Skip to main content
Log in

The dynamics of agonist-β2-adrenergic receptor activation induced by binding of GDP-bound Gs protein

  • Article
  • Published:

From Nature Chemistry

View current issue Submit your manuscript

Abstract

There is considerable uncertainty about the mechanism by which the β2-adrenergic receptor (β2AR) is activated. Here we use molecular metadynamics computations to predict the mechanism by which an agonist induces the activation of the β2AR and its cognate Gs protein. We found that binding agonist alone to the inactive β2AR does not break the ionic lock and hence does not drive the β2AR towards the activated conformation. However, we found that attaching the inactive Gs protein to the agonist-bound inactive β2AR (containing the ionic lock) leads to partial insertion of Gαs-α5 into the core of β2AR, which breaks the ionic lock, leading to activation of the Gs protein coupled to β2AR. Upon activation, the Gαs protein undergoes a remarkable opening of the GDP binding pocket, making the GDP available for exchange or release. Concomitantly, Gαs-α5 undergoes a remarkable expansion in the β2AR cytoplasmic region after the ionic lock is broken, inducing TM6 to displace outward by ~5 Å from TM3.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1: Ligand-first activation mechanism for β2AR and its cognate Gs protein.
Fig. 2: Inactive state of β2AR.
Fig. 3: Agonists do not stabilize the active conformation of β2AR.
Fig. 4: The inactive Gs-protein-bound GDP attaches to the agonist-bound β2AR with its closed cytoplasmic region.
Fig. 5: Activation of Gs protein-bound GDP triggers activation of BI67107-bound β2AR.
Fig. 6: Comparison of our predicted active state of BI167107–β2AR–Gs (GDP) with crystal structures.

Similar content being viewed by others

Data availability

All data generated or analysed during this study are included in this published Article (and its Supplementary Information files). We deposited (https://figshare.com/articles/dataset/free_energy_files/22217674) the metadynamics protocol and associate free-energy results along with the initial and final protein complex structures. Source data are provided with this paper.

Code availability

GROMACS (https://www.gromacs.org/) and Plumed (https://www.plumed.org/) are all available as open source.

References

  1. Lefkowitz, R. J. Seven transmembrane receptors: something old, something new. Acta Physiol. 190, 9–19 (2007).

    CAS  Google Scholar 

  2. Hauser, A. S., Attwood, M. M., Rask-Andersen, M., Schiöth, H. B. & Gloriam, D. E. Trends in GPCR drug discovery: new agents, targets and indications. Nat. Rev. Drug Discov. 16, 829–842 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Overington, J. P., Al-Lazikani, B. & Hopkins, A. L. How many drug targets are there?. Nat. Rev. Drug Discov. 5, 993–996 (2006).

    CAS  PubMed  Google Scholar 

  4. Fredriksson, R., Lagerström, M. C., Lundin, L.-G. & Schiöth, H. B. The G-protein-coupled receptors in the human genome form five main families. Phylogenetic analysis, paralogon groups and fingerprints. Mol. Pharmacol. 63, 1256–1272 (2003).

    CAS  PubMed  Google Scholar 

  5. Lefkowitz, R. J. The superfamily of heptahelical receptors. Nat. Cell Biol. 2, E133–E136 (2000).

    CAS  PubMed  Google Scholar 

  6. Ross, E. M., Maguire, M. E., Sturgill, T. W., Biltonen, R. L. & Gilman, A. G. Relationship between the β-adrenergic receptor and adenylate cyclase. J. Biol. Chem. 252, 5761–5775 (1977).

    CAS  PubMed  Google Scholar 

  7. De Lean, A., Stadel, J. M. & Lefkowitz, R. J. A ternary complex model explains the agonist-specific binding properties of the adenylate cyclase-coupled β-adrenergic receptor. J. Biol. Chem. 255, 7108–7117 (1980).

    PubMed  Google Scholar 

  8. MacGregor, D. A., Prielipp, R. C., Butterworth, J. F. IV, James, R. L. & Royster, R. L. Relative efficacy and potency of β-adrenoceptor agonists for generating cAMP in human lymphocytes. Chest 109, 194–200 (1996).

    CAS  PubMed  Google Scholar 

  9. Clark, A. J. The reaction between acetyl choline and muscle cells. J. Physiol. 61, 530–546 (1926).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Karlin, A. On the application of ‘a plausible model’ of allosteric proteins to the receptor for acetylcholine. J. Theor. Biol. 16, 306–320 (1967).

    CAS  PubMed  Google Scholar 

  11. Nygaard, R. et al. The dynamic process of β2-adrenergic receptor activation. Cell 152, 532–542 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Manglik, A. et al. Structural insights into the dynamic process of β2-adrenergic receptor signaling. Cell 161, 1101–1111 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Rosenbaum, D. M. et al. Structure and function of an irreversible agonist-β2 adrenoceptor complex. Nature 469, 236–240 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Gregorio, G. G. et al. Single-molecule analysis of ligand efficacy in β2 AR–G-protein activation. Nature 547, 68–73 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Lerch, M. T. et al. Viewing rare conformations of the β2 adrenergic receptor with pressure-resolved DEER spectroscopy. Proc. Natl Acad. Sci. USA 117, 31824–31831 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Vilardaga, J.-P., Bünemann, M., Krasel, C., Castro, M. & Lohse, M. J. Measurement of the millisecond activation switch of G protein-coupled receptors in living cells. Nat. Biotechnol. 21, 807–812 (2003).

    CAS  PubMed  Google Scholar 

  18. Barducci, A., Bussi, G. & Parrinello, M. Well-tempered metadynamics: a smoothly converging and tunable free-energy method. Phys. Rev. Lett. 100, 020603 (2008).

    PubMed  Google Scholar 

  19. 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  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Ballesteros, J. A. & Weinstein, H. in Methods in Neurosciences Vol. 25 (ed Sealfon, S. C.), 366–428 (Elsevier, 1995).

  22. Pándy-Szekeres, G. et al. GPCRdb in 2018: adding GPCR structure models and ligands. Nucleic Acids Res. 46, D440–D446 (2017).

    PubMed Central  Google Scholar 

  23. Kobilka, B. K. G protein coupled receptor structure and activation. Biochim. Biophys. Acta 1768, 794–807 (2007).

    CAS  PubMed  Google Scholar 

  24. Ballesteros, J. A. et al. Activation of the β2-adrenergic receptor involves disruption of an ionic lock between the cytoplasmic ends of transmembrane segments 3 and 6. J. Biol. Chem. 276, 29171–29177 (2001).

    CAS  PubMed  Google Scholar 

  25. Yao, X. et al. Coupling ligand structure to specific conformational switches in the β2-adrenoceptor. Nat. Chem. Biol. 2, 417–422 (2006).

    CAS  PubMed  Google Scholar 

  26. Liu, X. et al. Structural insights into the process of GPCR-G protein complex formation. Cell 177, 1243–1251 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Sprang, S. R. G protein mechanisms: insights from structural analysis. Annu. Rev. Biochem. 66, 639–678 (1997).

    CAS  PubMed  Google Scholar 

  28. Oldham, W. M. & Hamm, H. E. Heterotrimeric G protein activation by G-protein-coupled receptors. Nat. Rev. Mol. Cell Biol. 9, 60–71 (2008).

    CAS  PubMed  Google Scholar 

  29. Liu, R. et al. Palmitoylation regulates intracellular trafficking of β2 adrenergic receptor/arrestin/phosphodiesterase 4D complexes in cardiomyocytes. PLoS ONE 7, e42658 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. Palczewski, K. et al. Crystal structure of rhodopsin: AG protein-coupled receptor. Science 289, 739–745 (2000).

    CAS  PubMed  Google Scholar 

  31. Branduardi, D., Bussi, G. & Parrinello, M. Metadynamics with adaptive Gaussians. J. Chem. Theory Comput. 8, 2247–2254 (2012).

    CAS  PubMed  Google Scholar 

  32. Dror, R. O. et al. Identification of two distinct inactive conformations of the β2-adrenergic receptor reconciles structural and biochemical observations. Proc. Natl Acad. Sci. USA 106, 4689–4694 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Eswar, N., Eramian, D., Webb, B., Shen, M.-Y. & Sali, A. in Structural Proteomics 145–159 (Springer, 2008).

  34. Hilger, D. et al. Structural insights into differences in G protein activation by family A and family B GPCRs. Science 369, eaba3373 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Oldham, W. M., Van Eps, N., Preininger, A. M., Hubbell, W. L. & Hamm, H. E. Mechanism of the receptor-catalyzed activation of heterotrimeric G proteins. Nat. Struct. Mol. Biol. 13, 772–777 (2006).

    CAS  PubMed  Google Scholar 

  36. Onrust, R. et al. Receptor and βγ binding sites in the α subunit of the retinal G protein transducin. Science 275, 381–384 (1997).

    CAS  PubMed  Google Scholar 

  37. DeMars, G., Fanelli, F. & Puett, D. The extreme C-terminal region of Gαs differentially couples to the luteinizing hormone and β2-adrenergic receptors. Mol. Endocrinol. 25, 1416–1430 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Markby, D. W., Onrust, R. & Bourne, H. R. Separate GTP binding and GTPase activating domains of a Gα subunit. Science 262, 1895–1901 (1993).

    CAS  PubMed  Google Scholar 

  39. Carpenter, B., Nehmé, R., Warne, T., Leslie, A. G. & Tate, C. G. Structure of the adenosine A2A receptor bound to an engineered G protein. Nature 536, 104–107 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Mafi, A., Kim, S.-K., Chou, K. C., Güthrie, B. & Goddard, W. A. III Predicted structure of fully activated Tas1R3/1R3′ homodimer bound to G protein and natural sugars: structural insights into G protein activation by a Class C sweet taste homodimer with natural sugars. J. Am. Chem. Soc. 143, 16824–16838 (2021).

    CAS  PubMed  Google Scholar 

  42. Kwon, Y. et al. Dimerization of β2-adrenergic receptor is responsible for the constitutive activity subjected to inverse agonism. Cell Chem. Biol. 29, 1532–1540 (2022).

    CAS  PubMed  Google Scholar 

  43. Mafi, A., Kim, S.-K. & Goddard, W. A. The atomistic level structure for the activated human κ-opioid receptor bound to the full Gi protein and the MP1104 agonist. Proc. Natl Acad. Sci. USA 117, 5836–5843 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Mafi, A., Kim, S.-K. & Goddard, W. A. Mechanism of β-arrestin recruitment by the μ-opioid G protein-coupled receptor. Proc. Natl Acad. Sci. USA 117, 16346–16355 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Zhang, Y. et al. Cryo-EM structure of the activated GLP-1 receptor in complex with a G protein. Nature 546, 248–253 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Liang, Y.-L. et al. Phase-plate cryo-EM structure of a biased agonist-bound human GLP-1 receptor–Gs complex. Nature 555, 121–125 (2018).

    CAS  PubMed  Google Scholar 

  47. 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 

  48. Hu, Q. & Shokat, K. M. Disease-causing mutations in the G protein Gαs subvert the roles of GDP and GTP. Cell 173, 1254–1264 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Guex, N. & Peitsch, M. C. SWISS-MODEL and the Swiss-Pdb Viewer: an environment for comparative protein modeling. Electrophoresis 18, 2714–2723 (1997).

    CAS  PubMed  Google Scholar 

  50. Griffith, A. R. DarwinDock and GAG-Dock: Methods and Applications for Small Molecule Docking (California Institute of Technology, 2017).

  51. Mayo, S. L., Olafson, B. D. & Goddard, W. A. DREIDING: a generic force field for molecular simulations. J. Phys. Chem. 94, 8897–8909 (1990).

    CAS  Google Scholar 

  52. Tak Kam, V. W. & Goddard, W. A. III Flat-bottom strategy for improved accuracy in protein side-chain placements. J. Chem. Theory Comput. 4, 2160–2169 (2008).

    CAS  PubMed  Google Scholar 

  53. 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  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  55. Wacker, D. et al. Conserved binding mode of human β2 adrenergic receptor inverse agonists and antagonist revealed by X-ray crystallography. J. Am. Chem. Soc. 132, 11443–11445 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Needleman, S. B. & Wunsch, C. D. A general method applicable to the search for similarities in the amino acid sequence of two proteins. J. Mol. Biol. 48, 443–453 (1970).

    CAS  PubMed  Google Scholar 

  57. 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 

  58. Raniolo, S. & Limongelli, V. Ligand binding free-energy calculations with funnel metadynamics. Nat. Protoc. 15, 2837–2866 (2020).

    CAS  PubMed  Google Scholar 

  59. Maier, J. A. et al. ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB. J. Chem. Theory Comput. 11, 3696–3713 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Wang, J., Wolf, R. M., Caldwell, J. W., Kollman, P. A. & Case, D. A. Development and testing of a general amber force field. J. Comput. Chem. 25, 1157–1174 (2004).

    CAS  PubMed  Google Scholar 

  61. da Silva, A. W. S. & Vranken, W. F. ACPYPE-AnteChamber PYthon Parser interfacE. BMC Res. Notes 5, 367 (2012).

    Google Scholar 

  62. Wang, J., Wang, W., Kollman, P. A. & Case, D. A. Automatic atom type and bond type perception in molecular mechanical calculations. J. Mol. Graph. Model. 25, 247–260 (2006).

    PubMed  Google Scholar 

  63. Jakalian, A., Jack, D. B. & Bayly, C. I. Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J. Comput. Chem. 23, 1623–1641 (2002).

    CAS  PubMed  Google Scholar 

  64. Dickson, C. J. et al. Lipid14: the amber lipid force field. J. Chem. Theory Comput. 10, 865–879 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Lindorff-Larsen, K. et al. Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins 78, 1950–1958 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Meagher, K. L., Redman, L. T. & Carlson, H. A. Development of polyphosphate parameters for use with the AMBER force field. J. Comput. Chem. 24, 1016–1025 (2003).

    CAS  PubMed  Google Scholar 

  67. Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983).

    CAS  Google Scholar 

  68. Khoury, G. A., Thompson, J. P., Smadbeck, J., Kieslich, C. A. & Floudas, C. A. Forcefield_PTM: ab initio charge and AMBER forcefield parameters for frequently occurring post-translational modifications. J. Chem. Theory Comput. 9, 5653–5674 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. Bussi, G., Donadio, D. & Parrinello, M. Canonical sampling through velocity rescaling. J. Chem. Phys. 126, 014101 (2007).

    PubMed  Google Scholar 

  70. Parrinello, M. & Rahman, A. Polymorphic transitions in single crystals: a new molecular dynamics method. J. Appl. Phys. 52, 7182–7190 (1981).

    CAS  Google Scholar 

  71. Essmann, U. et al. A smooth particle mesh Ewald method. J. Chem. Phys. 103, 8577–8593 (1995).

    CAS  Google Scholar 

  72. Miyamoto, S. & Kollman, P. A. Settle: an analytical version of the SHAKE and RATTLE algorithm for rigid water models. J. Comput. Chem. 13, 952–962 (1992).

    CAS  Google Scholar 

  73. Hess, B. P-LINCS: a parallel linear constraint solver for molecular simulation. J. Chem. Theory Comput. 4, 116–122 (2008).

    CAS  PubMed  Google Scholar 

  74. 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 

  75. Pronk, S. et al. GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit. Bioinformatics 29, 845–854 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Tribello, G. A., Bonomi, M., Branduardi, D., Camilloni, C. & Bussi, G. PLUMED 2: new feathers for an old bird. Comput. Phys. Commun. 185, 604–613 (2014).

    CAS  Google Scholar 

Download references

Acknowledgements

A.M., S.-K.K. and W.A.G. acknowledge support from the NIH (R01HL155532 and R35HL150807).

Author information

Authors and Affiliations

Authors

Contributions

W.A.G. and A.M. designed the project. A.M. carried out all calculations. A.M. and S.-K.K. prepared all figures and tables and the Supplementary Information. A.M. wrote the manuscript with W.A.G. and S.-K.K.

Corresponding author

Correspondence to William A. Goddard III.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Chemistry thanks Irina Tikhonova and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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 Agonists alone do not activate β2AR.

(a) The optimized inverse agonist (ICI118551)-bound β2AR, featuring the ionic lock in the cytoplasmic region. (b) ICI118551-bound β2AR: MetaMD free energy of the distance between TM3 [the center of mass of Cα for residues 129-137] and TM6 [the center of mass of Cα for residues 266-277]. (c) inverse agonist: ICI118551: MetaMD free energy of the strength for the ionic lock between R1313.50(CZ)- E2686.30(CD). The weighted averages and the standard deviations were calculated for the reported ΔGif within the converged period. The metaMD free energies were reweighted31 for estimation of the error. We used block averaging (n = 951 blocks) to report the standard deviation. (d) The free energy of breaking the ionic lock in the presence of (inverse agonist and agonists) and in the absence of ligands. Comparison of our optimized ICI118551 (inverse-agonist)-bound β2AR with (e) epinephrine-bound β2AR and (f) BI167107-bound β2AR. All RMSDs were calculated for the backbone atoms on the TM domain of β2AR.

Source data

Extended Data Fig. 2 Agonist binding is the main driver for activation of the β2AR-Gs protein complex.

The optimized (a) unliganded-β2AR (apo); (c) carazolol-bound -β2AR (inverse agonist); and (e) ICI118551-bound -β2AR (inverse agonist) coupled to inactive Gs protein-bound GDP. (b), (d) & (f) MetaMD free energy versus the distance between the α-helical (AH) [the center of mass of Cαs for the residues 69-204] and Ras-like [the center of mass of Cαs for the residues 223-241, 250-285, and 294-358] subdomains. The weighted averages and the standard deviations were calculated for the reported ΔGif within the converged period. The metaMD free energies were reweighted31 for estimating the error. We used block averaging (n = 951 blocks) to report the standard deviation for each data point.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–20, Tables 1–5 and Videos 1–3.

Supplementary Video 1

MetaMD simulation of β2AR-bound BI167107 structure, starting from the activated structure (PDB 3SN6), but Gs protein was eliminated.

Supplementary Video 2

MetaMD simulation of β2AR-bound BI167107-GS-GDP structure from the intracellular view, showing a remarkable expansion in the cytoplasmic cavity of β2AR.

Supplementary Video 3

MetaMD simulation of β2AR-bound BI167107-GS-GDP structure, showing a remarkable GS protein opening, making GDP water exposed.

Source data

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Extended Data Fig./Table 1

Statistical source data.

Source Data Extended Data Fig./Table 2

Statistical source data.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mafi, A., Kim, SK. & Goddard, W.A. The dynamics of agonist-β2-adrenergic receptor activation induced by binding of GDP-bound Gs protein. Nat. Chem. 15, 1127–1137 (2023). https://doi.org/10.1038/s41557-023-01238-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41557-023-01238-6

  • Springer Nature Limited

Navigation