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Resolving native GABAA receptor structures from the human brain

Nature volume 638, pages 562–568 (2025) Cite this article

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Abstract

Type A GABA (γ-aminobutyric acid) receptors (GABAA receptors) mediate most fast inhibitory signalling in the brain and are targets for drugs that treat epilepsy, anxiety, depression and insomnia and for anaesthetics1,2. These receptors comprise a complex array of 19 related subunits, which form pentameric ligand-gated ion channels. The composition and structure of native GABAA receptors in the human brain have been inferred from subunit localization in tissue1,3, functional measurements and structural analysis from recombinant expression4,5,6,7 and in mice8. However, the arrangements of subunits that co-assemble physiologically in native human GABAA receptors remain unknown. Here we isolated α1 subunit-containing GABAA receptors from human patients with epilepsy. Using cryo-electron microscopy, we defined a set of 12 native subunit assemblies and their 3D structures. We address inconsistencies between previous native and recombinant approaches, and reveal details of previously undefined subunit interfaces. Drug-like densities in a subset of these interfaces led us to uncover unexpected activity on the GABAA receptor of antiepileptic drugs and resulted in localization of one of these drugs to the benzodiazepine-binding site. Proteomics and further structural analysis suggest interactions with the auxiliary subunits neuroligin 2 and GARLH4, which localize and modulate GABAA receptors at inhibitory synapses. This work provides a structural foundation for understanding GABAA receptor signalling and targeted pharmacology in the human brain.

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Fig. 1: Tissue samples and purification of α1-containing GABAA receptors.
The alternative text for this image may have been generated using AI.
Fig. 2: Architecture of native human α1-containing GABAA receptors.
The alternative text for this image may have been generated using AI.
Fig. 3: Densities in native α1-containing GABAA receptors and related pharmacology.
The alternative text for this image may have been generated using AI.
Fig. 4: Proteins associated with native α1-containing GABAA receptors.
The alternative text for this image may have been generated using AI.

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Data availability

All atomic models and cryo-EM maps have been deposited in the Protein Data Bank (PDB) and Electron Microscopy Data Bank (EMDB): β2–α1–β2–α1–γ2 (PDB 9CRS, EMD-45878), β2–α1–γ2–β2–α2 (PDB 9CRV, EMD-45884), β3–α1–β2–α2–γ2 (PDB 9CSB, EMD-45890), β2–α1–β2–α2–γ2 (PDB 9CT0, EMD-45894), β2–α1–β3–α2–γ2 (PDB 9CTJ, EMD-45908), β2–α1–β2–α3–γ2 (PDB 9CTP, EMD-45914), β2–α1–γ2–β1–α2 (PDB 9CTV, EMD-45920), β2–α1–β3–α1–γ2 (PDB 9CXA, EMD-45983), β3–α1–γ2–β2–α2 (PDB 9CXC, EMD-45985), β3–α1–γ2–β3–α2 (PDB 9CX7, EMD-45980), β2–α1–β1–α2–γ2 (PDB 9CXB, EMD-45984), β2–α1–β1–β1–γ2 (PDB 9CXD, EMD-45986), lamotrigine-bound β2–α1–β2–α1–γ2 (PDB 9DRX, EMD-47132). Raw electrophysiology and mass spectrometry data are included as  Source data with this paper.

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Acknowledgements

We are grateful to the patients and their families for providing the brain tissue and access to enable research. The authors thank H. Jiang, A. Marinas, S. Burke, H. Li and W. Chojnacka for discussions and manuscript review; L. Baxter for assistance with figures; the UC San Diego Cryo-EM Facility for their scientific and technical support; M. Matyszewski for discussions and assistance with data collection and processing; A. Lemoff and M. Ghassemian for their support with mass spectrometry; G. Konopka and M. Harper for facilitating surgical tissue preparation and storage; and S. Tomita for discussions and preliminary experiments with synaptic interacting proteins. This work was supported by grants from the American Heart Association (24POST1195454 to J.Z.) and from the NIH (NS132443 to H.M., NS126143 to B.L. and DA047325 to R.E.H.).

Author information

Authors and Affiliations

  1. Department of Neurobiology, University of California San Diego, La Jolla, CA, USA

    Jia Zhou, Colleen M. Noviello, Jinfeng Teng & Ryan E. Hibbs

  2. Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, USA

    Haley Moore

  3. Departments of Neurological Surgery, Neurology, Psychiatry and the Peter O’Donnell Jr. Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA

    Bradley Lega

  4. Department of Pharmacology, University of California San Diego, La Jolla, CA, USA

    Ryan E. Hibbs

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  1. Jia Zhou
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Contributions

J.Z. performed the biochemistry, cryo-EM sample preparation, data processing, model building, refinement, structural analysis and drafted and revised the manuscript. C.M.N. performed model building and manuscript revision. J.T. performed the electrophysiology experiments. H.M. collected and prepared tissue. B.L. performed surgeries. R.E.H. provided oversight for the project and drafted and revised the manuscript with all authors.

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Correspondence to Ryan E. Hibbs.

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Extended data figures and tables

Extended Data Fig. 1 Characterization of native human α1-containing GABAA receptors and associated proteins from brain tissue.

a, Sample analysis focus on the GABAAR and non-GABAAR bands. b, Same analysis conducted as in Fig. 1b. c, The top three unknown bands in the SDS-PAGE gel were individually excised for mass spectrometry analysis. Detailed results regarding associated proteins and their related homologues are provided in the table. The table groups are color-coded to match the boxes in a. Results shown in this representative gel were similarly obtained from n = 4 gels from independent purifications. Molecular weights of standards are given on the left of the gel in kD. Uncropped SDS-PAGE gel is provided in Supplementary Fig. 1.

Source data

Extended Data Fig. 2 Cryo-EM data processing of Dataset 1 from tissue from 45 patients.

~28k dose-fractionated micrographs were collected from multiple grids stemming from one purification using anti-α1 Fab (1F4) as the affinity reagent. All data processing was performed in CryoSPARC v4.4. Particles were picked and subjected to multiple rounds of 2D classification; final results are shown, with ~1.3 M particles selected from this step. Ab initio reconstruction was performed with 3 classes, which were used as inputs for heterogeneous refinement of the whole particle set. A single particle set emerged from heterogeneous refinement including ~1.0 M particles, which was subjected to non-uniform (NU) refinement. This map and particle set served as the starting point for all 3D classification. The primary 3D classification used a focused mask around the whole ECD and was set up with 10 classes (Class0 - Class9). The ECD mask was chosen due to the highest resolution features being mainly found in the ECD, and thus this region should allow more robust separation of compositional heterogeneity. Class0 and Class5 contained two strong Fab densities, so were combined and refined to a single subunit arrangement easily definable during model building as β2-α1-β2-α1-γ2. This map and subunit arrangement are indicated as a final, high confidence endpoint in this data processing by listing the subunit order in bold font. The FSC-based map resolution estimate and particle number are given below all maps. Classes 1, 2, and 4 were pooled due to the presence of one strong Fab, refined, and yielded a~2.6 Å resolution map. Heterogeneity in TMD signal in the input classes (1, 2, 4) motivated us to conduct a secondary 3D classification on this ~420k particle set (8 classes). Briefly, however, from the primary 3D classification, Class3 and Class6-Class9 were excluded from further analysis due to anisotropic resolution features suggestive of preferred orientation, or low resolution overall (Class3 and 9). Secondary classification of 1-Fab containing particles using focus map on Chains A-B ECD. This region was selected for masking after testing a large panel of masks (single subunits, pairs, adjacent triplets). All 3D classes were subjected to Nu refinement, then atomic model building was done to begin assigning subunits to map positions (Supplementary Figs. 1–11). Class0 and Class5 exhibited features of a common assembly, so were pooled and refined, to a final subunit arrangement of β2-α1-γ2-β2-α2. All processing is summarized in this flow chart for the dataset with the above explanations serving as representative decision-making approaches. Each composition has been also labeled as (a-g), corresponding to the labels in Fig. 2 and Extended Data Fig. 6. In some cases, a single position in a map was clearly a mixture of two subunits, for example α2/α3. In other cases, we designate the heterogeneity as a “mixture,” which instead means that one or more positions are not yet at that step clearly an α vs. β vs. γ. While we cannot rule out the possibility of contamination in a “final” particle set, arising from a minor fraction of incorrect particles, we can conclude with confidence that for each of the “final” maps, the model built represents the clearly dominant species in that particle set.

Extended Data Fig. 3 Cryo-EM data processing of Dataset 2 from tissue from 36 patients.

Approximately 45k dose-fractionated micrographs were collected, resulting in 1.8 million particles after several rounds of 2D classification. The workflow was conducted according to the procedures outlined in Extended Data Fig. 2. All models were constructed for the reconstructions highlighted in the back boxes. Each composition is also labeled as (a-c) and (h-k), corresponding to the labels in Fig. 2 and Extended Data Fig. 6.

Extended Data Fig. 4 Cryo-EM analysis of the native α1-containing GABAA receptors in complex with interacting partner density.

a, Single-particle cryo-EM image processing workflow, focusing on the transmembrane domain (TMD). Refer to the Methods section for further elaboration on the workflow. Fourier shell correlation (FSC) curves with gray line indicating FSC = 0.143 (b), angular distribution plot (c) and local-resolution maps (d) for the final 3D reconstruction.

Extended Data Fig. 5 Focused classification for γ2-TMD map reconstruction in the three subunit compositions abundant in both datasets.

All cryo-EM data processing steps were performed using CryoSPARC v4.4. Further NU refinement combined particles from both datasets. Focused 3D classifications on the entire TMD region were conducted, and the class with a strong γ2 subunit signal was selected for the final reconstruction. All models were constructed for the reconstructions highlighted in the outlined black boxes. The determination of the γ2 subunit in the compositions β2-α1-β2-α1-γ2, β2-α1-γ2-β2-α2, and β2/3-α1-β2-α1-γ2 is displayed in panels a, b, and c, respectively. Each final composition is also labeled as (a-c), corresponding to the labels in Fig. 2 and Extended Data Fig. 6.

Extended Data Fig. 6 Characteristics of cryo-EM reconstructions.

The angular distribution plots of particles used for the final cryo-EM reconstructions are shown in the top left. The cryo-EM maps, colored according to local resolution estimation in CryoSPARC v4.4, are displayed in the top right (color scale in Å). FSC curves were calculated between half-maps, with the overall resolution estimated using the FSC = 0.143 criterion (below). The detailed compositions of the eleven cryo-EM maps are labeled in the tables of FSC curves.

Extended Data Fig. 7 Comparative analysis of the most abundant native GABAA receptor with previously reported structures.

a, Structural comparison of the β2-α1-β2-α1-γ2 (light coral) with 6X3Z37 (burly wood), 6I5373 (light green), and 8G4N8 (sky blue) demonstrates high overall similarity. b, Detailed comparison of the transmembrane domain regions, with colors consistent with panel a. Each subunit is labeled accordingly. c, Pore conformation of the β2-α1-β2-α1-γ2 receptor, highlighting the opposing β2 and γ2 M2 α-helices as ribbons, with the pore-lining side chains shown as sticks. Purple and green spheres illustrate the pore shape. Distances shown within the pore represent diameters at the desensitization gate (−2′) and resting gate (9′) positions. d, Comparative pore diameter versus distance plot for the structures depicted in panel a, aligned at y = 0 at the level of the -2′ desensitization gate. e, Superposition of structures based on the extracellular domains of adjacent β and α subunits, as shown in panel a.

Extended Data Fig. 8 Densities in native α1-containing GABAA receptors, ligand docking and electrophysiological recordings.

Cryo-EM densities were observed at the interfaces formed by the ECDs of the α and β subunits in the composition of β2-α1-γ2-β2-α2 (a), β2-α1-β2/3-α1-γ2 (b) and β3-α1-γ2-β2/3-α2 (c). Additionally, density was observed at the interfaces formed by the ECDs of the β1 and β1 subunits in the composition of β2-α1-β1-β1-γ2 (d). Ligands of diazepam (DZP) and DMCM aligned with the composition of β2-α1-β2-α1-γ2 (e, f) and β2-α1-β2/3-α1-γ2 (g, h) at the interface of α1 and γ2 subunits. DZP pose is from PDB: 6X3X37 and DMCM from PDB: 8DD339. i, Superposition of surrounding residues from the compositions of β2-α1-γ2-β2-α2, β2-α1-β2/3-α1-γ2 and β3-α1-γ2-β2/3-α2 at interfaces of α and β subunits. j, The alignment of histamine (HSM) with the composition of β2-α1-β1-β1-γ2 at the interface of β1 and β1 subunits; histamine binding pose from Sente et al.5. k-l, Representative responses are shown for application of GABA, followed by GABA plus LTG with α1β2γ2 and α1β2, and same for LEV (m-n).

Extended Data Fig. 9 Cryo-EM analysis of recombinant GABAA receptor in complex with lamotrigine.

a, Single-particle cryo-EM image processing workflow, with several rounds of focused 3D classification on the transmembrane domain (TMD), as shown in b. c, Fourier shell correlation (FSC) curves, with the gray line indicating FSC = 0.143. d, Local-resolution map and e, angular distribution plot for the final 3D reconstruction. To enhance lamotrigine density, focused 3D classification and local refinement were applied to the extracellular domain (ECD), as shown in f. g, FSC curves, with the gray line indicating FSC = 0.143, and h, local-resolution maps for the final 3D reconstruction. In f and h, black box boundaries approximate mask used in focused refinement and local resolution estimate; local resolution for regions outside of the mask (e.g., TMD helices) are not meaningful.

Extended Data Table 1 Characteristics of 45 Epilepsy Patients
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Extended Data Table 2 Characteristics of 36 Epilepsy Patients
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Extended Data Table 3 Cryo-EM data collection parameters
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Extended Data Table 4 Refinement and validation statistics
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Extended Data Table 5 Refinement and validation statistics
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Zhou, J., Noviello, C.M., Teng, J. et al. Resolving native GABAA receptor structures from the human brain. Nature 638, 562–568 (2025). https://doi.org/10.1038/s41586-024-08454-1

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