S., Hussein, D.E.: E. GABAA receptors: structure, function, pharmacology, and related disorders. \u003cem\u003eJ. Genet. Eng. Biotechnol.\u003c/em\u003e 19, 123 (2021)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLuscher, B., Fuchs, T., Kilpatrick, C.L.: GABAA receptor trafficking-mediated plasticity of inhibitory synapses. Neuron. \u003cb\u003e70\u003c/b\u003e, 385\u0026ndash;409 (2011)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarris, R.A., Allan, A.M.: Functional coupling of gamma-aminobutyric acid receptors to chloride channels in brain membranes. Science. \u003cb\u003e228\u003c/b\u003e, 1108\u0026ndash;1110 (1985)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKittler, J.T., McAinsh, K., Moss, S.J.: Mechanisms of GABAA receptor assembly and trafficking: implications for the modulation of inhibitory neurotransmission. Mol. Neurobiol. \u003cb\u003e26\u003c/b\u003e, 251\u0026ndash;268 (2002)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRichardson, R.J., Petrou, S., Bryson, A.: Established and emerging GABAA receptor pharmacotherapy for epilepsy. Front. Pharmacol. \u003cb\u003e15\u003c/b\u003e, 1341472 (2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEnoch, M.-A.: The role of GABAA receptors in the development of alcoholism. Pharmacol. Biochem. Behav. \u003cb\u003e90\u003c/b\u003e, 95\u0026ndash;104 (2008)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eThompson, S.M.: Modulators of GABAA receptor-mediated inhibition in the treatment of neuropsychiatric disorders: past, present, and future. Neuropsychopharmacology. \u003cb\u003e49\u003c/b\u003e, 83\u0026ndash;95 (2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHernandez, C.C., Macdonald, R.L.: A structural look at GABAA receptor mutations linked to epilepsy syndromes. Brain Res. \u003cb\u003e1714\u003c/b\u003e, 234\u0026ndash;247 (2019)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaljevic, S., M\u0026oslash;ller, R.S., Reid, C.A., P\u0026eacute;rez-Palma, E., Lal, D., May, P., Lerche, H.: Spectrum of GABAA receptor variants in epilepsy. Curr. Opin. Neurol. \u003cb\u003e32\u003c/b\u003e, 183\u0026ndash;190 (2019)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAngelotti, T.P., Macdonald, R.L.: Assembly of GABAA receptor subunits: alpha 1 beta 1 and alpha 1 beta 1 gamma 2S subunits produce unique ion channels with dissimilar single-channel properties. J. Neurosci. \u003cb\u003e13\u003c/b\u003e, 1429\u0026ndash;1440 (1993)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEngin, E.: GABAA receptor subtypes and benzodiazepine use, misuse, and abuse. Front. Psychiatry. \u003cb\u003e13\u003c/b\u003e, 1060949 (2022)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFan, C., Cowgill, J., Howard, R.J., Lindahl, E.: Divergent mechanisms of steroid inhibition in the human ρ1 GABAA receptor. Nat. Commun. \u003cb\u003e15\u003c/b\u003e, 7795 (2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoetz, T., Arslan, A., Wisden, W., Wulff, P.: GABA(A) receptors: structure and function in the basal ganglia. Prog Brain Res. \u003cb\u003e160\u003c/b\u003e, 21\u0026ndash;41 (2007)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGielen, M., Barilone, N., Corringer, P.J.: The desensitization pathway of GABAA receptors, one subunit at a time. Nat. Commun. \u003cb\u003e11\u003c/b\u003e, (2020)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCowgill, J., Fan, C., Steyaert, J., Howard, R.J., Lindahl, E.: Structural basis for activation and potentiation in a human α5β3 GABAA receptor. bioRxiv. (2025). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1101/2025.01.27.635004\u003c/span\u003e\u003cspan address=\"10.1101/2025.01.27.635004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChua, H.C., Chebib, M.G.A.B.A.A.: Receptors and the Diversity in their Structure and Pharmacology. Adv. Pharmacol. \u003cb\u003e79\u003c/b\u003e, 1\u0026ndash;34 (2017)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSente, A., Desai, R., Naydenova, K., Malinauskas, T., Jounaidi, Y., Miehling, J., Zhou, X., Masiulis, S., Hardwick, S.W., Chirgadze, D.Y., Miller, K.W., Aricescu, A.R.: Differential assembly diversifies GABAA receptor structures and signalling. Nature. \u003cb\u003e604\u003c/b\u003e, 190\u0026ndash;194 (2022)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeng, H.-J., Forman, S.A.: Comparison of αβδ and αβγ GABAA receptors: Allosteric modulation and identification of subunit arrangement by site-selective general anesthetics. Pharmacol. Res. \u003cb\u003e133\u003c/b\u003e, 289\u0026ndash;300 (2018)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOlsen, R.W., Sieghart, W.: GABA A receptors: subtypes provide diversity of function and pharmacology. Neuropharmacology. \u003cb\u003e56\u003c/b\u003e, 141\u0026ndash;148 (2009)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSun, C., Zhu, H., Clark, S., Gouaux, E.: Cryo-EM structures reveal native GABAA receptor assemblies and pharmacology. Nature. \u003cb\u003e622\u003c/b\u003e, 195\u0026ndash;201 (2023)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBotzolakis, E.J., Gurba, K.N., Lagrange, A.H., Feng, H.-J., Stanic, A.K., Hu, N., Macdonald, R.L.: Comparison of γ-aminobutyric acid, type A (GABAA), receptor αβγ and αβδ expression using flow cytometry and electrophysiology: EVIDENCE FOR ALTERNATIVE SUBUNIT STOICHIOMETRIES AND ARRANGEMENTS. J. Biol. Chem. \u003cb\u003e291\u003c/b\u003e, 20440\u0026ndash;20461 (2016)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSieghart, W.: Structure, pharmacology, and function of GABAA receptor subtypes. Adv. Pharmacol. \u003cb\u003e54\u003c/b\u003e, 231\u0026ndash;263 (2006)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoldschen-Ohm, M.P.: Benzodiazepine modulation of GABAA receptors: A mechanistic perspective. Biomolecules. \u003cb\u003e12\u003c/b\u003e, 1784 (2022)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKnoflach, F., Bertrand, D.: Pharmacological modulation of GABAA receptors. Curr. Opin. Pharmacol. \u003cb\u003e59\u003c/b\u003e, 3\u0026ndash;10 (2021)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCrunkhorn, S.: Understanding GABAA receptor pharmacology. Nat. Rev. Drug Discov. \u003cb\u003e22\u003c/b\u003e, 873 (2023)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMartenson, J.S., Yamasaki, T., Chaudhury, N.H., Albrecht, D., Tomita, S.: Assembly rules for GABAA receptor complexes in the brain. Elife \u003cb\u003e6\u003c/b\u003e, (2017)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBollan, K., King, D., Robertson, L.A., Brown, K., Taylor, P.M., Moss, S.J., Connolly, C.: N. GABA(A) receptor composition is determined by distinct assembly signals within alpha and beta subunits. J. Biol. Chem. \u003cb\u003e278\u003c/b\u003e, 4747\u0026ndash;4755 (2003)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBaumann, S.W., Baur, R., Sigel, E.: Forced subunit assembly in alpha1beta2gamma2 GABAA receptors. Insight into the absolute arrangement. J. Biol. Chem. \u003cb\u003e277\u003c/b\u003e, 46020\u0026ndash;46025 (2002)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhou, J., Noviello, C.M., Teng, J., Moore, H., Lega, B., Hibbs, R.E.: Resolving native GABAA receptor structures from the human brain. Nature. \u003cb\u003e638\u003c/b\u003e, 562\u0026ndash;568 (2025)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChojnacka, W., Teng, J., Kim, J.J., Jensen, A.A., Hibbs, R.E.: Structural insights into GABAA receptor potentiation by Quaalude. Nat. Commun. \u003cb\u003e15\u003c/b\u003e, 5244 (2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu, S., Sridhar, A., Teng, J., Howard, R.J., Lindahl, E., Hibbs, R.E.: Structural and dynamic mechanisms of GABAA receptor modulators with opposing activities. \u003cem\u003eNature Communications 2022 13:1\u003c/em\u003e 13, 1\u0026ndash;13 (2022)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePhulera, S., Zhu, H., Yu, J., Claxton, D.P., Yoder, N., Yoshioka, C., Gouaux, E.: Cryo-EM structure of the benzodiazepine-sensitive α1β1γ2S tri-heteromeric GABAA receptor in complex with GABA. Elife. \u003cb\u003e7\u003c/b\u003e, e39383 (2018)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOhtsubo, K., Marth, J.D.: Glycosylation in cellular mechanisms of health and disease. Cell. \u003cb\u003e126\u003c/b\u003e, 855\u0026ndash;867 (2006)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eScott, H., Panin, V.M.: The role of protein N-glycosylation in neural transmission. Glycobiology. \u003cb\u003e24\u003c/b\u003e, 407\u0026ndash;417 (2014)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMueller, T.M., Haroutunian, V., Meador-Woodruff, J.H.: N-Glycosylation of GABAA receptor subunits is altered in Schizophrenia. Neuropsychopharmacology. \u003cb\u003e39\u003c/b\u003e, 528\u0026ndash;537 (2014)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLo, W.-Y., Lagrange, A.H., Hernandez, C.C., Harrison, R., Dell, A., Haslam, S.M., Sheehan, J.H., Macdonald, R.L.: Glycosylation of {beta}2 subunits regulates GABAA receptor biogenesis and channel gating. J. Biol. Chem. \u003cb\u003e285\u003c/b\u003e, 31348\u0026ndash;31361 (2010)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTanaka, M., Olsen, R.W., Medina, M.T., Schwartz, E., Alonso, M.E., Duron, R.M., Castro-Ortega, R., Martinez-Juarez, I.E., Pascual-Castroviejo, I., Machado-Salas, J., Silva, R., Bailey, J.N., Bai, D., Ochoa, A., Jara-Prado, A., Pineda, G., Macdonald, R.L.: Delgado-Escueta, A. V. Hyperglycosylation and reduced GABA currents of mutated GABRB3 polypeptide in remitting childhood absence epilepsy. Am. J. Hum. Genet. \u003cb\u003e82\u003c/b\u003e, 1249\u0026ndash;1261 (2008)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsai, Y.-X., Chang, N.-E., Reuter, K., Chang, H.-T., Yang, T.-J., von B\u0026uuml;low, S., Sehrawat, V., Zerrouki, N., Tuffery, M., Gecht, M., Grothaus, I.L., Ciacchi, C., Wang, L., Hsu, Y.-S., Khoo, M.-F., Hummer, K.-H., Hsu, G., Hanus, S.-T.D., C., Sikora, M.: Rapid simulation of glycoprotein structures by grafting and steric exclusion of glycan conformer libraries. Cell. \u003cb\u003e187\u003c/b\u003e, 1296\u0026ndash;1311e26 (2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim, J.J., Gharpure, A., Teng, J., Zhuang, Y., Howard, R.J., Zhu, S., Noviello, C.M., Walsh, R.M., Jr, Lindahl, E., Hibbs, R.E.: Shared structural mechanisms of general anaesthetics and benzodiazepines. Nature. \u003cb\u003e585\u003c/b\u003e, 303\u0026ndash;308 (2020)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhu, S., Noviello, C.M., Teng, J., Walsh, R.M., Jr, Kim, J.J., Hibbs, R.E.: Structure of a human synaptic GABAA receptor. Nature. \u003cb\u003e559\u003c/b\u003e, 67\u0026ndash;72 (2018)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBuller, A.L., Hastings, G.A., Kirkness, E.F., Fraser, C.M.: Site-directed mutagenesis of N-linked glycosylation sites on the gamma-aminobutyric acid type A receptor alpha 1 subunit. Mol. Pharmacol. \u003cb\u003e46\u003c/b\u003e, 858\u0026ndash;865 (1994)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKasaragod, V.B., Malinauskas, T., Wahid, A.A., Lengyel, J., Knoflach, F., Hardwick, S.W., Jones, C.F., Chen, W.-N., Lucas, X., El Omari, K., Chirgadze, D.Y., Aricescu, A.R., Cecere, G., Hernandez, M.-C., Miller, P.S.: The molecular basis of drug selectivity for α5 subunit-containing GABAA receptors. Nat. Struct. Mol. Biol. \u003cb\u003e30\u003c/b\u003e, 1936\u0026ndash;1946 (2023)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChen, Q., Wells, M.M., Arjunan, P., Tillman, T.S., Cohen, A.E., Xu, Y., Tang, P.: Structural basis of neurosteroid anesthetic action on GABAA receptors. Nat. Commun. \u003cb\u003e9\u003c/b\u003e, 1\u0026ndash;10 (2018)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStone, J.E.: An efficient library for parallel ray tracing and animation. at (1998). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u0026thinsp;https://scholarsmine.mst.edu/masters_theses/1747/\u003c/span\u003e\u003cspan address=\"http://\u0026thinsp;https://scholarsmine.mst.edu/masters_theses/1747/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHumphrey, W., Dalke, A., Schulten, K.: VMD: Visual molecular dynamics. J. Mol. Graph. \u003cb\u003e14\u003c/b\u003e, 33\u0026ndash;38 (1996)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRoberts, E., Eargle, J., Wright, D.: Luthey-Schulten, Z. MultiSeq: unifying sequence and structure data for evolutionary analysis. BMC Bioinform. \u003cb\u003e7\u003c/b\u003e, 382 (2006)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLomize, M.A., Pogozheva, I.D., Joo, H., Mosberg, H.I., Lomize, A.L.: OPM database and PPM web server: resources for positioning of proteins in membranes. Nucleic Acids Res. \u003cb\u003e40\u003c/b\u003e, D370\u0026ndash;D376 (2012)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJo, S., Kim, T., Iyer, V.G., Im, W.: CHARMM-GUI: a web-based graphical user interface for CHARMM. J. Comput. Chem. \u003cb\u003e29\u003c/b\u003e, 1859\u0026ndash;1865 (2008)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJo, S., Lim, J.B., Klauda, J.B., Im, W.: CHARMM-GUI Membrane Builder for mixed bilayers and its application to yeast membranes. Biophys. J. \u003cb\u003e97\u003c/b\u003e, 50\u0026ndash;58 (2009)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOlsson, M.H.M., S\u0026Oslash;ndergaard, C.R., Rostkowski, M., Jensen, J.H.: PROPKA3: Consistent treatment of internal and surface residues in empirical p K a predictions. J. Chem. Theory Comput. \u003cb\u003e7\u003c/b\u003e, 525\u0026ndash;537 (2011)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim, S., Lee, J., Jo, S., Brooks, C.L. 3rd, Lee, H.S., Im, W.: CHARMM-GUI ligand reader and modeler for CHARMM force field generation of small molecules. J. Comput. Chem. \u003cb\u003e38\u003c/b\u003e, 1879\u0026ndash;1886 (2017)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark, S.-J., Lee, J., Qi, Y., Kern, N.R., Lee, H.S., Jo, S., Joung, I., Joo, K., Lee, J., Im, W.: CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates. Glycobiology. \u003cb\u003e29\u003c/b\u003e, 320\u0026ndash;331 (2019)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark, S.-J., Lee, J., Patel, D.S., Ma, H., Lee, H.S., Jo, S., Im, W.: Glycan Reader is improved to recognize most sugar types and chemical modifications in the Protein Data Bank. Bioinformatics. \u003cb\u003e33\u003c/b\u003e, 3051\u0026ndash;3057 (2017)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJo, S., Song, K.C., Desaire, H., MacKerell, A.D. Jr., Im, W.: Glycan Reader: automated sugar identification and simulation preparation for carbohydrates and glycoproteins. J. Comput. Chem. \u003cb\u003e32\u003c/b\u003e, 3135\u0026ndash;3141 (2011)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHuang, J., Rauscher, S., Nawrocki, G., Ran, T., Feig, M., de Groot, B.L., Grubm\u0026uuml;ller, H., MacKerell, A.D.: Jr. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat. Methods. \u003cb\u003e14\u003c/b\u003e, 71\u0026ndash;73 (2017)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMacKerell, A.D., Bashford, D., Bellott, M., Dunbrack, R.L., Evanseck, J.D., Field, M.J., Fischer, S., Gao, J., Guo, H., Ha, S., Joseph-McCarthy, D., Kuchnir, L., Kuczera, K., Lau, F.T., Mattos, C., Michnick, S., Ngo, T., Nguyen, D.T., Prodhom, B., Reiher, W.E., Roux, B., Schlenkrich, M., Smith, J.C., Stote, R., Straub, J., Watanabe, M., Wi\u0026oacute;rkiewicz-Kuczera, J., Yin, D., Karplus, M.: All-atom empirical potential for molecular modeling and dynamics studies of proteins. J. Phys. Chem. B. \u003cb\u003e102\u003c/b\u003e, 3586\u0026ndash;3616 (1998)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMacKerell, A.D. Jr., Feig, M., Brooks, C.L.: Improved treatment of the protein backbone in empirical force fields. J. Am. Chem. Soc. \u003cb\u003e126\u003c/b\u003e, 698\u0026ndash;699 (2004). 3rd\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKlauda, J.B., Venable, R.M., Freites, J.A., O\u0026rsquo;Connor, J.W., Tobias, D.J., Mondragon-Ramirez, C., Vorobyov, I., MacKerell, A.D. Jr., Pastor, R.W.: Update of the CHARMM all-atom additive force field for lipids: validation on six lipid types. J. Phys. Chem. B. \u003cb\u003e114\u003c/b\u003e, 7830\u0026ndash;7843 (2010)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeglov, D., Roux, B.: Finite representation of an infinite bulk system: solvent boundary potential for computer simulations. J. Chem. Phys. \u003cb\u003e100\u003c/b\u003e, 9050\u0026ndash;9063 (1994)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuvench, O., Mallajosyula, S.S., Raman, E.P., Hatcher, E., Vanommeslaeghe, K., Foster, T.J., Jamison, F.W. I. I., MacKerell, A.D.: Jr. CHARMM Additive All-Atom Force Field for Carbohydrate Derivatives and Its Utility in Polysaccharide and Carbohydrate\u0026ndash;Protein Modeling. \u003cem\u003eJ. Chem. Theory Comput.\u003c/em\u003e 7, 3162\u0026ndash;3180 (2011)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJorgensen, W.L., Chandrasekhar, J., Madura, J.D.: Comparison of simple potential functions for simulating liquid water. \u003cem\u003eThe Journal of\u003c/em\u003e at (1983). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u0026thinsp;https://pubs.aip.org/aip/jcp/article-abstract/79/2/926/776316\u003c/span\u003e\u003cspan address=\"http://\u0026thinsp;https://pubs.aip.org/aip/jcp/article-abstract/79/2/926/776316\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFeller, S.E., Zhang, Y., Pastor, R.W., Brooks, B.R.: Constant pressure molecular dynamics simulation: The Langevin piston method. J. Chem. Phys. \u003cb\u003e103\u003c/b\u003e, 4613\u0026ndash;4621 (1995)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDarden, T., York, D., Pedersen, L.: Particle mesh Ewald: An N\u0026sdot;log(N) method for Ewald sums in large systems. J. Chem. Phys. \u003cb\u003e98\u003c/b\u003e, 10089\u0026ndash;10092 (1993)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDeuflhard, P., Hermans, J., Leimkuhler, B., Mark, A.E., Reich, S., Skeel, R.D.: \u003cem\u003eComputational Molecular Dynamics: Challenges, Methods, Ideas: Proceeding of the 2nd International Symposium on Algorithms for Macromolecular Modelling, Berlin, May 21\u0026ndash;24\u003c/em\u003e,. (Springer Science \u0026amp; Business Media, 2012). at (1997). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u0026thinsp;https://play.google.com/store/books/details?id=ZRX2CAAAQBAJ\u003c/span\u003e\u003cspan address=\"http://\u0026thinsp;https://play.google.com/store/books/details?id=ZRX2CAAAQBAJ\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGao, Y., Lee, J., Smith, I.P.S., Lee, H., Kim, S., Qi, Y., Klauda, J.B., Widmalm, G., Khalid, S., Im, W.: CHARMM-GUI Supports Hydrogen Mass Repartitioning and Different Protonation States of Phosphates in Lipopolysaccharides. J. Chem. Inf. Model. \u003cb\u003e61\u003c/b\u003e, 831\u0026ndash;839 (2021)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKal\u0026eacute;, L., Skeel, R., Bhandarkar, M., Brunner, R., Gursoy, A., Krawetz, N., Phillips, J., Shinozaki, A., Varadarajan, K., Schulten, K.: NAMD2: Greater scalability for parallel molecular dynamics. J. Comput. Phys. \u003cb\u003e151\u003c/b\u003e, 283\u0026ndash;312 (1999)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePhillips, J.C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R.D., Kal\u0026eacute;, L., Schulten, K.: Scalable molecular dynamics with NAMD. J. Comput. Chem. \u003cb\u003e26\u003c/b\u003e, 1781\u0026ndash;1802 (2005)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShaw, D.E., Adams, P.J., Azaria, A., Bank, J.A., Batson, B., Bell, A., Bergdorf, M., Bhatt, J., Butts, J.A., Correia, T., Dirks, R.M., Dror, R.O., Eastwood, M.P., Edwards, B., Even, A., Feldmann, P., Fenn, M., Fenton, C.H., Forte, A., Gagliardo, J., Gill, G., Gorlatova, M., Greskamp, B., Grossman, J.P., Gullingsrud, J., Harper, A., Hasenplaugh, W., Heily, M., Heshmat, B.C., Hunt, J., Ierardi, D.J., Iserovich, L., Jackson, B.L., Johnson, N.P., Kirk, M.M., Klepeis, J.L., Kuskin, J.S., Mackenzie, K.M., Mader, R.J., McGowen, R., McLaughlin, A., Moraes, M.A., Nasr, M.H., Nociolo, L.J., O\u0026rsquo;Donnell, L., Parker, A., Peticolas, J.L., Pocina, G., Predescu, C., Quan, T., Salmon, J.K., Schwink, C., Shim, K.S., Siddique, N., Spengler, J., Szalay, T., Tabladillo, R., Tartler, R., Taube, A.G., Theobald, M., Towles, B., Vick, W., Wang, S.C., Wazlowski, M., Weingarten, M.J., Williams: J. M. \u0026amp; Yuh, K. A. Anton 3. in \u003cem\u003eProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis\u003c/em\u003eACM, (2021). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1145/3458817.3487397\u003c/span\u003e\u003cspan address=\"10.1145/3458817.3487397\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBowers, K.J., Chow, E., Xu, H., Dror, R.O., Eastwood, M.P., Gregersen, B.A., Klepeis, J.L., Kolossvary, I., Moraes, M.A., Sacerdoti, F.D., Salmon, J.K., Shan, Y., Shaw, D.E.: Scalable algorithms for molecular dynamics simulations on commodity clusters. in \u003cem\u003eProceedings of the ACM/IEEE Conference on Supercomputing, SC\u0026rsquo;06\u003c/em\u003e (2006). (2006). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1145/1188455.1188544\u003c/span\u003e\u003cspan address=\"10.1145/1188455.1188544\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLippert, R.A., Predescu, C., Ierardi, D.J., Mackenzie, K.M., Eastwood, M.P., Dror, R.O., Shaw, D.E.: Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure. J. Chem. Phys. \u003cb\u003e139\u003c/b\u003e, 164106 (2013)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u0026Aring;qvist, J., Wennerstr\u0026ouml;m, P., Nervall, M., Bjelic, S., Brandsdal, B.O.: Molecular dynamics simulations of water and biomolecules with a Monte Carlo constant pressure algorithm. Chem. Phys. Lett. \u003cb\u003e384\u003c/b\u003e, 288\u0026ndash;294 (2004)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTuckerman, M., Berne, B.J., Martyna, G.J.: Reversible multiple time scale molecular dynamics. J. Chem. Phys. \u003cb\u003e97\u003c/b\u003e, 1990\u0026ndash;2001 (1992)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePredescu, C., Lerer, A.K., Lippert, R.A., Towles, B., Grossman, J.P., Dirks, R.M., Shaw, D.E.: The u-series: A separable decomposition for electrostatics computation with improved accuracy. J. Chem. Phys. \u003cb\u003e152\u003c/b\u003e, 084113 (2020)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePredescu, C., Bergdorf, M., Shaw, D.E.: Midtown splines: An optimal charge assignment for electrostatics calculations. J. Chem. Phys. \u003cb\u003e153\u003c/b\u003e, 224117 (2020)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMichaud-Agrawal, N., Denning, E.J., Woolf, T.B., Beckstein, O.: MDAnalysis: A toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. \u003cb\u003e32\u003c/b\u003e, 2319\u0026ndash;2327 (2011)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVirtanen, P., Gommers, R., Oliphant, T.E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S.J., Brett, M., Wilson, J., Millman, K.J., Mayorov, N., Nelson, A.R.J., Jones, E., Kern, R., Larson, E., Carey, C.J., Polat, İ., Feng, Y., Moore, E.W., VanderPlas, J., Laxalde, D., Perktold, J., Cimrman, R., Henriksen, I., Quintero, E.A., Harris, C.R., Archibald, A.M., Ribeiro, A.H., Pedregosa, F., van Mulbregt, P., Vijaykumar, A., Bardelli, A.P., Rothberg, A., Hilboll, A., Kloeckner, A., Scopatz, A., Lee, A., Rokem, A., Woods, C.N., Fulton, C., Masson, C., H\u0026auml;ggstr\u0026ouml;m, C., Fitzgerald, C., Nicholson, D.A., Hagen, D.R., Pasechnik, D.V., Olivetti, E., Martin, E., Wieser, E., Silva, F., Lenders, F., Wilhelm, F., Young, G., Price, G.A., Ingold, G.L., Allen, G.E., Lee, G.R., Audren, H., Probst, I., Dietrich, J.P., Silterra, J., Webber, J.T., Slavič, J., Nothman, J., Buchner, J., Kulick, J., Sch\u0026ouml;nberger, J.L., de Miranda Cardoso, J.V., Reimer, J., Harrington, J., Rodr\u0026iacute;guez, J.L.C., Nunez-Iglesias, J., Kuczynski, J., Tritz, K., Thoma, M., Newville, M., K\u0026uuml;mmerer, M., Bolingbroke, M., Tartre, M., Pak, M., Smith, N.J., Nowaczyk, N., Shebanov, N., Pavlyk, O., Brodtkorb, P.A., Lee, P., McGibbon, R.T., Feldbauer, R., Lewis, S., Tygier, S., Sievert, S., Vigna, S., Peterson, S., More, S., Pudlik, T., Oshima, T., Pingel, T.J., Robitaille, T.P., Spura, T., Jones, T.R., Cera, T., Leslie, T., Zito: T., Krauss, T., Upadhyay, U., Halchenko, Y. O. \u0026amp; V\u0026aacute;zquez-Baeza, Y. SciPy 1.0: fundamental algorithms for scientific computing in Python. \u003cem\u003eNat. Methods\u003c/em\u003e 17, 261\u0026ndash;272 (2020)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSmart, O.S., Neduvelil, J.G., Wang, X., Wallace, B.A., Sansom, M.S.: P. HOLE: A program for the analysis of the pore dimensions of ion channel structural models. J. Mol. Graph. \u003cb\u003e14\u003c/b\u003e, 354\u0026ndash;360 (1996)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGowers, R.J., Linke, M., Barnoud, J., Reddy, T.J.E., Melo, M.N., Seyler, S.L., Domański, J., Dotson, D.L., Buchoux, S., Kenney, I.M., Beckstein, O.: MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations. \u003cem\u003eProceedings of the 15th Python in Science Conference\u003c/em\u003e 98\u0026ndash;105 (2016). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.25080/MAJORA-629E541A-00E\u003c/span\u003e\u003cspan address=\"10.25080/MAJORA-629E541A-00E\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBali, M., Akabas, M.H.: The location of a closed channel gate in the GABAA receptor channel. J. Gen. Physiol. \u003cb\u003e129\u003c/b\u003e, 145\u0026ndash;159 (2007)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXu, M., Akabas, M.H.: Identification of channel-lining residues in the M2 membrane-spanning segment of the GABA(A) receptor alpha1 subunit. J. Gen. Physiol. \u003cb\u003e107\u003c/b\u003e, 195\u0026ndash;205 (1996)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGoren, E.N., Reeves, D.C., Akabas, M.H.: Loose protein packing around the extracellular half of the GABA(A) receptor beta1 subunit M2 channel-lining segment. J. Biol. Chem. \u003cb\u003e279\u003c/b\u003e, 11198\u0026ndash;11205 (2004)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGong, H., Porter, L.L., Rose, G.D.: Counting peptide-water hydrogen bonds in unfolded proteins. Protein Sci. \u003cb\u003e20\u003c/b\u003e, 417\u0026ndash;427 (2011)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSethi, A., Eargle, J., Black, A.A., Luthey-Schulten, Z.: Dynamical networks in tRNA:protein complexes. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e 106, 6620\u0026ndash;6625 (2009)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVan Rossum, G., Drake, F.L.: Python 3 Reference Manual; CreateSpace. \u003cem\u003eScotts Valley, CA\u003c/em\u003e 242 at (2009). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u0026thinsp;https://www.python.org/\u003c/span\u003e\u003cspan address=\"http://\u0026thinsp;https://www.python.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHarris, C.R., Millman, K.J., van der Walt, S.J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N.J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M.H., Brett, M., Haldane, A., del R\u0026iacute;o, J.F., Wiebe, M., Peterson, P., G\u0026eacute;rard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C.: Oliphant, T. E. Array programming with NumPy. Nature. \u003cb\u003e585\u003c/b\u003e, 357\u0026ndash;362 (2020)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTeam, T.P.: D. pandas-dev/pandas: Pandas. (2023). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5281/ZENODO.7979740\u003c/span\u003e\u003cspan address=\"10.5281/ZENODO.7979740\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHunter, J.D., Matplotlib: A 2D graphics environment. Comput. Sci. Eng. \u003cb\u003e9\u003c/b\u003e, 90\u0026ndash;95 (2007)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLyu, Q., Xue, W., Liu, R., Ma, Q., Kasaragod, V.B., Sun, S., Li, Q., Chen, Y., Yuan, M., Yang, Y., Zhang, B., Nie, A., Jia, S., Shen, C., Gao, P., Rong, W., Yu, C., Bi, Y., Zhang, C., Nan, F., Ning, G., Rao, Z., Yang, X., Wang, J., Wang, W.: A brain-to-gut signal controls intestinal fat absorption. Nature. \u003cb\u003e634\u003c/b\u003e, 936\u0026ndash;943 (2024)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLegesse, D.H., Fan, C., Teng, J., Zhuang, Y., Howard, R.J., Noviello, C.M., Lindahl, E., Hibbs, R.E.: Structural insights into opposing actions of neurosteroids on GABAA receptors. Nat. Commun. \u003cb\u003e14\u003c/b\u003e, 5091 (2023)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNoviello, C.M., Kreye, J., Teng, J., Pr\u0026uuml;ss, H., Hibbs, R.E.: Structural mechanisms of GABAA receptor autoimmune encephalitis. Cell. \u003cb\u003e185\u003c/b\u003e, 2469\u0026ndash;2477e13 (2022)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLaverty, D., Desai, R., Uchański, T., Masiulis, S., Stec, W.J., Malinauskas, T., Zivanov, J., Pardon, E., Steyaert, J., Miller, K.W., Aricescu, A.R.: Cryo-EM structure of the human α1β3γ2 GABAA receptor in a lipid bilayer. Nature. \u003cb\u003e565\u003c/b\u003e, 516\u0026ndash;520 (2019)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMasiulis, S., Desai, R., Uchański, T., Martin, S., Laverty, I., Karia, D., Malinauskas, D., Zivanov, T., Pardon, J., Kotecha, E., Steyaert, A., Miller, J., K. W., Aricescu, A.: R. GABAA receptor signalling mechanisms revealed by structural pharmacology. Nature. \u003cb\u003e565\u003c/b\u003e, 454\u0026ndash;459 (2019)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVenkatachalan, S.P., Czajkowski, C.: A conserved salt bridge critical for GABA(A) receptor function and loop C dynamics. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e 105, 13604\u0026ndash;13609 (2008)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKasaragod, V.B., Mortensen, M., Hardwick, S.W., Wahid, A.A., Dorovykh, V., Chirgadze, D.Y., Smart, T.G., Miller, P.S.: Mechanisms of inhibition and activation of extrasynaptic αβ GABAA receptors. Nature. \u003cb\u003e602\u003c/b\u003e, 529\u0026ndash;533 (2022)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUniProt Consortium: UniProt: The universal protein knowledgebase in 2023. Nucleic Acids Res. \u003cb\u003e51\u003c/b\u003e, D523\u0026ndash;D531 (2023)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarvill, G.L., Weckhuysen, S., McMahon, J.M., Hartmann, C., M\u0026oslash;ller, R.S., Hjalgrim, H., Cook, J., Geraghty, E., O\u0026rsquo;Roak, B.J., Petrou, S., Clarke, A., Gill, D., Sadleir, L.G., Muhle, H., von Spiczak, S., Nikanorova, M., Hodgson, B.L., Gazina, E.V., Suls, A., Shendure, J., Dibbens, L.M., De Jonghe, P., Helbig, I., Berkovic, S.F., Scheffer, I.E., Mefford, H.: C. GABRA1 and STXBP1: novel genetic causes of Dravet syndrome. Neurology. \u003cb\u003e82\u003c/b\u003e, 1245\u0026ndash;1253 (2014)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNykamp, K., Anderson, M., Powers, M., Garcia, J., Herrera, B., Ho, Y.-Y., Kobayashi, Y., Patil, N., Thusberg, J., Westbrook, M., Invitae Clinical Genomics Group, Topper, S.: Sherloc: a comprehensive refinement of the ACMG-AMP variant classification criteria. \u003cem\u003eGenet. Med.\u003c/em\u003e 19, 1105\u0026ndash;1117 (2017)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLev, B., Murail, S., Poitevin, F., Cromer, B.A., Baaden, M., Delarue, M., Allen, T.W.: String method solution of the gating pathways for a pentameric ligand-gated ion channel. \u003cem\u003eProc. Natl. Acad. Sci. U. S. A.\u003c/em\u003e 114, E4158\u0026ndash;E4167 (2017)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVenkatachalan, S.P., Czajkowski, C.: Structural link between γ-aminobutyric acid type A (GABAA) receptor agonist binding site and inner β-sheet governs channel activation and allosteric drug modulation. J. Biol. Chem. \u003cb\u003e287\u003c/b\u003e, 6714\u0026ndash;6724 (2012)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHaloi, N., Lidbrink, E., Howard, S., R. J., Lindahl, E.: Adaptive sampling-based structural prediction reveals opening of a GABAA receptor through the αβ interface. Sci. Adv. \u003cb\u003e11\u003c/b\u003e, eadq3788 (2025)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim, D.S., Hahn, Y.: The acquisition of novel N-glycosylation sites in conserved proteins during human evolution. BMC Bioinform. \u003cb\u003e16\u003c/b\u003e, 29 (2015)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark, C., Zhang, J.: Genome-wide evolutionary conservation of N-glycosylation sites. Mol. Biol. Evol. \u003cb\u003e28\u003c/b\u003e, 2351\u0026ndash;2357 (2011)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKim, D.S., Choi, D., Hahn, Y.: Loss of ancestral N-glycosylation sites in conserved proteins during human evolution. Int. J. Mol. Med. \u003cb\u003e36\u003c/b\u003e, 1685\u0026ndash;1692 (2015)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWilliams, R., Ma, X., Schott, R.K., Mohammad, N., Ho, C.Y., Li, C.F., Chang, B.S.W., Demetriou, M., Dennis, J.W.: Encoding asymmetry of the N-glycosylation motif facilitates glycoprotein evolution. PLoS One. \u003cb\u003e9\u003c/b\u003e, e86088 (2014)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMiller, P.S., Scott, S., Masiulis, S., De Colibus, L., Pardon, E., Steyaert, J., Aricescu, A.R.: Structural basis for GABAA receptor potentiation by neurosteroids. Nat. Struct. Mol. Biol. \u003cb\u003e24\u003c/b\u003e, 986\u0026ndash;992 (2017)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiao, V.W.Y., Chua, H.C., Kowal, N.M., Chebib, M., Balle, T., Ahring, P.K.: Concatenated γ-aminobutyric acid type A receptors revisited: Finding order in chaos. J. Gen. Physiol. \u003cb\u003e151\u003c/b\u003e, 798\u0026ndash;819 (2019)\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVarki, A., Cummings, R.D., Esko, J.D., Stanley, P., Hart, G.W., Aebi, M., Mohnen, D., Kinoshita, T., Packer, N.H., Prestegard, J.H., Schnaar, R.L., Seeberger, P.H.: Essentials of Glycobiology. Cold Spring Harbor Laboratory Press (2022). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1101/9781621824213\u003c/span\u003e\u003cspan address=\"10.1101/9781621824213\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFadda, E.: Molecular simulations of complex carbohydrates and glycoconjugates. Curr. Opin. Chem. Biol. \u003cb\u003e69\u003c/b\u003e, 102175 (2022)\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"
[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"GABAA receptor, pentameric ligand-gated ion channel, N-glycosylation, hetero oligomeric complexes, molecular dynamics simulation, neurotransmitter ","lastPublishedDoi":"10.21203/rs.3.rs-7743743/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7743743/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe assembly and gating of γ-aminobutyric acid type A receptors (GABA\u003csub\u003eA\u003c/sub\u003eRs) are tightly regulated by their hetero-pentameric subunit composition, yet the molecular determinants governing the pentameric form remain elusive. Here, we demonstrate that a conserved \u003cem\u003eN\u003c/em\u003e-linked glycan on α subunits, uniquely positioned within the central pore of the extracellular domain, acts as a structural gatekeeper limiting α subunit incorporation. Using a total of 28 \u0026micro;s of molecular dynamics simulations across native and putative GABA\u003csub\u003eA\u003c/sub\u003eRs assemblies, we show that introducing a third pore-facing glycan or positioning two glycans on adjacent subunits disrupts key interfacial salt bridges and hydrogen bonds, particularly at the β+/α\u0026ndash; interface that hosts the GABA binding site. These disruptions propagate allosterically, reduce internal loop flexibility, and alter extracellular-to-transmembrane domain coupling, ultimately leading to deep closure of the activation and desensitization gates in the transmembrane domain. Systems containing three glycans consistently shift toward dehydrated, non-conductive conformations. In contrast, native form with two pore-facing glycans preserved native interfacial networks and pore radius. Our findings provide a mechanistic insight for the long-observed α-limiting assembly pattern and identify glycan-mediated steric hindrance as a critical factor of receptor gating. These insights bridge evolutionary conservation, \u003cem\u003eN\u003c/em\u003e-glycosylation, and dynamic structure-function relationships, highlighting pore-facing glycosylation as a key determinant of GABA\u003csub\u003eA\u003c/sub\u003eRs architecture and function.\u003c/p\u003e","manuscriptTitle":"A Pore-Facing Glycan Determines GABAA Receptor Subunit Stoichiometry and Gating Behavior","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-17 13:36:36","doi":"10.21203/rs.3.rs-7743743/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"
[email protected]","identity":"communications-biology","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsbio","sideBox":"Learn more about [Communications Biology](http://www.nature.com/commsbio/)","snPcode":"","submissionUrl":"","title":"Communications Biology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1b178116-1fee-4934-913b-7bc4a003a28e","owner":[],"postedDate":"October 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":55857907,"name":"Biological sciences/Biophysics/Computational biophysics"},{"id":55857908,"name":"Biological sciences/Biophysics/Permeation and transport"},{"id":55857909,"name":"Biological sciences/Chemical biology/Glycobiology"}],"tags":[],"updatedAt":"2026-04-11T15:15:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-17 13:36:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7743743","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7743743","identity":"rs-7743743","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
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