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Positive allosteric mechanisms of adenosine A1 receptor-mediated analgesia

Nature volume 597, pages 571–576 (2021)Cite this article

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Abstract

The adenosine A1 receptor (A1R) is a promising therapeutic target for non-opioid analgesic agents to treat neuropathic pain1,2. However, development of analgesic orthosteric A1R agonists has failed because of a lack of sufficient on-target selectivity as well as off-tissue adverse effects3. Here we show that [2-amino-4-(3,5-bis(trifluoromethyl)phenyl)thiophen-3-yl)(4-chlorophenyl)methanone] (MIPS521), a positive allosteric modulator of the A1R, exhibits analgesic efficacy in rats in vivo through modulation of the increased levels of endogenous adenosine that occur in the spinal cord of rats with neuropathic pain. We also report the structure of the A1R co-bound to adenosine, MIPS521 and a Gi2 heterotrimer, revealing an extrahelical lipid–detergent-facing allosteric binding pocket that involves transmembrane helixes 1, 6 and 7. Molecular dynamics simulations and ligand kinetic binding experiments support a mechanism whereby MIPS521 stabilizes the adenosine–receptor–G protein complex. This study provides proof of concept for structure-based allosteric drug design of non-opioid analgesic agents that are specific to disease contexts.

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Fig. 1: MIPS521 reduces spinal nociceptive signalling and mechanical allodynia in an animal model of neuropathic pain.
Fig. 2: Comparison of the structures of the A1R–Gi2 complex in the presence and absence of the PAM MIPS521.
Fig. 3: Identification of an extrahelical lipid-facing allosteric pocket involving TM1, TM6 and TM7 on the A1R.
Fig. 4: MIPS521 stabilizes the A1R–Gi2 ternary complex.

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Data availability

Cryo-EM coordinates have been deposited in the PDB under the accession codes 7LD3 (MIPS521- and ADO-bound A1R–Gi2 complex) and 7LD4 (ADO-bound A1R–Gi2 complex); the corresponding electron microscopy maps have been deposited in the Electron Microscopy Data Bank (EMDB) under accession codes EMD-23280 and EMD-23281.

References

  1. Nakamura, I., Ohta, Y. & Kemmotsu, O. M. Characterization of adenosine receptors mediating spinal sensory transmission related to nociceptive information in the rat. Anesthesiology 87, 577–584 (1997).

    Article  CAS  PubMed  Google Scholar 

  2. Poon, A. & Sawynok, J. Antinociception by adenosine analogs and inhibitors of adenosine metabolism in an inflammatory thermal hyperalgesia model in the rat. Pain 74, 235–245 (1998).

    Article  PubMed  Google Scholar 

  3. Zylka, M. J. Pain-relieving prospects for adenosine receptors and ectonucleotidases. Trends Mol. Med. 17, 188–196 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. King, A. Analgesia without opioids. Nature 573, S4 (2019).

    Article  ADS  CAS  Google Scholar 

  5. Busse, J. W. et al. Opioids for chronic noncancer pain: a systematic review and meta-analysis. JAMA 320, 2448–2460 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Ribeiro, J. A., Sebastião, A. M. & de Mendonça, A. Adenosine receptors in the nervous system: pathophysiological implications. Prog. Neurobiol. 68, 377–392 (2002).

    Article  CAS  PubMed  Google Scholar 

  7. Choca, J. I., Proudfit, H. K. & Green, R. D. Identification of A1 and A2 adenosine receptors in the rat spinal cord. J. Pharmacol. Exp. Ther. 242, 905–910 (1987).

    CAS  PubMed  Google Scholar 

  8. Choca, J. I., Green, R. D. & Proudfit, H. K. Adenosine A1 and A2 receptors of the substantia gelatinosa are located predominantly on intrinsic neurons: an autoradiography study. J. Pharmacol. Exp. Ther. 247, 757–764 (1988).

    CAS  PubMed  Google Scholar 

  9. Yang, Z. et al. Cardiac overexpression of A1-adenosine receptor protects intact mice against myocardial infarction. Am. J. Physiol. Heart. Circ. Physiol. 282, H949–H955 (2002).

    Article  CAS  PubMed  Google Scholar 

  10. Christopoulos, A. & Kenakin, T. G protein-coupled receptor allosterism and complexing. Pharmacol. Rev. 54, 323–374 (2002).

    Article  CAS  PubMed  Google Scholar 

  11. May, L. T. et al. Allosteric modulation of G protein-coupled receptors. Annu. Rev. Pharmacol. Toxicol. 47, 1–51 (2007).

    Article  CAS  PubMed  Google Scholar 

  12. Bruns, R. F. & Fergus, J. H. Allosteric enhancement of adenosine A1 receptor binding and function by 2-amino-3-benzoylthiophenes. Mol. Pharmacol. 38, 939–949 (1990).

    CAS  PubMed  Google Scholar 

  13. Li, X. et al. Spinal noradrenergic activation mediates allodynia reduction from an allosteric adenosine modulator in a rat model of neuropathic pain. Pain 97, 117–125 (2002).

    Article  CAS  PubMed  Google Scholar 

  14. Childers, S. R. et al. Allosteric modulation of adenosine A1 receptor coupling to G-proteins in brain. J. Neurochem. 93, 715–723 (2005).

    Article  CAS  PubMed  Google Scholar 

  15. Vincenzi, F. et al. TRR469, a potent A1 adenosine receptor allosteric modulator, exhibits anti-nociceptive properties in acute and neuropathic pain models in mice. Neuropharmacology 81, 6–14 (2014).

    Article  CAS  PubMed  Google Scholar 

  16. Gramec, D., Mašič, L. P. & Dolenc, M. S. Bioactivation potential of thiophene-containing drugs. Chem. Res. in Toxicol. 27, 1344–1358 (2014).

    Article  CAS  Google Scholar 

  17. Nguyen, A. T. et al. Role of the second extracellular loop of the adenosine A1 receptor on allosteric modulator binding, signaling, and cooperativity. Mol. Pharmacol. 90, 715–725 (2016).

    Article  CAS  PubMed  Google Scholar 

  18. Miao, Y. et al. Structural basis for binding of allosteric drug leads in the adenosine A1 receptor. Sci. Rep. 8, 16836 (2018).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  19. Glukhova, A. et al. Structure of the adenosine A1 receptor reveals the basis for subtype selectivity. Cell 168, 867–877 (2017).

    Article  CAS  PubMed  Google Scholar 

  20. Thal, D. M. et al. Structural insights into G-protein-coupled receptor allostery. Nature 559, 45–53 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  21. Miao, Y., Feher, V. A. & McCammon, J. A. Gaussian accelerated molecular dynamics: unconstrained enhanced sampling and free energy calculation. J. Chem. Theory Comput. 11, 3584–3595 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Imlach, W. L. et al. A positive allosteric modulator of the adenosine A1 receptor selectively inhibits primary afferent synaptic transmission in a neuropathic pain model. Mol. Pharmacol. 88, 460–468 (2015).

    Article  CAS  PubMed  Google Scholar 

  23. Aurelio, L. et al. Allosteric modulators of the adenosine A1 receptor: synthesis and pharmacological evaluation of 4-substituted 2-amino-3-benzoylthiophenes. J. Med. Chem. 52, 4543–4547 (2009).

    Article  CAS  PubMed  Google Scholar 

  24. Valant, C. et al. Separation of on-target efficacy from adverse effects through rational design of a bitopic adenosine receptor agonist. Proc. Natl Acad. Sci. USA 111, 4614–4619 (2014).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  25. Schulte, G. et al. Distribution of antinociceptive adenosine A1 receptors in the spinal cord dorsal horn, and relationship to primary afferents and neuronal subpopulations. Neuroscience 121, 907–916 (2003).

    Article  CAS  PubMed  Google Scholar 

  26. Wu, Z.-Y. et al. Endomorphin-2 decreases excitatory synaptic transmission in the spinal ventral horn of the rat. Front. Neural Circuits 11, 55–55 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Geiger, J. G., LaBella, F. S. & Nagy, J. I. Characterization and localization of adenosine receptors in rat spinal cord. J. Neurosci. 4, 2303–2310 (1984).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Johansson, B. et al. Hyperalgesia, anxiety, and decreased hypoxic neuroprotection in mice lacking the adenosine A1 receptor. Proc. Natl Acad. Sci. USA 98, 9407–9412 (2001).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  29. Liang, Y. L. et al. Dominant negative G proteins enhance formation and purification of agonist–GPCR–G protein complexes for structure determination. ACS Pharmacol. Transl. Sci. 1, 12–20 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Draper-Joyce, C. J. et al. Structure of the adenosine-bound human adenosine A1 receptor–Gi complex. Nature 558, 559–563 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  31. Leach, K. et al. Molecular mechanisms of action and in vivo validation of an M4 muscarinic acetylcholine receptor allosteric modulator with potential antipsychotic properties. Neuropsychopharmacology 35, 855–869 (2010).

    Article  CAS  PubMed  Google Scholar 

  32. Zhang, D. et al. Two disparate ligand-binding sites in the human P2Y1 receptor. Nature 520, 317–321 (2015).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. Cheng, R. K. et al. Structural insight into allosteric modulation of protease-activated receptor 2. Nature 545, 112–115 (2017).

    Article  ADS  CAS  PubMed  Google Scholar 

  34. Robertson, N. et al. Structure of the complement C5a receptor bound to the extra-helical antagonist NDT9513727. Nature 553, 111–114 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  35. Shao, Z. et al. Structure of an allosteric modulator bound to the CB1 cannabinoid receptor. Nat. Chem. Biol. 15, 1199–1205 (2019).

    Article  CAS  PubMed  Google Scholar 

  36. Lu, J. et al. Structural basis for the cooperative allosteric activation of the free fatty acid receptor GPR40. Nat. Struct. Mol. Biol. 24, 570–577 (2017).

    Article  CAS  PubMed  Google Scholar 

  37. Liu, X. et al. Mechanism of β2AR regulation by an intracellular positive allosteric modulator. Science 364, 1283–1287 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  38. Zhuang, Y. et al. Mechanism of dopamine binding and allosteric modulation of the human D1 dopamine receptor. Cell Res. 31, 593–596 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. DeVree, B. T. et al. Allosteric coupling from G protein to the agonist-binding pocket in GPCRs. Nature 535, 182–186 (2016).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  40. Seltzer, Z., Dubner, R. & Shir, Y. A novel behavioral model of neuropathic pain disorders produced in rats by partial sciatic nerve injury. Pain 43, 205–218 (1990).

    Article  PubMed  Google Scholar 

  41. Imlach, W. L. et al. Glycinergic dysfunction in a subpopulation of dorsal horn interneurons in a rat model of neuropathic pain. Sci. Rep.6, 37104 (2016).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  42. Bonin, R. P., Bories, C. & De Koninck, Y. A simplified up-down method (SUDO) for measuring mechanical nociception in rodents using von Frey filaments. Mol. Pain 10, 10–26 (2014).

    Article  Google Scholar 

  43. Størkson, R. V. et al. Lumbar catheterization of the spinal subarachnoid space in the rat. J. Neurosci. Methods 65, 167–172 (1996).

    Article  PubMed  Google Scholar 

  44. King, T. et al. Unmasking the tonic-aversive state in neuropathic pain. Nat. Neurosci. 12, 1364–1366 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Usoskin, D. et al. Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing. Nat. Neurosci.18, 145–153 (2015).

    Article  CAS  PubMed  Google Scholar 

  46. Schorb, M. et al. Software tools for automated transmission electron microscopy. Nat. Methods 16, 471–477 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Zhang, K. Gctf: real-time CTF determination and correction. J. Struct. Biol.193, 1–12 (2016).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  49. Maeda, S. et al. Development of an antibody fragment that stabilizes GPCR/G-protein complexes. Nat. Commun. 9, 3712 (2018).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  50. Emsley, P. et al. Features and development of Coot. Acta Crystallogr. D 66, 486–501 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Adams, P. D. et al. PHENIX: a comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D 66, 213–221 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Chen, V. B. et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr. D 66, 12–21 (2010).

    Article  CAS  PubMed  Google Scholar 

  53. Pettersen, E. F. et al. UCSF Chimera—a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004).

    Article  CAS  PubMed  Google Scholar 

  54. Baltos, J. A. et al. Quantification of adenosine A1 receptor biased agonism: implications for drug discovery. Biochem. Pharmacol. 99, 101–112 (2016).

    Article  CAS  PubMed  Google Scholar 

  55. Nguyen, A. T. et al. Extracellular loop 2 of the adenosine A1 receptor has a key role in orthosteric ligand affinity and agonist efficacy. Mol. Pharmacol. 90, 703–714 (2016).

    Article  CAS  PubMed  Google Scholar 

  56. Morris, G. M. et al. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J. Comput. Chem. 30, 2785–2791 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Dror, R. O. et al. Structural basis for nucleotide exchange in heterotrimeric G proteins. Science 348, 1361–1365 (2015).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  58. Dror, R. O. et al. Activation mechanism of the β2-adrenergic receptor. Proc. Natl Acad. Sci. USA 108, 18684–18689 (2011).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  59. Wang, J. & Miao, Y. Mechanistic insights into specific G protein interactions with adenosine receptors. J. Phys. Chem. B 123, 6462–6473 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Humphrey, W., Dalke, A. & Schulten, K. VMD: xisual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996).

    Article  CAS  PubMed  Google Scholar 

  61. Vanommeslaeghe, K. & MacKerell, A. D. CHARMM additive and polarizable force fields for biophysics and computer-aided drug design. Biochim. Biophys. Acta 1850, 861–871 (2015).

    Article  CAS  PubMed  Google Scholar 

  62. Huang, J. et al. CHARMM36m: an improved force field for folded and intrinsically disordered proteins. Nat. Methods 14, 71–73 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Klauda, J. B. et al. Update of the CHARMM all-atom additive force field for lipids: validation on six lipid types. J. Phys. Chem. B 114, 7830–7843 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Vanommeslaeghe, K. & MacKerell, A. D. Automation of the CHARMM General Force Field (CGenFF) I: bond perception and atom typing. J. Chem. Inf. Model. 52, 3144–3154 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Vanommeslaeghe, K., Raman, E. P. & MacKerell, A. D. Automation of the CHARMM General Force Field (CGenFF) II: assignment of bonded parameters and partial atomic charges. J. Chem. Inf. Model. 52, 3155–3168 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Miao, Y. & McCammon, J. A. Graded activation and free energy landscapes of a muscarinic G-protein–coupled receptor. Proc. Natl Acad. Sci. USA 113, 12162–12167 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Miao, Y. & McCammon, J. A. Mechanism of the G-protein mimetic nanobody binding to a muscarinic G-protein-coupled receptor. Proc. Natl Acad. Sci. USA 115, 3036–3041 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Phillips, J. C. et al. Scalable molecular dynamics with NAMD. J. Comput. Chem. 26, 1781–1802 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. 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 (1993).

    Article  ADS  CAS  Google Scholar 

  70. Ryckaert, J.-P., Ciccotti, G. & Berendsen, H. J. Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J. Comput. Phys. 23, 327–341 (1977).

    Article  ADS  CAS  Google Scholar 

  71. Bernstein, N. et al. QM/MM simulation of liquid water with an adaptive quantum region. Phys. Chem. Chem. Phys. 14, 646–656 (2012).

    Article  CAS  PubMed  Google Scholar 

  72. Roe, D. R. & Cheatham, T. E. PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data. J. Chem. Theory Comput. 9, 3084–3095 (2013).

    Article  CAS  PubMed  Google Scholar 

  73. Whorton, M. R. et al. A monomeric G protein-coupled receptor isolated in a high-density lipoprotein particle efficiently activates its G protein. Proc. Natl Acad. Sci. USA 104, 7682–7687 (2007).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by the National Health and Medical Research Council of Australia (NHMRC) project grants 1145420 and 1147291, NHMRC program grant 1050083, American Heart Association grant 17SDG33370094 and the National Institutes of Health grant R01GM132572. P.M.S., W.L.I. and D.W. are NHMRC Senior Principal Research, Career Development and Senior Research Fellows, respectively. C.J.D.-J., A.G. and D.M.T. are Australian Research Council Discovery Early Career Research Fellows. L.T.M. is an Australian Heart Foundation Future Leaders Fellow. J.C. acknowledges support from the Swedish Research Council (2017-04676). We are grateful to S. Charman and K. White for performing the VCP171 and MIPS521 plasma and liver microsome stability studies. We acknowledge use of facilities within the Monash Ramaciotti Cryo-EM platform. This work was supported by the MASSIVE HPC facility (https://www.massive.org.au) and the Extreme Science and Engineering Discovery Environment supercomputing award TG-MCB180049.

Author information

Author notes

  1. Christopher J. Draper-Joyce

    Present address: The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Victoria, Australia

  2. Alisa Glukhova

    Present address: Structural Biology Division, Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia

  3. Alisa Glukhova

    Present address: Department of Biochemistry and Pharmacology, University of Melbourne, Parkville, Victoria, Australia

Authors and Affiliations

  1. Drug Discovery Biology and Department of Pharmacology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia

    Christopher J. Draper-Joyce, Anh T. N. Nguyen, Ling Yeong Chia, Celine Valant, David M. Thal, Denise Wootten, Paul J. White, Lauren T. May, Patrick M. Sexton, Alisa Glukhova & Arthur Christopoulos

  2. Department of Physiology, Monash Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia

    Rebecca Bhola, India Cowie-Kent, Kelly O’Sullivan & Wendy L. Imlach

  3. Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, USA

    Jinan Wang, Apurba Bhattarai & Yinglong Miao

  4. Department of Biochemistry and Molecular Biology, Monash University, Clayton, Victoria, Australia

    Hariprasad Venugopal

  5. ARC Centre for Cryo-electron Microscopy of Membrane Proteins, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia

    Denise Wootten, Patrick M. Sexton & Arthur Christopoulos

  6. Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden

    Nicolas Panel & Jens Carlsson

  7. Discipline of Pharmacology, Faculty of Medicine and Health, University of Sydney, Camperdown, New South Wales, Australia

    Macdonald J. Christie

  8. Medicinal Chemistry, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia

    Peter Scammells

  9. Graduate School of Medicine, University of Tokyo, Tokyo, Japan

    Radostin Danev

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  1. Christopher J. Draper-Joyce
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Contributions

C.J.D.-J. developed the expression and purification strategy, performed virus production, insect cell expression and purification, generated nanodisc and nanodisc-based pharmacological assays, performed negative-stain EM data acquisition and analysis, and prepared samples for cryo-EM. R.B. prepared pain models for in vivo studies, surgical placement of intrathecal catheters, drug administration and behavioural testing (von Frey and rotarod), and analysed in vivo data. K.O. prepared pain models for electrophysiology studies and pain behavioural testing (von Frey) on rats used for electrophysiology. I.C.-K. assisted R.B. with behavioural assays. W.L.I. performed spinal cord electrophysiology, surgeries for pain models and intrathecal catheter placement, evoked pain behaviour (von Frey) and spontaneous pain behaviour (conditioned place preference) studies, supervised experiments and oversaw experimental design of ex vivo and in vivo experiments. L.Y.C conducted atrial contraction organ bath experiments. P.J.W. oversaw atrial contraction design, experiments and analysis. J.W. and A.B. designed, performed and analysed molecular dynamics simulations. Y.M. oversaw molecular dynamics simulations and analysis. N.P. and J.C. designed, performed and analysed molecular docking studies. D.M.T. developed the expression and purification strategy and assisted with biochemistry and reconstitution of nanodiscs. H.V. organized microscopy time and provided oversight of image acquisition within the Monash EM facility. A.T.N.N. performed whole cell radioligand binding pharmacological assays. A.T.N.N. performed cAMP pharmacological assays, designed the A1R mutation strategy, generated mutant A1Rs and associated stable cell lines, and performed whole-cell radioligand binding pharmacological assays. L.T.M. supervised A1R mutagenesis, whole-cell pharmacological assays and atrial contraction assays. C.J.D.-J., A.T.T.N., C.V. and L.T.M. performed data analysis. P.S. supervised medicinal chemistry design and synthesis. R.D. performed sample plunging for cryo-EM, imaging and data collection. R.D., M.J.C., L.T.M., D.W. and P.M.S. assisted with data interpretation and preparation of the manuscript. A.G. developed the expression and purification strategy, performed negative stain transmission EM, cryo-EM data processing, model building, refinement and validation. C.J.D.-J., Y.M., W.L.I., A.G. and A.C. wrote the manuscript. P.M.S., Y.M., A.G., W.L.I. and A.C. supervised the project.

Corresponding authors

Correspondence to Alisa Glukhova, Wendy L. Imlach or Arthur Christopoulos.

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Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Grégory Scherrer, Irina Tikhonova, Daniel Wacker and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Physiological effects of VCP171 and MIPS521.

a, Chemical structure of VCP171. b, Time courses of paw withdrawal threshold (PWT) to mechanical stimulus by von Frey filaments in nerve-injured rats post-intrathecal administration of VCP171 (blue) or MIPS521 (red). Significance to vehicle control was determined using Greenhouse-Geisser correction for multiple comparisons, corrected with Dunnett’s post-hoc test, * P < 0.05, ** P < 0.01, *** P < 0.001. Data are shown as mean +/- SEM (n=8-10 rats per data group) c, Single trial place preference conditioning with intrathecal VCP171 (30 µg, blue), MIPS521 (10 µg, red) and morphine (10 µg, black) increased the time nerve-injured rats spent in the drug paired chamber, with a corresponding decrease in the vehicle paired chamber. Sham surgery rats showed no chamber preference. Empty circles show individual data points, and bars show mean +SEM (n = 8 per group). Significance was determined using a two-tailed unpaired t test assuming unequal variance, * P < 0.05, ** P < 0.01, compared to vehicle control. d, Rotarod latency in rats following intrathecal administration of VCP171 (blue) or MIPS521 (red) is not significantly different to vehicle controls, whereas intrathecal administration of morphine reduces rotarod latency to fall. Data are shown as mean +/- SEM (n = 3-4 per group). Significance was determined using a two-tailed unpaired t test assuming unequal variance, * P < 0.05, ** P < 0.01, compared to vehicle control. e, Effect of CPA (black; n = 4) or MIPS521 (solid red; n = 6) on rate of atrial contraction. Data represent mean ± SD.

Extended Data Fig. 2

Effects of VCP171 and MIPS521 on spontaneous excitatory synaptic activity. a, Examples of spontaneous excitatory postsynaptic potentials (sEPSCs) recorded from neurons of the superficial laminae of the spinal dorsal horn of nerve-injured rats. b, sEPSC frequency and amplitude were reduced following superfusion of VCP171 or MIPS521, which is reversed by the antagonist, DPCPX (n = 8 per group). Significance compared to baseline was determined using a two-tailed paired t test, *P < 0.05, **P < 0.01.

Extended Data Fig. 3 Expression and purification of the MIPS521–ADO–A1R–Gi2 complex.

a, Expression and purification flowchart for the A1R–Gi2 complex. A1R and the Gi2 heterotrimer with Gβ1γ2 were expressed separately in insect cell membranes. Addition of ADO (1 mM) and MIP521 (100 nM) initiated complex formation, which was solubilized with 0.5% (w/v) lauryl maltose neopentyl glycol and 0.05% (w/v) cholesteryl hemisuccinate. Solubilized A1R and A1R –Gi2 complex was immobilized on Flag antibody resin. Flag-eluted fractions were purified by size-exclusion chromatography (SEC). Illustrations taken from ChemDraw. b, SDS–PAGE/western blot of the purified A1R–Gi2 complex. An anti-His antibody was used to detect Flag–A1R-His and Gβ1-His (red) and an anti-Gi2 antibody was used to detect Gαi2 (green). For gel source data, see Supplementary Fig. 1. c, SDS–PAGE/Coomassie blue stain of the purified complex concentrated from the Superdex 200 Increase 10/30 column. For gel source data, see Supplementary Fig. 1. d, Representative elution profile of Flag-purified complex on Superdex 200 Increase 10/30 SEC.

Extended Data Fig. 4 Cryo-EM data processing for the MIPS521–ADOβ–A1R–Gi2 and ADO–A1R–Gi2 complexes.

a, MIPS521–ADOβ–A1R–Gi2; b, ADO–A1R–Gi2. Representative cryo-EM micrographs of each of the complexes. Reference-free 2D class averages of the complexes in LMNG and CHS detergent micelles. Gold-standard Fourier shell correlation (FSC) curves, showing the overall nominal resolution of 3.2 Å and 3.3 Å, respectively, at FSC 0.143. Corresponding 3D cryo-EM maps coloured according to local resolution estimation (Å) in Relion. c, Atomic resolution model of representative regions from the MIPS521-ADO-A1R-Gi2 structure of the A1R transmembrane domain, ADO, and MIPS521. The molecular model is shown in ball and stick representation, coloured by heteroatom, and the cryo-EM map displayed in mesh contoured at 0.02.

Extended Data Fig. 5 Stable hydrogen bonds formed between residue S6.47/L7.41 in A1R and MIPS521 in A1R–Gi2–MIPS521.

a, c, GaMD and b, d, cMD simulations. Each simulation trace is displayed in a different colour (black, red, blue). The lines depict the running average over 2 ns.

Extended Data Fig. 6 Affinity of orthosteric ligands at mutations of the MIPS521 extrahelical allosteric binding pocket.

a, c, The affinity of (a) [3H]-DPCPX and (c) NECA for wildtype and mutant A1Rs performed in FlpInCHO cells. b, Bmax; determined by [3H]-DPCPX radioligand saturation binding studies. Data are the means + S.E.M. of 3-7 independent experiments (shown as circles) performed in duplicate. *P < 0.05 (compared with WT; one-way analysis of variance, Dunnett’s post-hoc test).

Extended Data Fig. 7 Extrahelical binding sites for allosteric modulators of class A GPCRs.

The unique extrahelical binding pose of MIPS521 in the A1R (orange) compared to previously reported extrahelical allosteric binding pockets for class A GPCRs in P2Y1R (BPTU, red; PDB 4XNV), PAR2 (AZ3451, yellow; PDB 5NDZ), CB1 (ORG28569, green; 6KQI), GPR40 (AP8, cyan; PDB 5TZY), C5aR (NDT9513727, blue; PDB 5O9H), D1R (LY3154207, navy; PDB 7LJD), and β2AR (Compound-6FA, pink; PDB 6N48).

Extended Data Fig. 8 Stability of MIPS521 at the allosteric binding site of A1R is enhanced by Gi2 protein coupling to the receptor.

a, b, RMSD (Å) of MIPS521 relative to the starting cryo-EM conformation obtained from GaMD simulations in the (a) absence and (b) presence of Gi2. c, d, RMSD (Å) of MIPS521 relative to the starting cryo-EM conformation obtained from cMD simulations in the (c) absence and (d) presence of Gi2. Each condition represents three GaMD/cMD simulations, with each simulation trace displayed in a different colour (black, red, blue). Lines depict the running average over 2 ns.

Extended Data Fig. 9 MIPS521 stabilizes the A1R–Gi2 ternary complex.

a–d, RMSD (Å) of ADO from cMD simulations completed in the (a) absence or (b) presence of MIPS521, (c) Gi2, or (d) both Gi2 and MIPS521. e–h, Distance between the intracellular ends of TM3 and TM6 (measured as the distance in Å between Arg1053.50 and Glu2296.30) in the (e) absence or (f) presence of MIPS521, (g) Gi2, or (h) both Gi2 and MIPS521. Each condition represents three cMD simulations, with each simulation trace displayed in a different colour (black, red, blue). The lines depict the running average over 2 ns. i, j, Distance between A1R and Gi2 (measured as the distance in Å between the NPxxY motif of A1R and the C terminus of the Gα α5 helix) from GaMD simulations in the (i) absence and (j) presence of MIPS521. k, l, Distance between A1R and Gi2 from cMD simulations in the (k) absence and (l) presence of MIPS521. Each condition represents three GaMD/cMD simulations, with each simulation trace displayed in a different colour (black, red, blue). Thick lines depict the running average over 2 ns. m–p, Flexibility change upon removal of PAM and/or Gi2 protein from the ADO-bound A1R obtained from GaMD simulations.(m, RMSFs of the A1R-Gi2-MIPS521. A colour scale of 0.0 Å (blue) to 5.0 Å (red) was used. n, Change in the RMSFs of the A1R-Gi2 when MIPS521 was removed from A1R-Gi2-MIPS521. o, Change in the RMSFs of the A1R and MIPS521 when the Gi2 was removed from A1R-Gi2-MIPS521. p, Change in the RMSFs of the A1R when the Gi2 and MIPS521 were removed from A1R-Gi2-MIPS521 system. A colour scale of -2.0 Å (blue) to 2.0 Å (red) was used for n, o and p.

Extended Data Table 1 Cryo-EM data collection, refinement and validation statistics
Full size table

Supplementary information

Supplementary Information

This file contains Supplementary Tables 1–6 and their accompanying legends.

Reporting Summary

Supplementary Figure 1

Original western and SDS–PAGE gels used to generate Extended Data Fig. 3b, c. Dotted boxes indicate the area of gel used.

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Draper-Joyce, C.J., Bhola, R., Wang, J. et al. Positive allosteric mechanisms of adenosine A1 receptor-mediated analgesia. Nature 597, 571–576 (2021). https://doi.org/10.1038/s41586-021-03897-2

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