Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Molecular basis of β-arrestin coupling to formoterol-bound β1-adrenoceptor


The β1-adrenoceptor (β1AR) is a G-protein-coupled receptor (GPCR) that couples1 to the heterotrimeric G protein Gs. G-protein-mediated signalling is terminated by phosphorylation of the C terminus of the receptor by GPCR kinases (GRKs) and by coupling of β-arrestin 1 (βarr1, also known as arrestin 2), which displaces Gs and induces signalling through the MAP kinase pathway2. The ability of synthetic agonists to induce signalling preferentially through either G proteins or arrestins—known as biased agonism3—is important in drug development, because the therapeutic effect may arise from only one signalling cascade, whereas the other pathway may mediate undesirable side effects4. To understand the molecular basis for arrestin coupling, here we determined the cryo-electron microscopy structure of the β1AR–βarr1 complex in lipid nanodiscs bound to the biased agonist formoterol5, and the crystal structure of formoterol-bound β1AR coupled to the G-protein-mimetic nanobody6 Nb80. βarr1 couples to β1AR in a manner distinct to that7 of Gs coupling to β2AR—the finger loop of βarr1 occupies a narrower cleft on the intracellular surface, and is closer to transmembrane helix H7 of the receptor when compared with the C-terminal α5 helix of Gs. The conformation of the finger loop in βarr1 is different from that adopted by the finger loop of visual arrestin when it couples to rhodopsin8. β1AR coupled to βarr1 shows considerable differences in structure compared with β1AR coupled to Nb80, including an inward movement of extracellular loop 3 and the cytoplasmic ends of H5 and H6. We observe weakened interactions between formoterol and two serine residues in H5 at the orthosteric binding site of β1AR, and find that formoterol has a lower affinity for the β1AR–βarr1 complex than for the β1AR–Gs complex. The structural differences between these complexes of β1AR provide a foundation for the design of small molecules that could bias signalling in the β-adrenoceptors.

This is a preview of subscription content

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Overall cryo-EM reconstruction of the β1AR6P–βarr1 complex.
Fig. 2: Structure of βarr1 in complex with β1AR6P.
Fig. 3: Comparison of the receptor-coupling interfaces in the β1AR6P–βarr1 and β2AR–Gs complexes.
Fig. 4: Differences between formoterol-bound β1AR coupled to either βarr1 or Nb80.

Data availability

Structures of formoterol-bound β1AR–Nb80 and formoterol-bound β1AR– βarr1–Fab30 have been deposited in the PDB with accession numbers 6IBL and 6TKO, respectively. The cryo-EM data for 6TKO has also been deposited in the Electron Microscopy Data Bank under accession number EMDB-10515. All other data are included within the paper and its Supporting Information.


  1. 1.

    Evans, B. A., Sato, M., Sarwar, M., Hutchinson, D. S. & Summers, R. J. Ligand-directed signalling at β-adrenoceptors. Br. J. Pharmacol. 159, 1022–1038 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    DeWire, S. M., Ahn, S., Lefkowitz, R. J. & Shenoy, S. K. β-arrestins and cell signaling. Annu. Rev. Physiol. 69, 483–510 (2007).

    CAS  PubMed  Google Scholar 

  3. 3.

    Smith, J. S., Lefkowitz, R. J. & Rajagopal, S. Biased signalling: from simple switches to allosteric microprocessors. Nat. Rev. Drug Discov. 17, 243–260 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Kenakin, T. Biased receptor signaling in drug discovery. Pharmacol. Rev. 71, 267–315 (2019).

    CAS  PubMed  Google Scholar 

  5. 5.

    Rajagopal, S. et al. Quantifying ligand bias at seven-transmembrane receptors. Mol. Pharmacol. 80, 367–377 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Rasmussen, S. G. et al. Structure of a nanobody-stabilized active state of the β2 adrenoceptor. Nature 469, 175–180 (2011).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  7. 7.

    Rasmussen, S. G. et al. Crystal structure of the β2 adrenergic receptor–Gs protein complex. Nature 477, 549–555 (2011).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  8. 8.

    Zhou, X. E. et al. Identification of phosphorylation codes for arrestin recruitment by G protein-coupled receptors. Cell 170, 457–469.e13 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Siuda, E. R., Carr, R., III, Rominger, D. H. & Violin, J. D. Biased mu-opioid receptor ligands: a promising new generation of pain therapeutics. Curr. Opin. Pharmacol. 32, 77–84 (2017).

    CAS  PubMed  Google Scholar 

  10. 10.

    Violin, J. D. et al. Selectively engaging β-arrestins at the angiotensin II type 1 receptor reduces blood pressure and increases cardiac performance. J. Pharmacol. Exp. Ther. 335, 572–579 (2010).

    CAS  PubMed  Google Scholar 

  11. 11.

    Wisler, J. W. et al. A unique mechanism of β-blocker action: carvedilol stimulates β-arrestin signaling. Proc. Natl Acad. Sci. USA 104, 16657–16662 (2007).

    CAS  PubMed  ADS  Google Scholar 

  12. 12.

    Wootten, D., Christopoulos, A., Marti-Solano, M., Babu, M. M. & Sexton, P. M. Mechanisms of signalling and biased agonism in G protein-coupled receptors. Nat. Rev. Mol. Cell Biol. 19, 638–653 (2018).

    CAS  PubMed  Google Scholar 

  13. 13.

    Wingler, L. M. et al. Angiotensin analogs with divergent bias stabilize distinct receptor conformations. Cell 176, 468–478.e11 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Baker, J. G., Proudman, R. G. & Tate, C. G. The pharmacological effects of the thermostabilising (m23) mutations and intra and extracellular (β36) deletions essential for crystallisation of the turkey β-adrenoceptor. Naunyn-Schmiedeberg’s Arch. Pharmacol. 384, 71–91 (2011).

    CAS  Google Scholar 

  15. 15.

    Staus, D. P. et al. Sortase ligation enables homogeneous GPCR phosphorylation to reveal diversity in β-arrestin coupling. Proc. Natl Acad. Sci. USA 115, 3834–3839 (2018).

    CAS  PubMed  Google Scholar 

  16. 16.

    Shukla, A. K. et al. Structure of active β-arrestin-1 bound to a G-protein-coupled receptor phosphopeptide. Nature 497, 137–141 (2013).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  17. 17.

    Warne, T., Edwards, P. C., Doré, A. S., Leslie, A. G. W. & Tate, C. G. Molecular basis for high-affinity agonist binding in GPCRs. Science 364, 775–778 (2019).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  18. 18.

    Yin, W. et al. A complex structure of arrestin-2 bound to a G protein-coupled receptor. Cell Res. 29, 971–983 (2019).

    CAS  PubMed  Google Scholar 

  19. 19.

    Huang, W. et al. Structure of the neurotensin receptor 1 in complex with β-arrestin 1. Nature 579, 303–308 (2020).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  20. 20.

    Staus, D. P. et al. Structure of the M2 muscarinic receptor–β-arrestin complex in a lipid nanodisc. Nature 579, 297–302 (2020).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  21. 21.

    García-Nafría, J. & Tate, C. G. Cryo-EM structures of GPCRs coupled to Gs, Gi and Go. Mol. Cell. Endocrinol. 488, 1–13 (2019).

    PubMed  Google Scholar 

  22. 22.

    Pándy-Szekeres, G. et al. GPCRdb in 2018: adding GPCR structure models and ligands. Nucleic Acids Res. 46, D440–D446 (2018).

    PubMed  Google Scholar 

  23. 23.

    Ballesteros, J. A. & Weinstein, H. Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptors. Methods Neurosci., 366–428 (1995).

  24. 24.

    Sommer, M. E., Smith, W. C. & Farrens, D. L. Dynamics of arrestin–rhodopsin interactions: acidic phospholipids enable binding of arrestin to purified rhodopsin in detergent. J. Biol. Chem. 281, 9407–9417 (2006).

    CAS  PubMed  Google Scholar 

  25. 25.

    Bayburt, T. H. et al. Monomeric rhodopsin is sufficient for normal rhodopsin kinase (GRK1) phosphorylation and arrestin-1 binding. J. Biol. Chem. 286, 1420–1428 (2011).

    CAS  PubMed  Google Scholar 

  26. 26.

    Sommer, M. E., Hofmann, K. P. & Heck, M. Distinct loops in arrestin differentially regulate ligand binding within the GPCR opsin. Nat. Commun. 3, 995 (2012); correction 3, 1273 (2012).

    PubMed  PubMed Central  ADS  Google Scholar 

  27. 27.

    Lally, C. C., Bauer, B., Selent, J. & Sommer, M. E. C-edge loops of arrestin function as a membrane anchor. Nat. Commun. 8, 14258 (2017).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  28. 28.

    Ostermaier, M. K., Peterhans, C., Jaussi, R., Deupi, X. & Standfuss, J. Functional map of arrestin-1 at single amino acid resolution. Proc. Natl Acad. Sci. USA 111, 1825–1830 (2014).

    CAS  PubMed  ADS  Google Scholar 

  29. 29.

    Peterhans, C., Lally, C. C., Ostermaier, M. K., Sommer, M. E. & Standfuss, J. Functional map of arrestin binding to phosphorylated opsin, with and without agonist. Sci. Rep. 6, 28686 (2016).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  30. 30.

    Gaidarov, I., Krupnick, J. G., Falck, J. R., Benovic, J. L. & Keen, J. H. Arrestin function in G protein-coupled receptor endocytosis requires phosphoinositide binding. EMBO J. 18, 871–881 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Kumari, P. et al. Functional competence of a partially engaged GPCR–β-arrestin complex. Nat. Commun. 7, 13416 (2016).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  32. 32.

    Yen, H. Y. et al. PtdIns(4,5)P2 stabilizes active states of GPCRs and enhances selectivity of G-protein coupling. Nature 559, 423–427 (2018).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  33. 33.

    Cherezov, V. et al. High-resolution crystal structure of an engineered human β2-adrenergic G protein-coupled receptor. Science 318, 1258–1265 (2007).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  34. 34.

    Warne, T. et al. The structural basis for agonist and partial agonist action on a β1-adrenergic receptor. Nature 469, 241–244 (2011).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  35. 35.

    Ring, A. M. et al. Adrenaline-activated structure of β2-adrenoceptor stabilized by an engineered nanobody. Nature 502, 575–579 (2013).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  36. 36.

    García-Nafría, J., Lee, Y., Bai, X., Carpenter, B. & Tate, C. G. Cryo-EM structure of the adenosine A2A receptor coupled to an engineered heterotrimeric G protein. eLife 7, e35946 (2018).

    PubMed  PubMed Central  Google Scholar 

  37. 37.

    Warne, T., Edwards, P. C., Leslie, A. G. & Tate, C. G. Crystal structures of a stabilized β1-adrenoceptor bound to the biased agonists bucindolol and carvedilol. Structure 20, 841–849 (2012).

    CAS  PubMed  Google Scholar 

  38. 38.

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

    CAS  Article  Google Scholar 

  39. 39.

    Warne, T., Chirnside, J. & Schertler, G. F. Expression and purification of truncated, non-glycosylated turkey beta-adrenergic receptors for crystallization. Biochim. Biophys. Acta 1610, 133–140 (2003).

    CAS  PubMed  Google Scholar 

  40. 40.

    Warne, T., Serrano-Vega, M. J., Tate, C. G. & Schertler, G. F. Development and crystallization of a minimal thermostabilised G protein-coupled receptor. Protein Expr. Purif. 65, 204–213 (2009).

    CAS  PubMed  Google Scholar 

  41. 41.

    Kobashigawa, Y., Kumeta, H., Ogura, K. & Inagaki, F. Attachment of an NMR-invisible solubility enhancement tag using a sortase-mediated protein ligation method. J. Biomol. NMR 43, 145–150 (2009).

    CAS  PubMed  Google Scholar 

  42. 42.

    Pandey, S., Roy, D. & Shukla, A. K. Measuring surface expression and endocytosis of GPCRs using whole-cell ELISA. Methods Cell Biol. 149, 131–140 (2019).

    PubMed  Google Scholar 

  43. 43.

    Kumari, P. et al. Core engagement with β-arrestin is dispensable for agonist-induced vasopressin receptor endocytosis and ERK activation. Mol. Biol. Cell 28, 1003–1010 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Dogra, S., Sona, C., Kumar, A. & Yadav, P. N. Tango assay for ligand-induced GPCR–β-arrestin2 interaction: Application in drug discovery. Methods Cell Biol. 132, 233–254 (2016).

    CAS  PubMed  Google Scholar 

  45. 45.

    Ghosh, E. et al. Conformational sensors and domain swapping reveal structural and functional differences between β-arrestin isoforms. Cell Reports 28, 3287–3299.e6 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Urbani, A. & Warne, T. A colorimetric determination for glycosidic and bile salt-based detergents: applications in membrane protein research. Anal. Biochem. 336, 117–124 (2005).

    CAS  PubMed  Google Scholar 

  47. 47.

    Bowler, M. W. et al. MASSIF-1: a beamline dedicated to the fully automatic characterization and data collection from crystals of biological macromolecules. J. Synchrotron Radiat. 22, 1540–1547 (2015).

    PubMed  PubMed Central  Google Scholar 

  48. 48.

    Svensson, O., Malbet-Monaco, S., Popov, A., Nurizzo, D. & Bowler, M. W. Fully automatic characterization and data collection from crystals of biological macromolecules. Acta Crystallogr. D 71, 1757–1767 (2015).

    CAS  PubMed  Google Scholar 

  49. 49.

    Svensson, O., Gilski, M., Nurizzo, D. & Bowler, M. W. Multi-position data collection and dynamic beam sizing: recent improvements to the automatic data-collection algorithms on MASSIF-1. Acta Crystallogr. D 74, 433–440 (2018).

    CAS  Google Scholar 

  50. 50.

    Leslie, A. G. The integration of macromolecular diffraction data. Acta Crystallogr. D 62, 48–57 (2006).

    PubMed  Google Scholar 

  51. 51.

    Evans, P. Scaling and assessment of data quality. Acta Crystallogr. D 62, 72–82 (2006).

    PubMed  Google Scholar 

  52. 52.

    McCoy, A. J. et al. Phaser crystallographic software. J. Appl. Crystallogr. 40, 658–674 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Murshudov, G. N. et al. REFMAC5 for the refinement of macromolecular crystal structures. Acta Crystallogr. D 67, 355–367 (2011).

    CAS  PubMed  Google Scholar 

  54. 54.

    Emsley, P. & Cowtan, K. Coot: model-building tools for molecular graphics. Acta Crystallogr. D 60, 2126–2132 (2004).

    PubMed  Google Scholar 

  55. 55.

    Gurevich, V. V. & Gurevich, E. V. The molecular acrobatics of arrestin activation. Trends Pharmacol. Sci. 25, 105–111 (2004).

    CAS  PubMed  Google Scholar 

  56. 56.

    Banerjee, S., Huber, T. & Sakmar, T. P. Rapid incorporation of functional rhodopsin into nanoscale apolipoprotein bound bilayer (NABB) particles. J. Mol. Biol. 377, 1067–1081 (2008).

    CAS  PubMed  Google Scholar 

  57. 57.

    Ritchie, T. K. et al. Chapter 11 – reconstitution of membrane proteins in phospholipid bilayer nanodiscs. Methods Enzymol. 464, 211–231 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Rigaud, J. L., Levy, D., Mosser, G. & Lambert, O. Detergent removal by non-polar polystyrene beads. Eur. Biophys. J. 27, 305–319 (1998).

    CAS  Google Scholar 

  59. 59.

    Naydenova, K. & Russo, C. J. Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy. Nat. Commun. 8, 629 (2017).

    PubMed  PubMed Central  ADS  Google Scholar 

  60. 60.

    Mastronarde, D. N. Automated electron microscope tomography using robust prediction of specimen movements. J. Struct. Biol. 152, 36–51 (2005).

    Google Scholar 

  61. 61.

    Zivanov, J. et al. New tools for automated high-resolution cryo-EM structure determination in RELION-3. eLife 7, e42166 (2018).

    PubMed  PubMed Central  Google Scholar 

  62. 62.

    Tegunov, D. & Cramer, P. Real-time cryo-electron microscopy data preprocessing with Warp. Nat. Methods 16, 1146–1152 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63.

    Ramlaul, K., Palmer, C. M. & Aylett, C. H. S. Mitigating local over-fitting during single particle reconstruction with Sidesplitter. Preprint at (2020).

  64. 64.

    Ramlaul, K., Palmer, C. M. & Aylett, C. H. S. A local agreement filtering algorithm for transmission EM reconstructions. J. Struct. Biol. 205, 30–40 (2019).

    PubMed  PubMed Central  Google Scholar 

  65. 65.

    Wood, C. et al. Collaborative computational project for electron cryo-microscopy. Acta Crystallogr. D 71, 123–126 (2015).

    CAS  PubMed  Google Scholar 

  66. 66.

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

    CAS  PubMed  Google Scholar 

  67. 67.

    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 65, 1074–1080 (2009).

    CAS  PubMed  Google Scholar 

  68. 68.

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

    CAS  PubMed  Google Scholar 

  69. 69.

    Barad, B. A. et al. EMRinger: side chain-directed model and map validation for 3D cryo-electron microscopy. Nat. Methods 12, 943–946 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. 70.

    Amunts, A. et al. Structure of the yeast mitochondrial large ribosomal subunit. Science 343, 1485–1489 (2014).

    CAS  PubMed  PubMed Central  ADS  Google Scholar 

  71. 71.

    Carpenter, B. & Tate, C. G. Expression, purification and crystallisation of the adenosine A2A receptor bound to an engineered mini G protein. Bio Protoc. 7, e2234 (2017).

    PubMed  PubMed Central  Google Scholar 

  72. 72.

    Tan, Y. Z. et al. Addressing preferred specimen orientation in single-particle cryo-EM through tilting. Nat. Methods 14, 793–796 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references


Work in the C.G.T. laboratory was funded by a grant from the European Research Council (EMPSI 339995), Heptares Therapeutics Ltd and core funding from the Medical Research Council (MRC U105197215). The research program in the A.K.S. laboratory is supported by an Intermediate Fellowship of the Wellcome Trust/DBT India Alliance Fellowship (grant number IA/I/14/1/501285), the Science and Engineering Research Board (SERB) (EMR/2017/003804), Innovative Young Biotechnologist Award from the Department of Biotechnology (DBT) (BT/08/IYBA/2014-3) and the Indian Institute of Technology, Kanpur. H.D.-A. is supported by the National Post-Doctoral Fellowship of SERB (PDF/2016/002930) and DBT-BioCaRE grant (BT/PR31791/BIC/101/1228/2019). We thank Diamond Light Source (UK) for access and support of the cryo-EM facilities at eBIC (proposal EM17434) funded by the Wellcome Trust, MRC and BBSRC. We thank the beamline staff at the European Synchrotron Radiation Facility MASSIF-1 for help with X-ray diffraction data collection; T. Nakane, S. Monteleone and P. Kolb for discussions; D. Gloriam for access to unreleased data from GPCRdb; and G. Cannone from the LMB EM facility and J. Grimmett and T. Darling from LMB Scientific Computing for technical support during this work.

Author information




Y.L. performed receptor, arrestin and zap1 expression, purification, nanodisc reconstitution and complex formation, cryo-EM grid preparation, data collection, data processing and model building. T.W. performed receptor and nanobody expression, purification and complex formation, crystallization, cryo-cooling of the crystals, X-ray data collection, data processing and X-ray structure refinement. Y.L. and T.W. performed the pharmacological analyses. S.P. and H.D.-A. performed Fab expression, purification and validation; H.D.-A. carried out GloSensor and Tango assays for β1AR constructs with help from S.P. and M.C.; and M.C. performed the confocal microscopy experiments. R.N. developed the sortase ligation of phosphorylated peptides onto β1AR. P.C.E. purified mini-GS. J.G.-N. advised on cryo-EM data collection, data processing and model building. A.G.W.L. advised on X-ray data processing, structure solution and analysis. Y.L. and C.G.T. carried out structure analysis and manuscript preparation. A.K.S. supervised the expression and purification of Fab, and functional characterization of the β1AR constructs. C.G.T. analysed data and managed the overall project. The manuscript was written by C.G.T. and Y.L., and included contributions from all authors.

Corresponding author

Correspondence to Christopher G. Tate.

Ethics declarations

Competing interests

C.G.T. is a shareholder, consultant and member of the scientific advisory board of Sosei Heptares, who also partly funded this work.

Additional information

Peer review information Nature thanks Oliver Clarke, Martin Lohse 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 β1AR constructs, purification and activity.

a, Schematic of the constructs used for X-ray crystallography (trx-β1AR), cryo-EM (β83), radioligand binding (MBP-β83) and cell-based assays (β44–V2R, β83–V2R), indicating the sites of truncations, point mutations and tags. b, Purification scheme for the preparation of the β1AR6P–βarr1–Fab30 complex for structure determination by cryo-EM. c, d, Representative competition binding curves using either formoterol (c) or isoprenaline (d) show the high-affinity state of MBP–β1AR6P stabilized by either mini-Gs or βarr1. Experiments (Methods) to determine the high-affinity state were performed in a molar excess of mini-Gs (green curves; n = 2) or βarr1 (red curves; n = 3 with formoterol, n = 4 with isoprenaline) and compared to the low-affinity state (blue curves; n = 4). Experiments were all performed in duplicate, with the number of independent experiments indicated (n). Data are mean ± s.e.m. The apparent Ki values were determined using the Cheng–Prusoff equation, using apparent Kd values for [3H]DHA of 6 nM (MBP–β1AR6P and MBP–β1AR6P + βarr1) and 1.5 nM (MBP–β1AR6P + mini-Gs). Ki values for formoterol are 1.5 ± 0.4 μM (MBP–β1AR6P), 42 ± 18 nM (MBP–β1AR6P + βarr1) and 0.7 ± 0.1 nM (MBP–β1AR6P + mini-Gs). Ki values for isoprenaline are 340 ± 70 nM (MBP–β1AR6P), 4.4 ± 0.8 nM (MBP–β1AR6P + βarr1) and 0.13 ± 0.02 nM (MBP–β1AR6P + mini-Gs).

Extended Data Fig. 2 Functional characterization of β1AR construct β83 in cells.

a, HEK293 cells expressing the two β1AR constructs β44–V2R (blue circles) and β83–V2R (red squares) together with the cAMP sensor 22F (GloSensor assay) were stimulated with the indicated concentrations of isoprenaline (dashed line) or formoterol (solid line). Subsequently, the luminescence readings were recorded and normalized with respect to the signal at the maximal dose of isoprenaline for β44–V2R (treated as 100%). The results are from four independent experiments of duplicate measurements, data are mean ± s.e.m. The maximum effect (Emax) and half-maximal effective concentration (EC50) were calculated by nonlinear regression (GraphPad Prism), data are mean ± s.e.m. b, HTLA cells expressing the β44–V2R (blue circles) and β83–V2R (red squares) Tango assay constructs (Methods) were stimulated with indicated concentrations of isoprenaline and formoterol, and the luminescence readings were recorded 8 h post-stimulation. Afterwards, the data were normalized with respect to the signal at the maximal dose of isoprenaline for β44–V2R (treated as 100%). Results are from five independent experiments of a duplicate measurement, data are mean ± s.e.m. Emax and EC50 values were calculated by nonlinear regression (GraphPad Prism), data are mean ± s.e.m. c, Surface expression of β44–V2R and β83–V2R constructs in cells used for assays in a, b were measured by whole-cell ELISA using anti-Flag M2 antibody. Data are normalized with respect to β44–V2R (blue bars; treated as 100%). Values for p83–V2R are as follows: ELISA for G-protein assay, 99% ± 13% (n = 5); ELISA for arrestin assay, 94% ± 17% (n = 4). Experiments were performed in duplicate with the number of independent experiments indicated (n), data are mean ± s.e.m. d, HEK293 cells expressing β44–V2R and β83–V2R together with βarr1–mYFP were stimulated with 100 μM formoterol for the indicated times and the localization of βarr1–mYFP was monitored using live-cell confocal microscopy. Representative images from three independent experiments are shown. Scale bars, 10 μm.

Extended Data Fig. 3 Cryo-EM single-particle reconstruction of the β1AR–βarr1–Fab30 complex.

a, Representative micrograph (LMB-Krios2, magnification 105,000× , defocus –1.9 μm) of the β1AR6P–βarr1–Fab30 complex collected using a Titan Krios with the GIF Quantum K2 detector. b, Representative 2D class averages of the β1AR6P–βarr1–Fab30 complex determined using approximately 1 million particles after 3D classification. Copies of the final reconstruction are juxtaposed to indicate relative orientations. c, FSC curve of the final reconstruction (black) showing an overall resolution of 3.3 Å using the gold standard FSC of 0.143. The directional 3D-FSC curves calculated from the two half maps are shown in colour72. d, Final reconstruction coloured by polypeptides (contour level 0.023). e. Local resolution estimation of the β1AR6P–βarr1–Fab30 map as calculated by Relion.

Extended Data Fig. 4 Flow chart of cryo-EM data processing.

Micrographs were collected during three sessions on a Titan Krios (between 48-h and 96-h long) using a 30° stage tilt to improve particle orientation distribution. Each dataset was corrected separately for drift, beam-induced motion and radiation damage. After focus gradient and CTF estimation, particles were picked using a Gaussian blob. At this stage, each of the LMB Krios2 datasets was split into two halves by micrographs, generating a total of five groups of particles. Each group was processed and curated independently. The number of particles from group G1 is indicated on the flowchart as a guide. At the bottom of the figure, the final number of particles is shown. Particles were submitted to two rounds of 3D classification using an ab initio model as a reference. In each round, classification was performed in six classes. The models with the best features were merged and refined together before correcting for per-particle beam-induced motion. Subtracted particles were generated by removing most of the non-receptor nanodisc signal and refined. 3D classification without alignment was performed in six classes using a mask encompassing the entire complex. The models showing the best features were refined either individually or in combination. The quality of the models was judged on the basis of both resolution and map features and weighed against the size of the contributing particle set (the resolution of the models refers to the resolution after refinement and calculation of gold-standard FSC of 0.143). The best particles from each group were merged and re-extracted. After merging, the combined particle set was processed together except at the stage of per-particle beam-induced motion correction, at which particles were split into their session-stacks for Bayesian polishing. Particles were assigned to one of 19 optical groups (Methods) and corrected iteratively for beam-tilt, per-micrograph astigmatism, anisotropic magnification and per-particle CTF estimation. A final model with 403,991 particles was refined and achieved a global resolution of 3.3 Å.

Extended Data Fig. 5 Cryo-EM map quality of the β1AR6P–βarr1–Fab30 complex and model validation.

Unless otherwise stated, density maps were visualized using Chimera38 (contour level 0.017) and encompass a radius of 2 Å around the region of interest. a, Transmembrane helices of β1AR6P with density shown as a mesh. b, ICL2 of β1AR6P. For clarity, the neighbouring βarr1 side chains are depicted without density. c, ECL3 of β1AR6P and the adjacent helical turns of H6 and H7. d, The phosphorylated V2R6P C terminus. Inset, interaction between the V2R6P phospho-threonine dyad and the βarr1 lariat loop. Density in the inset is depicted with contour level 0.01 (carve radius 2 Å). e, The finger loop of βarr1. f, Formoterol and the neighbouring side chains in the orthosteric binding site. g, FSC of the refined model versus the map (green curve), and FSCwork and FSCfree validation curves (blue and red curves, respectively). h, Amino acid sequence of the β1AR6P construct used for the cryo-EM structure determination. The residues are numbered according to the wild-type sequence of β1AR. Residues are coloured according to how they have been modelled (key). Regions highlighted in grey represent the transmembrane α-helices, amphipathic helix 8 is highlighted in yellow, and phosphorylated residues are highlighted in green. The dashes represent amino acid residues that were deleted.

Extended Data Fig. 6 Comparison of arrestin coupled to different GPCRs.

a, Superposition of arrestin molecules in the complexes of β1AR6P–βarr1 (green) and rhodopsin–arrestin (pale brown). The different angle between the respective receptors and coupled arrestins is shown by the 20° difference in tilt of H3 (blue, H3 in rhodopsin; red, H3 in β1AR). b, Superposition of β1AR6P and β2AR (pink and purple cartoons, respectively) coupled to either βarr1 (magenta surface) or Gs (blue and purple surfaces), respectively. c, Superposition of β1AR6P (rainbow cartoon) and NTSR1 (grey cartoon) coupled to βarr1 (magenta) and βarr1 (grey), respectively. d, Alignment in c viewed from the membrane surface and the respective molecules of βarr shown in surface representation. e, Superposition of the active state of βarr1 (pale brown; PDB ID: 4JQI) not bound to receptor and βarr1 (green) coupled to β1AR6P. The phosphopeptides are shown as sticks: yellow carbon atoms, V2Rpp in 4JQI; magenta carbon atoms, V2R6P in the β1AR6P–βarr1 complex.

Extended Data Fig. 7 β1AR6P-βarr1 and formoterol–β1AR6P contacts, and comparison with other complexes.

a, Interactions between amino acid residues in β1AR6P and βarr1. The size of the circle depicting the residue is proportional to the number of van der Waals interactions (grey lines) and hydrogen bonds (red lines) made, with residues in circles outlined in black making potential hydrogen bonds. Secondary structure elements are shown with the total number of interactions they make. The thickness of lines making contacts is proportional to the number of contacts made. b, Residues are depicted in β1AR6P that make contact (≤3.9 Å) with βarr1 (red) and residues in β2AR (PDB ID: 3SN6) that make contact to Gs (blue); purple residues make contacts in both structures. The sequence of turkey β1AR is depicted. c, Residues in human rhodopsin that make contact with either visual arrestin or transducin (Gt). Plots were made using GPCRdb. d, The number of atomic contacts between the ligand formoterol and secondary structure elements in β1AR is depicted; grey bars, β1AR–Nb80 complex; blue bars, β1AR6P–βarr1 complex. Light regions correspond to the number of van der Waals interactions and dark regions correspond to the number of hydrogen bonds. Data for chain A and chain B in the crystal unit cell of the β1AR–Nb80 complex are shown separately (A and B).

Extended Data Fig. 8 Comparison of the visual arrestin and βarr1 interfaces with GPCRs and lipids.

a, A snake plot (GPCRdb) of human βarr1 depicts the secondary structure elements in the protein, with amino acid residues that make contact with β1AR coloured blue. Equivalent regions in mouse visual arrestin (S-arr) that make contact to rhodopsin are shown in red. Alignments of human arrestins show the variation of amino acid sequences within these specific regions, with residues that make contact to the respective receptors highlighted. Highlighted are residues equivalent to those in visual arrestin that have been shown by mutagenesis to interact with phosphoinositides by mutagenesis (&)31 or to interact with the lipid bilayer by bimane fluorescence quenching ($)28. b, c, β1AR6P is depicted in surface representation and βarr1 as a cartoon (green) with atoms predicted to be within the head group region of the lipid bilayer shown as spheres: oxygen, red; nitrogen, blue; carbon, green or cyan. Residues coloured cyan are predicted to be entirely within the lipid head group region, while the carbons coloured green are the portions of these side chains that are potentially interacting with lipid head groups. b, c, View of the lipid-interacting surface viewed parallel to the membrane plane (b) and through the receptor (c).

Extended Data Fig. 9 Conformational changes in β1AR and potential drug-interaction sites to discriminate between complexes of β-adrenoceptors coupled to either βarr1 or Gs.

a, The inactive state (R) of β1AR binds agonist (blue hexagon) resulting in an inward movement of H5 in the orthosteric binding pocket (yellow arrow), to form an intermediate state (R′). Coupling of G protein results in outward movement of the cytoplasmic ends of H5 and H6 (red arrow) and contraction of the orthosteric binding site (yellow arrows). Displacement of G protein by arrestin results in an inward movement of the cytoplasmic ends of H5 and H6 (red arrow) and an outward movement of H5 in the orthosteric biding pocket (yellow arrow). Receptors in the R* state have higher affinity for agonists than those in the R state. Representative structures of each of the states depicted have been determined, but in reality there is likely to be a continuum of states between them. Several factors probably affect the arrestin bias of ligands, not just the structure of the receptor–arrestin complex. b, Surface view of β1AR6P showing the finger loop of βarr1 (sticks). c, Surface view of β2AR showing the α5 helix of Gs (sticks). In b, c, potential druggable sites are depicted (magenta oval) in b and c that could be used to develop small molecules that discriminate between the same receptor coupled to either βarr1 or Gs. d, e, Two examples of small-molecule negative allosteric modulators that bind to the surface of GPCRs, which give a proof of concept to the surface-interacting molecules.

Extended Data Table 1 Cryo-EM data collection and refinement statistics
Extended Data Table 2 X-ray data collection and refinement statistics

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lee, Y., Warne, T., Nehmé, R. et al. Molecular basis of β-arrestin coupling to formoterol-bound β1-adrenoceptor. Nature 583, 862–866 (2020).

Download citation

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links