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ABSTRACT Class C G-protein-coupled receptors (GPCRs) are activated through binding of agonists to the large extracellular domain (ECD) followed by rearrangement of the transmembrane domains

(TMDs). GPR156, a class C orphan GPCR, is unique because it lacks an ECD and exhibits constitutive activity. Impaired GPR156–Gi signaling contributes to loss of hearing. Here we present the

cryo-electron microscopy structures of human GPR156 in the Go-free and Go-coupled states. We found that an endogenous phospholipid molecule is located within each TMD of the GPR156 dimer.

Asymmetric binding of Gα to the phospholipid-bound GPR156 dimer restructures the first and second intracellular loops and the carboxy-terminal part of the elongated transmembrane 7 (TM7)

without altering dimer conformation. Our findings reveal that GPR156 is a transducer for phospholipid signaling. Constant binding of abundant phospholipid molecules and the G-protein-induced

reshaping of the cytoplasmic face provide a basis for the constitutive activation of GPR156. Access through your institution Buy or subscribe This is a preview of subscription content,

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institutional subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS MOLECULAR INSIGHTS INTO THE ACTIVATION MECHANISM OF GPR156 IN MAINTAINING

AUDITORY FUNCTION Article Open access 05 December 2024 SPECIFIC BINDING OF GPR174 BY ENDOGENOUS LYSOPHOSPHATIDYLSERINE LEADS TO HIGH CONSTITUTIVE GS SIGNALING Article Open access 22

September 2023 GPR161 STRUCTURE UNCOVERS THE REDUNDANT ROLE OF STEROL-REGULATED CILIARY CAMP SIGNALING IN THE HEDGEHOG PATHWAY Article 07 February 2024 DATA AVAILABILITY Atomic coordinates

and the cryo-EM map have been deposited in the the EM Data Bank (EMD) and Protein Data Bank (PDB), respectively, under the following accession numbers: EMD-35380 and PDB 8IED

(GPR156-Go–scFv16), EMD-35377 and PDB 8IEB (GPR156 dimer of GPR156-Go–scFv16), EMD-35378 and PDB 8IEC (Go–scFv16 of GPR156-Go–scFv16), EMD-35390 and PDB 8IEQ (GPR156A/B/C/D), EMD-35382 and

PDB 8IEI (GPR156A/B of GPR156A/B/C/D) and EMD-35389 and PDB 8IEP (GPR156C/D of GPR156A/B/C/D). Mass spectroscopy data are deposited on Figshare (https://doi.org/10.6084/m9.figshare.24212226

and https://doi.org/10.6084/m9.figshare.24715704.v1). The trajectories for GPR156-PC and GPR156-PG from the molecular dynamics simulations data are deposited on Zenodo

(https://doi.org/10.5281/zenodo.8418994 and https://doi.org/10.5281/zenodo.8419006, respectively). Previously published PDBs used in this study are available under PDB accession codes 7UM5,

7MTR, 7MTS, 6UO8, 7EB2, 7C7S, 7E9H, 7EPA, 7EWL, 7M3J, 7M3F, 6WIV and 7E9G. The AlphaFold2 model is available in ModelArchive (https://www.modelarchive.org) with accession code ma-1015e.

Sequence data used in the alignment for Extended Data Fig. 7 are _H. sapiens_ GPR156, GABR1, GABR2, CaSR, mGlu1, mGlu2, mGlu3, mGlu4, mGlu5 and mGlu7 (Uniprot accession codes Q8NFN8, Q9UBS5,

O75899, P41180, Q13255, Q14416, Q14832, Q14833, P41594 and Q14831, respectively). Sequence data used in the alignment for Extended Data Fig. 10d are _H. sapiens_ Gi1, Gi2, Gi3, Gs, Gq, G12

and G13 (Uniprot accession codes P63096, P04899, P08754, P63092, P50148, Q03113 and Q14344, respectively). Source data are provided with this paper. REFERENCES * Gilman, A. G. G proteins:

transducers of receptor-generated signals. _Annu. Rev. Biochem._ 56, 615–649 (1987). CAS  PubMed  Google Scholar  * Weis, W. I. & Kobilka, B. K. The molecular basis of G protein-coupled

receptor activation. _Annu. Rev. Biochem._ 87, 897–919 (2018). CAS  PubMed  PubMed Central  Google Scholar  * Chun, L., Zhang, W. & Liu, J. Structure and ligand recognition of class C

GPCRs. _Acta Pharmacol. Sin._ 33, 312–323 (2012). CAS  PubMed  PubMed Central  Google Scholar  * Ellaithy, A., Gonzalez-Maeso, J., Logothetis, D. A. & Levitz, J. Structural and

biophysical mechanisms of class C G protein-coupled receptor function. _Trends Biochem. Sci._ 45, 1049–1064 (2020). CAS  PubMed  PubMed Central  Google Scholar  * Shen, C. et al. Structural

basis of GABAB receptor–Gi protein coupling. _Nature_ 594, 594–598 (2021). CAS  PubMed  PubMed Central  Google Scholar  * Seven, A. B. et al. G-protein activation by a metabotropic glutamate

receptor. _Nature_ 595, 450–454 (2021). CAS  PubMed  PubMed Central  Google Scholar  * Lin, S. et al. Structures of Gi-bound metabotropic glutamate receptors mGlu2 and mGlu4. _Nature_ 594,

583–588 (2021). CAS  PubMed  Google Scholar  * Watkins, L. R. & Orlandi, C. In vitro profiling of orphan G protein coupled receptor (GPCR) constitutive activity. _Br. J. Pharmacol._ 178,

2963–2975 (2021). CAS  PubMed  Google Scholar  * Tsutsumi, N. et al. Structural basis for the constitutive activity and immunomodulatory properties of the Epstein–Barr virus-encoded G

protein-coupled receptor BILF1. _Immunity_ 54, 1405–1416.e7 (2021). CAS  PubMed  PubMed Central  Google Scholar  * Kang, Y. et al. Cryo-EM structure of human rhodopsin bound to an inhibitory

G protein. _Nature_ 558, 553–558 (2018). CAS  PubMed  PubMed Central  Google Scholar  * Lin, X. et al. Cryo-EM structures of orphan GPR21 signaling complexes. _Nat. Commun._ 14, 216 (2023).

CAS  PubMed  PubMed Central  Google Scholar  * Xu, L. et al. Cryo-EM structure of constitutively active human Frizzled 7 in complex with heterotrimeric Gs. _Cell Res._ 31, 1311–1314 (2021).

CAS  PubMed  PubMed Central  Google Scholar  * Zhang, H. et al. Structural basis for chemokine recognition and receptor activation of chemokine receptor CCR5. _Nat. Commun._ 12, 4151

(2021). CAS  PubMed  PubMed Central  Google Scholar  * Lin, X. et al. Structural basis of ligand recognition and self-activation of orphan GPR52. _Nature_ 579, 152–157 (2020). CAS  PubMed 

Google Scholar  * Xu, P. et al. Structural insights into the lipid and ligand regulation of serotonin receptors. _Nature_ 592, 469–473 (2021). CAS  PubMed  Google Scholar  * Xu, P. et al.

Structural identification of lysophosphatidylcholines as activating ligands for orphan receptor GPR119. _Nat. Struct. Mol. Biol._ 29, 863–870 (2022). CAS  PubMed  Google Scholar  * Qu, X. et

al. Structural basis of tethered agonism of the adhesion GPCRs ADGRD1 and ADGRF1. _Nature_ 604, 779–785 (2022). CAS  PubMed  PubMed Central  Google Scholar  * Ping, Y.-Q. et al. Structural

basis for the tethered peptide activation of adhesion GPCRs. _Nature_ 604, 763–770 (2022). CAS  PubMed  Google Scholar  * Xiao, P. et al. Tethered peptide activation mechanism of the

adhesion GPCRs ADGRG2 and ADGRG4. _Nature_ 604, 771–777 (2022). CAS  PubMed  Google Scholar  * Barros-Álvarez, X. et al. The tethered peptide activation mechanism of adhesion GPCRs. _Nature_

604, 757–762 (2022). PubMed  PubMed Central  Google Scholar  * Jeong, E., Kim, Y., Jeong, J. & Cho, Y. Structure of the class C orphan GPCR GPR158 in complex with RGS7-Gβ5. _Nat.

Commun._ 12, 6805 (2021). CAS  PubMed  PubMed Central  Google Scholar  * Smith, E. L. et al. GPRC5D is a target for the immunotherapy of multiple myeloma with rationally designed CAR T

cells. _Sci. Transl. Med._ 11, eaau7746 (2019). PubMed  PubMed Central  Google Scholar  * Patil, D. N. et al. Cryo-EM structure of human GPR158 receptor coupled to the RGS7-Gβ5 signaling

complex. _Science_ 375, 86–91 (2021). PubMed  PubMed Central  Google Scholar  * Calver, A. R. et al. Molecular cloning and characterisation of a novel GABAB-related G-protein coupled

receptor. _Mol. Brain. Res._ 110, 305–317 (2003). CAS  PubMed  Google Scholar  * Kindt, K. S. et al. EMX2-GPR156-Gαi reverses hair cell orientation in mechanosensory epithelia. _Nat.

Commun._ 12, 2861 (2021). CAS  PubMed  PubMed Central  Google Scholar  * Greene, D. et al. Genetic association analysis of 77,539 genomes reveals rare disease etiologies. _Nat. Med._ 29,

679–688 (2023). CAS  PubMed  PubMed Central  Google Scholar  * Ramzan, M. et al. Novel GPR156 variants confirm its role in moderate sensorineural hearing loss. _Sci. Rep._ 13, 17010 (2023).

CAS  PubMed  PubMed Central  Google Scholar  * Kalam, H. et al. Identification of host regulators of _Mycobacterium tuberculosis_ phenotypes uncovers a role for the MMGT1-GPR156 lipid

droplet axis in persistence. _Cell Host Microbe_ 31, 978–992 (2023). CAS  PubMed  Google Scholar  * Maeda, S. et al. Development of an antibody fragment that stabilizes GPCR/G-protein

complexes. _Nat. Commun._ 9, 3712 (2018). PubMed  PubMed Central  Google Scholar  * Park, J. et al. Structure of human GABAB receptor in an inactive state. _Nature_ 584, 304–309 (2020). CAS

  PubMed  PubMed Central  Google Scholar  * Papasergi-Scott, M. M. et al. Structures of metabotropic GABAB receptor. _Nature_ 584, 310–314 (2020). CAS  PubMed  PubMed Central  Google Scholar

  * Shaye, H. et al. Structural basis of the activation of a metabotropic GABA receptor. _Nature_ 584, 298–303 (2020). CAS  PubMed  PubMed Central  Google Scholar  * Mao, C. et al. Cryo-EM

structures of inactive and active GABAB receptor. _Cell Res._ 30, 564–573 (2020). CAS  PubMed  PubMed Central  Google Scholar  * Kim, Y., Jeong, E., Jeong, J.-H., Kim, Y. & Cho, Y.

Structural basis for activation of the heterodimeric GABAB Receptor. _J. Mol. Biol._ 432, 5966–5984 (2020). CAS  PubMed  Google Scholar  * Koehl, A. et al. Structural insights into the

activation of metabotropic glutamate receptors. _Nature_ 566, 79–84 (2019). CAS  PubMed  PubMed Central  Google Scholar  * Gao, Y. et al. Asymmetric activation of the calcium-sensing

receptor homodimer. _Nature_ 595, 455–459 (2021). CAS  PubMed  PubMed Central  Google Scholar  * Du, J. et al. Structures of human mGlu2 and mGlu7 homo- and heterodimers. _Nature_ 594,

589–593 (2021). CAS  PubMed  Google Scholar  * Jurcik, A. et al. CAVER Analyst 2.0: analysis and visualization of channels and tunnels in protein structures and molecular dynamics

trajectories. _Bioinformatics_ 34, 3586–3588 (2018). CAS  PubMed  PubMed Central  Google Scholar  * Suckau, D. et al. A novel MALDI LIFT-TOF/TOF mass spectrometer for proteomics. _Anal.

Bioanal. Chem._ 376, 952–965 (2003). CAS  PubMed  Google Scholar  * Carlson, M. L. et al. The peptidisc, a simple method for stabilizing membrane proteins in detergent-free solution. _eLife_

7, e34085 (2018). PubMed  PubMed Central  Google Scholar  * Symons, J. L. et al. Lipidomic atlas of mammalian cell membranes reveals hierarchical variation induced by culture conditions,

subcellular membranes, and cell lineages. _Soft Matter_ 17, 288–297 (2021). CAS  PubMed  PubMed Central  Google Scholar  * Pin, J.-P., Galvez, T. & Prézeau, L. Evolution, structure, and

activation mechanism of family 3/C G-protein-coupled receptors. _Pharmacol. Ther._ 98, 325–354 (2003). CAS  PubMed  Google Scholar  * Congreve, M., Oswald, C. & Marshall, F. H. Applying

structure-based drug design approaches to allosteric modulators of GPCRs. _Trends Pharmacol. Sci._ 38, 837–847 (2017). CAS  PubMed  Google Scholar  * Potterton, L. et al. CCP4i2: the new

graphical user interface to the CCP4 program suite. _Acta Crystallogr. D. Struct. Biol._ 74, 68–84 (2018). CAS  PubMed  PubMed Central  Google Scholar  * Jumper, J. et al. Highly accurate

protein structure prediction with AlphaFold. _Nature_ 596, 583–589 (2021). CAS  PubMed  PubMed Central  Google Scholar  * Pándy-Szekeres, G. et al. GPCRdb in 2023: state-specific structure

models using AlphaFold2 and new ligand resources. _Nucleic Acids Res._ 51, D395–D402 (2022). PubMed Central  Google Scholar  * Flock, T. et al. Universal allosteric mechanism for Gα

activation by GPCRs. _Nature_ 524, 173–179 (2015). CAS  PubMed  PubMed Central  Google Scholar  * Nehmé, R. et al. Mini-G proteins: novel tools for studying GPCRs in their active

conformation. _PLoS One_ 12, e0175642 (2017). PubMed  PubMed Central  Google Scholar  * Liang, J. et al. Structural basis of lysophosphatidylserine receptor GPR174 ligand recognition and

activation. _Nat. Commun._ 14, 1012 (2023). CAS  PubMed  PubMed Central  Google Scholar  * Koehl, A. et al. Structure of the µ-opioid receptor–Gi protein complex. _Nature_ 558, 547–552

(2018). CAS  PubMed  PubMed Central  Google Scholar  * Kim, K. et al. Structure of a hallucinogen-activated Gq-coupled 5-HT2A serotonin receptor. _Cell_ 182, 1574–1588.e19 (2020). CAS 

PubMed  PubMed Central  Google Scholar  * Zhang, S. et al. Inactive and active state structures template selective tools for the human 5-HT5A receptor. _Nat. Struct. Mol. Biol._ 29, 677–687

(2022). CAS  PubMed  PubMed Central  Google Scholar  * Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure

determination. _Nat. Methods_ 14, 290–296 (2017). CAS  PubMed  Google Scholar  * Rohou, A. & Grigorieff, N. CTFFIND4: fast and accurate defocus estimation from electron micrographs. _J.

Struct. Biol._ 192, 216–221 (2015). PubMed  PubMed Central  Google Scholar  * Yue, Y. et al. Structural insight into apelin receptor-G protein stoichiometry. _Nat. Struct. Mol. Biol._ 29,

688–697 (2022). CAS  PubMed  Google Scholar  * Bepler, T. et al. Positive-unlabeled convolutional neural networks for particle picking in cryo-electron micrographs. _Nat. Methods_ 16,

1153–1160 (2018). Google Scholar  * Sanchez-Garcia, R. et al. DeepEMhancer: a deep learning solution for cryo-EM volume post-processing. _Commun. Biol._ 4, 874 (2021). PubMed  PubMed Central

  Google Scholar  * Pettersen, E. F. et al. UCSF Chimera—a visualization system for exploratory research and analysis. _J. Comput. Chem._ 25, 1605–1612 (2004). CAS  PubMed  Google Scholar  *

Emsley, P. & Cowtan, K. Coot: model-building tools for molecular graphics. _Acta Crystallogr. D. Biol. Crystallogr._ 60, 2126–2132 (2004). PubMed  Google Scholar  * Afonine, P. V. et

al. Real-space refinement in PHENIX for cryo-EM and crystallography. _Acta Crystallogr. D. Struct. Biol._ 74, 531–544 (2018). CAS  PubMed  PubMed Central  Google Scholar  * Adams, P. D. et

al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. _Acta Crystallogr. D. Biol. Crystallogr._ 66, 213–221 (2010). CAS  PubMed  PubMed Central  Google

Scholar  * Chen, V. B. et al. MolProbity: all-atom structure validation for macromolecular crystallography. _Acta Crystallogr. D. Biol. Crystallogr._ 66, 12–21 (2010). CAS  PubMed  Google

Scholar  * Moriarty, N. W., Grosse‐Kunstleve, R. W. & Adams, P. D. electronic Ligand Builder and Optimization Workbench (eLBOW): a tool for ligand coordinate and restraint generation.

_Acta Crystallogr. D. Biol. Crystallogr._ 65, 1074–1080 (2009). CAS  PubMed  PubMed Central  Google Scholar  * Afonine, P. V. et al. New tools for the analysis and validation of cryo-EM maps

and atomic models. _Acta Crystallogr. D. Struct. Biol._ 74, 814–840 (2018). CAS  PubMed  PubMed Central  Google Scholar  * Olsen, R. H. J. et al. TRUPATH, an open-source biosensor platform

for interrogating the GPCR transducerome. _Nat. Chem. Biol._ 16, 841–849 (2020). CAS  PubMed  PubMed Central  Google Scholar  * Schmidpeter, P. A. M. et al. Anionic lipids unlock the gates

of select ion channels in the pacemaker family. _Nat. Struct. Mol. Biol._ 29, 1092–1100 (2022). CAS  PubMed  PubMed Central  Google Scholar  * Hutchins, P. D., Russell, J. D. & Coon, J.

J. LipiDex: an integrated software package for high-confidence lipid identification. _Cell Syst._ 6, 621–625.e5 (2018). CAS  PubMed  PubMed Central  Google Scholar  * Pluskal, T., Castillo,

S., Villar-Briones, A. & Orešič, M. MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. _BMC Bioinform._ 11, 395

(2010). Google Scholar  * An, J. N. et al. Effects of periostin deficiency on kidney aging and lipid metabolism. _Aging (Albany NY)_ 13, 22649–22665 (2021). CAS  PubMed  Google Scholar  *

Breil, C., Vian, M. A., Zemb, T., Kunz, W. & Chemat, F. ‘Bligh and Dyer’ and Folch methods for solid–liquid–liquid extraction of lipids from microorganisms. Comprehension of solvatation

mechanisms and towards substitution with alternative solvents. _Int. J. Mol. Sci._ 18, 708 (2017). PubMed  PubMed Central  Google Scholar  * Lee, J. W., Nishiumi, S., Yoshida, M., Fukusaki,

E. & Bamba, T. Simultaneous profiling of polar lipids by supercritical fluid chromatography/tandem mass spectrometry with methylation. _J. Chromatogr. A_ 1279, 98–107 (2013). CAS  PubMed

  Google Scholar  * Lee, J. W. et al. Detailed characterization of alterations in the lipid profiles during autophagic cell death of leukemia cells. _RSC Adv._ 6, 29512–29518 (2016). CAS 

Google Scholar  * Shanta, S. R. et al. Binary matrix for MALDI imaging mass spectrometry of phospholipids in both ion modes. _Anal. Chem._ 83, 1252–1259 (2011). CAS  PubMed  Google Scholar 

* Fahy, E., Sud, M., Cotter, D. & Subramaniam, S. LIPID MAPS online tools for lipid research. _Nucleic Acids Res._ 35, W606–W612 (2007). PubMed  PubMed Central  Google Scholar  * Sud, M.

et al. LMSD: LIPID MAPS structure database. _Nucleic Acids Res._ 35, D527–D532 (2007). CAS  PubMed  Google Scholar  * Noh, S. A. et al. Alterations in lipid profile of the aging kidney

identified by MALDI imaging mass spectrometry. _J. Proteome Res._ 18, 2803–2812 (2019). CAS  PubMed  Google Scholar  * Liebisch, G. et al. Quantitative measurement of different ceramide

species from crude cellular extracts by electrospray ionization tandem mass spectrometry (ESI–MS/MS). _J. Lipid Res._ 40, 1539–1546 (1999). CAS  PubMed  Google Scholar  * Hsu, F.-F. &

Turk, J. Structural determination of sphingomyelin by tandem mass spectrometry with electrospray ionization. _J. Am. Soc. Mass Spectr._ 11, 437–449 (2000). CAS  Google Scholar  * Pi, J., Wu,

X. & Feng, Y. Fragmentation patterns of five types of phospholipids by ultra-high-performance liquid chromatography electrospray ionization quadrupole time-of-flight tandem mass

spectrometry. _Anal. Methods_ 8, 1319–1332 (2016). CAS  Google Scholar  * Sugawara, T., Aida, K., Duan, J. & Hirata, T. Analysis of glucosylceramides from various sources by liquid

chromatography–ion trap mass spectrometry. _J. Oleo Sci._ 59, 387–394 (2010). CAS  PubMed  Google Scholar  * Gu, M., Kerwin, J. L., Watts, J. D. & Aebersold, R. Ceramide profiling of

complex lipid mixtures by electrospray ionization mass spectrometry. _Anal. Biochem._ 244, 347–356 (1997). CAS  PubMed  Google Scholar  * Abraham, M. J. et al. GROMACS: high performance

molecular simulations through multi-level parallelism from laptops to supercomputers. _SoftwareX_ 1, 19–25 (2015). Google Scholar  * Huang, J. et al. CHARMM36m: an improved force field for

folded and intrinsically disordered proteins. _Nat. Methods_ 14, 71–73 (2017). CAS  PubMed  Google Scholar  * Abagyan, R., Totrov, M. & Kuznetsov, D. ICM—a new method for protein

modeling and design: applications to docking and structure prediction from the distorted native conformation. _J. Comput. Chem._ 15, 488–506 (1994). CAS  Google Scholar  * 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). CAS  PubMed  Google Scholar  * 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). CAS  PubMed 

Google Scholar  * Wu, E. L. et al. CHARMM‐GUI Membrane Builder toward realistic biological membrane simulations. _J. Comput. Chem._ 35, 1997–2004 (2014). CAS  PubMed  PubMed Central  Google

Scholar  * Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. LINCS: a linear constraint solver for molecular simulations. _J. Comput. Chem._ 18, 1463–1472 (1997). CAS 

Google Scholar  * Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. _J. Chem. Phys._ 126, 014101 (2007). PubMed  Google Scholar  * McGibbon, R. T. et

al. MDTraj: a modern open library for the analysis of molecular dynamics trajectories. _Biophys. J._ 109, 1528–1532 (2015). CAS  PubMed  PubMed Central  Google Scholar  * 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). PubMed  PubMed Central

  Google Scholar  * Virtanen, P. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. _Nat. Methods_ 17, 261–272 (2020). CAS  PubMed  PubMed Central  Google Scholar 

Download references ACKNOWLEDGEMENTS We thank J. Koh for technical help and Y. Kim, C. Lee, J. Lee, K. Kim, S. H. Ryu (POSTECH), Y. Yu (Kookmin U.), M. Jin (GIST) and J. Kim (SNU) for

helpful comments. This work was supported by grants from the National Research Foundation of Korea (NRF) funded by the Korean government (MEST, No. 2021R1A2C301335711 and 2019M3E5D6066058 to

Y.C.), the Bio & Medical Technology Development Program (NRF-2019M3E5D3073567 to K.P.K.), the Ministry of Science and ICT (grant number 2022R1A2C1005885 to J.H.), the BK21 program

(Ministry of Education to Y.C.), Wellcome Trust Investigator Award (221795/Z/20/Z to X.Q., D.W., C.V.R.) and internal funding from the University of Southern California Dornsife College (to

V.K). Cryo-EM data were acquired at the Core Research Facility, Pusan National University. Computing resources were provided by the Center for Advanced Research Computing (CARC) at the

University of Southern California (https://carc.usc.edu). AUTHOR INFORMATION Author notes * These authors contributed equally: Jinwoo Shin, Junhyeon Park. AUTHORS AND AFFILIATIONS *

Department of Life Sciences, Pohang University of Science and Technology, Pohang, Republic of Korea Jinwoo Shin, Junhyeon Park & Yunje Cho * Department of Applied Chemistry, Global

Center for Pharmaceutical Ingredient Materials, Kyung Hee University, Yongin, Republic of Korea Jieun Jeong & Kwang Pyo Kim * Department of Quantitative and Computational Biology,

University of Southern California, Los Angeles, CA, USA Jordy Homing Lam & Vsevolod Katritch * Bridge Institute and Michelson Center for Convergent Biosciences, University of Southern

California, Los Angeles, CA, USA Jordy Homing Lam & Vsevolod Katritch * Department of Chemistry, University of Oxford, Oxford, UK Xingyu Qiu, Di Wu & Carol V. Robinson * Kavli

Institute for Nanoscience Discovery, University of Oxford, Oxford, UK Xingyu Qiu, Di Wu & Carol V. Robinson * Department of Pharmacy, Yonsei University, Incheon, Republic of Korea Kuglae

Kim * Therapeutics and Biotechnology Division, Korea Research Institute of Chemical Technology, 141 Gajeong-ro, Yuseong-gu, Daejeon, Republic of Korea Joo-Youn Lee * School of Pharmacy,

Sungkyunkwan University, Suwon, Republic of Korea Jaekyung Hyun * Center for New Technologies in Drug Discovery and Development, University of Southern California, Los Angeles, CA, USA

Vsevolod Katritch * Department of Chemistry, University of Southern California, Los Angeles, CA, USA Vsevolod Katritch * Department of Biomedical Science and Technology, Kyung Hee Medical

Science Research Institute, Kyung Hee University, Seoul, Republic of Korea Kwang Pyo Kim * Department of Medical Science and Engineering, Pohang University of Science and Technology, Pohang,

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 Google Scholar CONTRIBUTIONS J.S. carried out protein expression, purification and structure determination with the help of J.P. J.S. carried out data collection with the help of J.H. J.P.

and J.S. performed biochemical experiments with the help of K.K. and J.-Y.L. K.P.K. and J.J. performed mass spectroscopy and phospholipid characterization analysis. X.Q., D.W. and C.V.R.

performed comparative lipidomics analysis. J.H.L. and V.K. performed molecular dynamics simulations. J.S., J.P. and Y.C. designed the research; Y.C. wrote the manuscript with the help of

J.S., J.P. and K.P.K. CORRESPONDING AUTHORS Correspondence to Kwang Pyo Kim or Yunje Cho. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. PEER REVIEW PEER

REVIEW INFORMATION _Nature Structural & Molecular Biology_ thanks Bryan Roth and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer

reports are available. Primary Handling Editor: Katarzyna Ciazynska, in collaboration with the _Nature Structural & Molecular Biology_ team. ADDITIONAL INFORMATION PUBLISHER’S NOTE

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. EXTENDED DATA EXTENDED DATA FIG. 1 PURIFICATION OF THE GPR156-GO

COMPLEX. A–C, Size-exclusion chromatography profile (A), SDS-PAGE gel (B), and negative-staining microscopy analysis (C) of the purified GPR156-Go complex. Purification experiments of the

GPR156-Go complex in (B) were performed independently at least three times. Negative-staining microscopy analysis (C) was performed once. D, Representative cryo-EM micrograph of the

GPR156-Go complex. The cryo-EM data collection of GPR156-Go was performed once. E, 2D class averages of the Go-free GPR156. F, 2D class averages of the GPR156-Go complex. G, Comparison of

constitutive activities of GPR156 and GABAB in G-protein activation, measured by BRET2 assay. The activity of GABAB was observed in the absence or presence of 100 µM GABA. Data were mean ± 

SEM from three independent experiments, performed in technical triplicate. Statistical differences in ΔBRET were analyzed by two-way ANOVA with Dunnett’s post hoc test. H, cAMP inhibition

assay for GPR156 C-terminal truncation. Mock transfected with an empty vector was used as a negative control. cAMP production was normalized to a percent of WT activity. I, Surface

expression levels of WT and GPR156 mutants in the cAMP assay, measured by ELISA. Surface expression levels of GPR156 mutants were normalized to a percent of WT surface expression level. Data

in H and I were mean ± SEM from at least three independent experiments, performed in technical triplicate. Statistical differences were analyzed by one-way ANOVA with Dunnett’s post hoc

test, compared to WT (NS, not significant; ***_P_ < 0.001; ****_P_ < 0.0001). J, K, A model of GPR156 predicted from AlphaFold2 was used for initial docking and model building. The

N-terminal (1 to 39) and the C-terminal (336 to 814) regions are disordered and omitted in the figure. The model is colored according to the predicted Local Distance Difference Test (pLDDT)

score (J). The Predicted-Alignment-Error (PAE) plot of the GPR156 model (K). Source data EXTENDED DATA FIG. 2 FLOW CHART OF CRYO-EM AND DATA PROCESSING. Cryo-EM processing chart of the

G-protein coupled and G-protein free GPR156. EXTENDED DATA FIG. 3 ANALYSIS OF THE QUALITY OF THE CRYO-EM MAP. A, B, Angular distributions, Fourier shell correlation curves, and globally

refined cryo-EM density maps of GPR156-Go (A) and GPR156 alone (B). C–F, Angular distributions, Fourier shell correlation curves and locally refined cryo-EM density maps marked local

resolution of GPR156 dimer (C), G-protein-scFv16 (D), GPR156A/B (E), and GPR156C/D (F). G, H, Fourier shell correlation curves of the model versus the map generated through PHENIX.Mtriage64

of globally and locally refined GPR156-Go (G) and GPR156 alone (H). I, J, Global fitting of the structures of GPR156-Go into the composite map (I) and GPR156 alone into the globally refined

map (J). K, Cryo-EM densities and fitted atomic models. GF-GPR156, Go, GPR156A, GPR156B, and GC-GPR156 are shown in yellow, pink, salmon, cyan, and green, respectively. EXTENDED DATA FIG. 4

KEY FEATURES OF GPR156. A, Cryo-EM map of the GPR156 tetramer. B, Interface between the head-to-head dimer of GPR156. C, Interaction between TM7 of GPR156C and ICL2 of GPR156B. H-bonds

(Q314-D155 and E321-V158) and hydrophobic interactions (F318-V158 and I325-I159) are highlighted. D, E, Aligned structures of the two GPR156 dimers in two views; front view (D), bottom view.

Structures of the ICL2s are encircled (E). F–H, Structural comparison of GPR156B and GABAB-Gi (PDB:7EB2 ref. 5) with respect to ECL2 (F), TM7 (G), and ICLs (H). I, Cryo-EM map of the

GPR156-Go complex. J, K, Aligned structures of an GPR156 alone dimer with the GPR156-Go complex in two views; front view (J), bottom view (K). L, A density on top of the ECL2 in two

different views. M, Close-up view of the interactions between Y1463.55 (nGC) and H248ICL3 (GC). EXTENDED DATA FIG. 5 COMPARISON OF THE DIMERIC ARRANGEMENT OF GPR156 WITH OTHER CLASS C GPCRS

IN INACTIVE AND ACTIVE STATES. A–I, The TMDs of Class C GPCRs were aligned with GC-GPR156 (black line) and shown in the extracellular (top) view. GPR156-Go (A), inactive GABAB (red; PDB:

7C7S ref. 33) (B), active GABAB (orange; 7EB2 ref. 5) (C), active mGlu4 (beige; 7E9H ref. 7) (D), inactive mGlu2 (yellow; 7EPA ref. 37) (E), active mGlu2 (green; 7MTS ref. 6) (F), apo GPR158

(pink; 7EWL ref. 21) (G), inactive CaSR (blue; 7M3J ref. 36) (H), active CaSR (purple; 7M3F ref. 36) (I). The gray filled line represents nGC-GPR156. EXTENDED DATA FIG. 6 CHARACTERIZATION

OF PHOSPHOLIPID IN GPR156. A, Comparative lipidomics analysis of endogenous lipids bound to purified recombinant GPR156. PC and PE are enrichment in GPR156 fraction relative to total

cellular lysate. Bars show mean ± standard deviation from three independent experiments (dots). B–C, GPR156 activation as measured by GTPase-Glo assay for GPR156-Gi peptidisc containing PE

(B) or GPR156 in LMNG (C). A peptidisc containing GPRC5D-Gi and PE was incubated with PG as a control. Lower levels of residual GTP indicate higher level of G-protein activity. Data in (B)

and (C) were mean ± SEM from three independent experiments, performed in technical duplicate. Statistical differences were analyzed by one-way ANOVA with Dunnett’s post hoc test. D‒F,

Comparison of molecular dynamics simulation of GPR156 Go-coupled complexes with PG versus PC. D, Root-mean-square-fluctuation (r.m.s.f.) calculated of each subunit in the complexes; shading

refers to 95 % confidence interval (n = 5). E–F, Distribution of the closest distances between the sidechain of R2796.57 and the phospholipids against the closest distances between the

backbone of C216ECL2 and the phospholipids on the nGC protomer (E) and on the GC protomer (F). The shading refers to density estimated with a multivariate gaussian kernel; the marginal

distribution (by count) is shown on the sidebar. The black points in the background is the datapoints collected every 0.5 ns. All distances were calculated using only the heavy atoms. The

horizontal and vertical dotted line refers to 3.5 Å. G, Mutational effect on the F215ECL2 adjacent to the phospholipid head in G-protein activation, measured by BRET2 assay. Data were mean ±

 SEM from four independent experiments, performed in technical triplicate. Statistical differences were analyzed by two-way ANOVA with Dunnett’s post hoc test, compared to WT (NS, not

significant; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001). H‒I, Comparison of PC- and PG-bound GPR156 with representative snapshots from MD simulations of GPR156.

Close-up views of a phospholipid-binding site in the simulations of PC-bound (H) and PG-bound GPR156 (I). nGC protomer and GC protomer are shown on top and bottom, respectively. Three

representative snapshots (970, 985, and 1000 ns) of a simulation trajectory are displayed. Source data EXTENDED DATA FIG. 7 SEQUENCE ALIGNMENT OF GPR156 WITH OTHER HUMAN CLASS C GPCRS. The

conserved residues are marked in yellow. The alignment was output from GPCRdb (gpcrdb.org) and edited by using snapgene (snapgene.com). EXTENDED DATA FIG. 8 PHOSPHOLIPIDS IN GPR156. A, In

one protomer, the phenyl ring is flipped by 85° toward the dimer interface, creating space for the lateral movement of the phospholipid. We refer this conformer to as an open form. The W229

indole ring can be repositioned upon the conformational change of the F275 ring. B, In another protomer, F275 is packed against the fatty-acyl chain of the phospholipid to form a closed

conformation. C, Density at the top half of the dimer interface, in which a CLR molecule is modelled. D, E, Densities near V223 (D) and W284 (E) in GPR156. F, Comparison of the

phospholipid-binding in GPR156 with that of GABAB2. G, Comparison of the phospholipid-binding in GPR156 with the PAM-binding in mGlu2 and CaSR. H–J, cAMP inhibition assay for GPR156 mutated

at the phospholipid binding site (H), dimer interface (I, J). Data were mean ± SEM from at least three independent experiments, performed in technical triplicate. Statistical differences

were analyzed by one-way ANOVA with Dunnett’s post hoc test, compared to WT (NS, not significant; **P < 0.01; ***P < 0.001; ****P < 0.0001). Source data EXTENDED DATA FIG. 9

STRUCTURAL TRANSITION OF THE CYTOPLASMIC FACE OF GPR156 IN THE GO PROTEIN-COUPLED STATE. A–C, Comparison of the Go-free, nGC-, and GC-protomers in three different views; front (A),

extracellular (B), and cytoplasmic view (C). D–E, Aligned ICL1s (D) and ICL2s (E) of the GPR156B with GC-protomers. The major structural differences in the C-terminal loop and ICLs are

indicated by red arrows. F, cAMP inhibition assay for GPR156 mutated at ICL2. Data were mean ± SEM from three independent experiments. Statistical differences were analyzed by one-way ANOVA

with Dunnett’s post hoc test, compared to WT. G–L, Comparison of the TMD and ICLs of GPR156 with those of other class C GPCRs–Gi; GABAB-Gi1 (PDB: 7EB2 ref. 5), mGlu2-Gi1 (7MTS ref. 6),

mGlu4-Gi3 (7E9H ref. 7). Comparison of the TMD of GPR156 GC-protomer with those of other class C GPCRs bound to Gi in three different views; front (G), extracellular (H), and cytoplasmic

view (I). Comparison of ICL1 (J), ICL2 (K), and ICL3 and the C-terminal loop (L). M, Mutational effect on CTL of GPR156 in G-protein activation, measured by BRET2 assay. Data were mean ± SEM

from three independent experiments, performed in technical triplicate. Statistical differences were analyzed by two-way ANOVA with Dunnett’s post hoc test, compared to WT (NS, not

significant; **P < 0.01; ***P < 0.001; ****P < 0.0001). Source data EXTENDED DATA FIG. 10 GO BINDING TO GPR156. A–C, Comparison of Go binding between GPR156 and other class C GPCRs:

GABAB-Gi1 (PDB: 7EB2 ref. 5) (A), mGlu2-Gi1 (7MTS ref. 6) (B), mGlu4-Gi3 (7E9H ref. 7) (C). The red arrows indicate the structural differences in the receptors and the G proteins. D.

Sequence alignment of the residues in the α5 helix in different human Gα proteins. Residues interacting with GPR156 are marked with a light green circle. Absolutely conserved and highly

conserved (≥50%) residues are marked with orange and yellow colors, respectively. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Notes 1–7, Videos 1–3, and Tables 1–4.

REPORTING SUMMARY PEER REVIEW FILE SUPPLEMENTARY VIDEO 1 Dynamics of TM4 and ICL2 of the GPR156B protomer revealed by 3D variability analysis. SUPPLEMENTARY VIDEO 2 Flexibility of CTL in the

GPR156 GC protomer. SUPPLEMENTARY VIDEO 3 Rigid body movement of the GC protomer with respect to the G protein. SOURCE DATA SOURCE DATA FIG. 2 Statistical source data. SOURCE DATA FIG. 3

Statistical source data. SOURCE DATA FIG. 5 Statistical source data. SOURCE DATA EXTENDED DATA FIG./TABLE 1 Unprocessed gel SOURCE DATA EXTENDED DATA FIG./TABLE 1 Statistical source data.

SOURCE DATA EXTENDED DATA FIG./TABLE 6 Statistical source data. SOURCE DATA EXTENDED DATA FIG./TABLE 8 Statistical source data. SOURCE DATA EXTENDED DATA FIG./TABLE 9 Statistical source

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permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Shin, J., Park, J., Jeong, J. _et al._ Constitutive activation mechanism of a class C GPCR. _Nat Struct Mol Biol_ 31, 678–687 (2024).

https://doi.org/10.1038/s41594-024-01224-7 Download citation * Received: 22 February 2023 * Accepted: 09 January 2024 * Published: 08 February 2024 * Issue Date: April 2024 * DOI:

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