Abstract
The adenosine A2A receptor (A2AR) engages several G proteins, notably Go and its cognate Gs protein. This coupling promiscuity is facilitated by a dynamic ensemble, revealed by 19F nuclear magnetic resonance imaging of A2AR and G protein. Two transmembrane helix 6 (TM6) activation states, formerly associated with partial and full agonism, accommodate the differing volumes of Gs and Go. While nucleotide depletion biases TM7 toward a fully active state in A2AR–Gs, A2AR–Go is characterized by a dynamic inactive/intermediate fraction. Molecular dynamics simulations reveal that the NPxxY motif, a highly conserved switch, establishes a unique configuration in the A2AR–Go complex, failing to stabilize the helix-8 interface with Gs, and adoption of the active state. The resulting TM7 dynamics hamper G protein coupling, suggesting kinetic gating may be responsible for reduced efficacy in the noncognate G protein complex. Thus, dual TM6 activation states enable greater diversity of coupling partners while TM7 dynamics dictate coupling efficacy.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
All data from this study are included in Source data files provided with this paper. Requests for further information, resources and reagents should be directed to and will be fulfilled by the lead contacts, Scott Prosser (scott.prosser@utoronto.ca), Louis-Philippe Picard (louisphilippe.picard@utoronto.ca) or Adnan Sljoka (adnan.sljoka@riken.jp).
Change history
28 August 2024
A Correction to this paper has been published: https://doi.org/10.1038/s41589-024-01732-z
References
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).
Tehan, B. G., Bortolato, A., Blaney, F. E., Weir, M. P. & Mason, J. S. Unifying family A GPCR theories of activation. Pharmacol. Ther. 143, 51–60 (2014).
Inoue, A. et al. Illuminating G-protein-coupling selectivity of GPCRs. Cell 177, 1933–1947.e25 (2019).
Zhou, Q. et al. Common activation mechanism of class A GPCRs. eLife 8, e50279 (2019).
Kapolka, N. J. et al. DCyFIR: a high-throughput CRISPR platform for multiplexed G protein-coupled receptor profiling and ligand discovery. Proc. Natl Acad. Sci. USA 117, 13117–13126 (2020).
Madsen, J. J., Ye, L., Frimurer, T. M. & Olsen, O. H. Mechanistic basis of GPCR activation explored by ensemble refinement of crystallographic structures. Protein Sci. 31, e4456 (2022).
Avet, C. et al. Effector membrane translocation biosensors reveal G protein and βarrestin coupling profiles of 100 therapeutically relevant GPCRs. eLife 11, e74101 (2022).
Chen, S., Teng, X. & Zheng, S. Molecular basis for the selective G protein signaling of somatostatin receptors. Nat. Chem. Biol. 19, 133–140 (2023).
Shimada, I., Ueda, T., Kofuku, Y., Eddy, M. T. & Wüthrich, K. GPCR drug discovery: integrating solution NMR data with crystal and cryo-EM structures. Nat. Rev. Drug Discov. 10, 579 (2018).
Nygaard, R. et al. The dynamic process of β2-adrenergic receptor activation. Cell 152, 532–542 (2013).
Kofuku, Y. et al. Functional dynamics of deuterated β2-adrenergic receptor in lipid bilayers revealed by NMR spectroscopy. Angew. Chem. Int. ed. Engl. 53, 13376–13379 (2014).
Manglik, A. et al. Structural insights into the dynamic process of β2-adrenergic receptor signaling. Cell 161, 1101–1111 (2015).
Isogai, S. et al. Backbone NMR reveals allosteric signal transduction networks in the β1-adrenergic receptor. Nature 530, 237–241 (2016).
Eddy, M. T. et al. Allosteric coupling of drug binding and intracellular signaling in the A2A adenosine receptor. Cell 172, 68–80.e12 (2018).
Mizumura, T. et al. Activation of adenosine A2A receptor by lipids from docosahexaenoic acid revealed by NMR. Sci. Adv. 6, eaay8544 (2020).
Huang, S. K. et al. Delineating the conformational landscape of the adenosine A2A receptor during G protein coupling. Cell 184, 1884–1894.e14 (2021).
Wu, F.-J. et al. Nanobody GPS by PCS: an efficient new NMR analysis method for G protein coupled receptors and other large proteins. J. Am. Chem. Soc. 144, 21728–21740 (2022).
Guerrero, A. A2A adenosine receptor agonists and their potential therapeutic applications. An update. Curr. Med. Chem. 25, 3597–3612 (2018).
Gessi, S. et al. A2A adenosine receptor as a potential biomarker and a possible therapeutic target in Alzheimer’s disease. Cells 10, 2344 (2021).
Fredholm, B. B., Chen, J.-F., Masino, S. A. & Vaugeois, J.-M. Actions of adenosine at its receptors in the CNS: insights from knockouts and drugs. Annu. Rev. Pharmacol. Toxicol. 45, 385–412 (2005).
Yu, F., Zhu, C., Xie, Q. & Wang, Y. Adenosine A2A receptor antagonists for cancer immunotherapy: miniperspective. J. Med. Chem. 63, 12196–12212 (2020).
Hickey, P. & Stacy, M. Adenosine A2A antagonists in Parkinson’s disease: what’s next? Curr. Neurol. Neurosci. 12, 376–385 (2012).
Morello, S., Sorrentino, R. & Pinto, A. Adenosine A2a receptor agonists as regulators of inflammation: pharmacology and therapeutic opportunities. J. Receptor Ligand Channel Res. 2, 11–17 (2009).
Zhu, C. et al. Adenosine A2A receptor antagonist istradefylline 20 versus 40 mg/day as augmentation for Parkinson’s disease: a meta-analysis. Neurol. Res. 36, 1028–1034 (2014).
Victor-Vega, C., Desai, A., Montesinos, M. C. & Cronstein, B. N. Adenosine A2A receptor agonists promote more rapid wound healing than recombinant human platelet–derived growth factor (becaplermin gel). Inflammation 26, 19–24 (2002).
Valls, M. D., Cronstein, B. N. & Montesinos, M. C. Adenosine receptor agonists for promotion of dermal wound healing. Biochem. Pharmacol. 77, 1117–1124 (2009).
Jenner, P. An Overview of Adenosine A2A Receptor Antagonists in Parkinson’s Disease Vol. 119 (Elsevier, 2014).
Zheng, J., Zhang, X. & Zhen, X. Development of adenosine A2A receptor antagonists for the treatment of Parkinson’s disease: a recent update and challenge. ACS Chem. Neurosci. 10, 783–791 (2019).
Cunha, R. A. Neuroprotection by adenosine in the brain: from A1 receptor activation to A2A receptor blockade. Purinergic Signal. 1, 111–134 (2005).
Allard, D., Turcotte, M. & Stagg, J. Targeting A2 adenosine receptors in cancer. Immunol. Cell Biol. 95, 333–339 (2017).
Fredholm, B., Cunha, R. & Svenningsson, P. Pharmacology of adenosine A2A receptors and therapeutic applications. Curr. Top. Med. Chem. 3, 413–426 (2003).
Mondal, S., Hsiao, K. & Goueli, S. A. A homogenous bioluminescent system for measuring GTPase, GTPase activating protein, and guanine nucleotide exchange factor activities. Assay Drug Dev. Technol. 13, 444–455 (2015).
Carpenter, B., Nehmé, R., Warne, T., Leslie, A. G. W. & Tate, C. G. Structure of the adenosine A2A receptor bound to an engineered G protein. Nature 536, 104–107 (2016).
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, 213 (2018).
Flock, T. et al. Universal allosteric mechanism for Gα activation by GPCRs. Nature 524, 173 (2015).
Venkatakrishnan, A. J. et al. Diverse activation pathways in class A GPCRs converge near the G-protein-coupling region. Nature 536, 484–487 (2016).
Ragnarsson, L., Andersson, Å., Thomas, W. G. & Lewis, R. J. Mutations in the NPxxY motif stabilize pharmacologically distinct conformational states of the α1B- and β2-adrenoceptors. Sci. Signal. 12, eaas9485 (2019).
Prosser, R. S., Ye, L., Pandey, A. & Orazietti, A. Activation processes in ligand-activated G protein-coupled receptors: a case study of the adenosine A2A receptor. BioEssays 39, 1700072–10 (2017).
Sušac, L., Eddy, M. T., Didenko, T., Stevens, R. C. & Wüthrich, K. A2A adenosine receptor functional states characterized by 19F-NMR. Proc. Natl Acad. Sci. USA 115, 12733–12738 (2018).
Sykes, B. D., Weingarten, H. I. & Schlesinger, M. J. Fluorotyrosine alkaline phosphatase from Escherichia coli: preparation, properties, and fluorine-19 nuclear magnetic resonance spectrum. Proc. Natl Acad. Sci. USA 71, 469–473 (1974).
Lovera, S., Cuzzolin, A., Kelm, S., Fabritiis, G. D. & Sands, Z. A. Reconstruction of apo A2A receptor activation pathways reveal ligand-competent intermediates and state-dependent cholesterol hotspots. Sci. Rep. 9, 14199 (2019).
Liu, X. et al. Structural insights into the process of GPCR-G protein complex formation. Cell 177, 1–22 (2019).
Wang, J. & Miao, Y. Mechanistic insights into specific G protein interactions with adenosine receptors. J. Phys. Chem. B 123, 6462–6473 (2019).
Hata, H., Tran, D. P., Sobeh, M. M. & Kitao, A. Binding free energy of protein/ligand complexes calculated using dissociation Parallel Cascade Selection Molecular Dynamics and Markov state model. Biophys. Physicobiol. 18, 305–316 (2021).
Tran, D. P. & Kitao, A. Dissociation process of a MDM2/p53 complex investigated by parallel cascade selection molecular dynamics and the Markov state model. J. Phys. Chem. B 123, 2469–2478 (2019).
Farrell, D. W., Speranskiy, K. & Thorpe, M. F. Generating stereochemically acceptable protein pathways. Proteins 78, 2908–2921 (2010).
Zhu, S. et al. Hyperphosphorylation of intrinsically disordered tau protein induces an amyloidogenic shift in its conformational ensemble. PLoS ONE 10, e0120416 (2015).
Gowers, R. J. et al. MDAnalysis: a Python package for the rapid analysis of molecular dynamics simulations. SciPy2016 https://doi.org/10.25080/majora-629e541a-00e (2016).
Huang, S. et al. GPCRs steer Gi and Gs selectivity via TM5-TM6 switches as revealed by structures of serotonin receptors. Mol. Cell 82, 2681–2695.e6 (2022).
Westfield, G. H. et al. Structural flexibility of the Gαs α-helical domain in the β2-adrenoceptor Gs complex. Proc. Natl Acad. Sci. USA 108, 16086–16091 (2011).
Eps, N. V. et al. Interaction of a G protein with an activated receptor opens the interdomain interface in the alpha subunit. Proc. Natl Acad. Sci. USA 108, 9420–9424 (2011).
Ham, D. et al. Conformational switch that induces GDP release from Gi. J. Struct. Biol. 213, 107694 (2021).
Huang, S. K. et al. Mapping the conformational landscape of the stimulatory heterotrimeric G protein. Nat. Struct. Mol. Biol. 30, 502–511 (2023).
Koehl, A. et al. Structure of the µ-opioid receptor–Gi protein complex. Nature 558, 547–552 (2018).
Eps, N. V. et al. Gi- and Gs-coupled GPCRs show different modes of G-protein binding. Proc. Natl Acad. Sci. USA 115, 2383–2388 (2018).
Maeda, S., Qu, Q., Robertson, M. J., Skiniotis, G. & Kobilka, B. K. Structures of the M1 and M2 muscarinic acetylcholine receptor/G-protein complexes. Science 364, 552–557 (2019).
Faurobert, E., Otto‐Bruc, A., Chardin, P. & Chabre, M. Tryptophan W207 in transducin T alpha is the fluorescence sensor of the G protein activation switch and is involved in the effector binding. EMBO J. 12, 4191–4198 (1993).
Sljoka, A. Probing allosteric mechanism with long-range rigidity transmission across protein networks. Methods Mol. Biol. 2253, 61–75 (2021).
Chen, X. et al. Structural determinants in the second intracellular loop of the human cannabinoid CB1 receptor mediate selective coupling to Gs and Gi. Br. J. Pharmacol. 161, 1817–1834 (2010).
Hauser, A. S. et al. Common coupling map advances GPCR-G protein selectivity. eLife 11, e74107 (2022).
Sandhu, M. et al. Dynamic spatiotemporal determinants modulate GPCR:G protein coupling selectivity and promiscuity. Nat. Commun. 13, 7428 (2022).
Okashah, N. et al. Variable G protein determinants of GPCR coupling selectivity. Proc. Natl Acad. Sci. USA 46, 201905993–201905996 (2019).
Flock, T. et al. Selectivity determinants of GPCR–G-protein binding. Nature 545, 317–322 (2017).
Tawfik, D. S. Accuracy-rate tradeoffs: how do enzymes meet demands of selectivity and catalytic efficiency? Curr. Opin. Chem. Biol. 21, 73–80 (2014).
Copley, S. D. An evolutionary biochemist’s perspective on promiscuity. Trends Biochem. Sci. 40, 72–78 (2015).
Pabon, N. A. & Camacho, C. J. Probing protein flexibility reveals a mechanism for selective promiscuity. eLife 6, e22889 (2017).
Okashah, N. et al. Variable G protein determinants of GPCR coupling selectivity. Proc. Natl Acad. Sci. USA 116, 12054–12059 (2019).
Sandhu, M. et al. Conformational plasticity of the intracellular cavity of GPCR−G-protein complexes leads to G-protein promiscuity and selectivity. Proc. Natl Acad. Sci. USA 116, 11956–11965 (2019).
Ridge, K. D. et al. NMR analysis of rhodopsin–transducin interactions. Vis. Res. 46, 4482–4492 (2006).
Wrabl, J. O. et al. The role of protein conformational fluctuations in allostery, function, and evolution. Biophys. Chem. 159, 129–141 (2011).
Motlagh, H. N., Wrabl, J. O., Li, J. & Hilser, V. J. The ensemble nature of allostery. Nature 508, 331–339 (2014).
Ye, L., Eps, N. V., Zimmer, M., Ernst, O. P. & Prosser, R. S. Activation of the A2A adenosine G-protein-coupled receptor by conformational selection. Nature 533, 265 (2016).
Etzkorn, M. et al. Cell-free expressed bacteriorhodopsin in different soluble membrane mimetics: biophysical properties and NMR accessibility. Structure 21, 394–401 (2013).
Ehrlich, A. T. et al. Mapping GPR88-Venus illuminates a novel role for GPR88 in sensory processing. Brain Struct. Funct. 223, 1275–1296 (2018).
Fiser, A. & Šali, A. Modeller: generation and refinement of homology-based protein structure models. Methods Enzymol. 374, 461–491 (2003).
Tian, C. et al. ff19SB: amino-acid-specific protein backbone parameters trained against quantum mechanics energy surfaces in solution. J. Chem. Theory Comput. 16, 528–552 (2019).
He, X., Man, V. H., Yang, W., Lee, T.-S. & Wang, J. A fast and high-quality charge model for the next generation general AMBER force field. J. Chem. Phys. 153, 114502 (2020).
Dickson, C. J. et al. Lipid14: the amber lipid force field. J. Chem. Theory Comput. 10, 865–879 (2014).
Izadi, S., Anandakrishnan, R. & Onufriev, A. V. Building water models: a different approach. J. Phys. Chem. Lett. 5, 3863–3871 (2014).
Nosé, S. A unified formulation of the constant temperature molecular dynamics methods. J. Chem. Phys. 81, 511–519 (1984).
Hoover, W. G. Canonical dynamics-equilibrium phase-space distributions. Phys. Rev. A 31, 1695–1697 (1985).
Parrinello, M. & Rahman, A. Polymorphic transitions in single crystals: a new molecular dynamics method. J. Appl. Phys. 52, 7182–7190 (1981).
Scherer, M. K. et al. PyEMMA 2: a software package for estimation, validation, and analysis of Markov models. J. Chem. Theory Comput. 11, 5525–5542 (2015).
Harada, R. & Kitao, A. Parallel cascade selection molecular dynamics (PaCS-MD) to generate conformational transition pathway. J. Chem. Phys. 139, 035103 (2013).
Ikizawa, S. et al. PaCS-Toolkit: optimized software utilities for parallel cascade selection molecular dynamics (PaCS-MD) simulations and subsequent analyses. J. Phys. Chem. B 128, 3631–3642 (2024).
Sljoka, A. in Sublinear Computation Paradigm (eds Katoh, N. et al.) 337–367 (Springer Singapore, 2022).
Tucs, A., Tsuda, K. & Sljoka, A. Probing conformational dynamics of antibodies with geometric simulations. Methods Mol. Biol. 2552, 125–139 (2023).
Sljoka, A. Algorithms in rigidity theory with applications to protein flexibility and mechanical linkages. PhD dissertation, York University. (2012).
Whiteley, W. Counting out to the flexibility of molecules. Phys. Biol. 2, S116–S126 (2005).
Jacobs, D. J., Rader, A. J., Kuhn, L. A. & Thorpe, M. F. Protein flexibility predictions using graph theory. Proteins 44, 150–165 (2001).
Acknowledgements
This work was supported by the Canadian Institutes of Health Research (CIHR) Operating Grant no. MOP-43998 to R.S.P.; the MEXT/JSPS KAKENHI grant nos. JP19K23721 and JP23K14154 D.P.T. and grant nos. JP19H03191, JP22H04745, JP23H02445 and JP23H02445 to A.K.; and the MEXT ‘Program for Promoting Research on the Supercomputer Fugaku’ (Simulation- and AI-driven next-generation medicine and drug discovery based on ‘Fugaku’, grant no. JPMXP1020230120) to D.P.T. A.S. was supported by the RIKEN International Collaboration Program grant. S.K.H. was supported by an Alexander Graham Bell Canada Graduate Scholarship-Doctoral from NSERC. A.S. was supported by CREST, Japan Science and Technology Agency (JST), Japan, grant no. JPMJCR1402. We thank M. Bouvier for providing constructs for BRET studies, D. Pichugin for technical assistance and maintenance of the NMR spectrometer at the Center for Magnetic Resonance Research, University of Toronto Mississauga, and the UTM’s Office of the Vice-Principal, Research (OVPR), for providing research infrastructure needed for this research. We also thank S. Furness (U. Queensland) for helpful suggestions. This work also used computational resources provided by the Institute for Solid State Physics, the University of Tokyo, the Research Center for Computational Science, Okazaki, Japan (Project: 23-IMS-C045), and the supercomputer Fugaku through the HPCI System Research Project (Project IDs: hp220107, hp230077 and hp240024) and the RIKEN Center for Computational Science (Project ID: hp230216).
Author information
Authors and Affiliations
Contributions
L.-P.P., A.O. and R.S.P. designed the research. L.-P.P., A.O., Z.Q. and S.K.H. performed protein expression and purification. L.-P.P. performed BRET and hydrolysis experiments. L.-P.P. and A.O. performed NMR experiments. D.P.T. and S.H. performed MD simulations under the supervision of A.K. A.K. designed and supervised analysis of molecular modelling, MD simulations, PCA analysis and related analysis. A.T. performed MC simulations under the supervision of A.S. K.T. assisted with simulations. A.S. performed RTA analysis. A.S. designed and supervised computational analysis, M.C. simulations and rigidity theory analysis. L.-P.P., A.O., D.P.T., A.K., A.S. and R.S.P. prepared the manuscript. R.S.P. supervised the project.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Chemical Biology thanks Yinglong Miao 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 A2AR coupling to multiple G proteins and corresponding Bioluminescence Resonance Energy Transfer (BRET) and 19F NMR response to Gs and Go associated with TM6.
(a) Schematic representation of the BRET sensor, showing activation through the addition of an agonist (yellow triangle) and the corresponding dissociation of the α and βγ subunits, allowing for formation of the GRK-GFP and βγ-RLuc BRET pair. (b) BRET-based assay showing coupling of A2AR to Gs and Go upon agonist (NECA) stimulation. Data represent mean +/− SEM of n = 4 independent experiments. (c) Overlay of inactive and mini-Gs bound active A2AR crystal structures, illustrating the reorientation of TM6. (d) 19F NMR of TM6 labeled A2AR. The A2AR inactive ensemble (S1TM6 and S2TM6) is distinguished by a salt bridge between R1023.50 and E2286.30 that is either intact (S1TM6, −61.2 ppm) or broken (S2TM6, −60.9 ppm), where disruption of the salt bridge is necessary for reorientation of TM6 and activation. The A2AR activation ensemble is characterized by a preactivated state (A3), observed upon complexation of the apo receptor with GDP-bound G protein, and two distinct active states (A1 and A2) which become prominent upon removal of nucleotide. The nucleotide-free A2AR-Go complex is characterized by a lack of the A1 state, formerly associated with full agonism in the A2AR-Gs complex. All 19F NMR spectra are deconvoluted into a superposition of Lorentzian lines as shown. The light red line illustrates the residual error between the fitted and experimental spectra.
Extended Data Fig. 2 TM7-labeled A2AR reveals multiple intermediates and activation states.
a) 19F NMR reveals a wealth of functional states in a dynamic equilibrium. Complexation with Gs results in an activation ensemble, defined by A1TM7, A2TM7 and A3TM7. Removal of nucleotide subsequently shifts this activation ensemble toward A1TM7. In contrast, complexation with Go results in a partial shift to the activation ensemble, while multiple activation intermediates persist upon nucleotide removal. b) Overlay of inactive and active crystal structures of A2AR depict reorientation of TM7 upon complexation with mini-Gs. c–d) T2-filtered spectroscopy of the nucleotide-free complexes reveals sub-millisecond timescale dynamics of the intermediates, while the surviving (long-T2) activation states are identical for the nucleotide-free A2AR-Gs and A2AR-Go complexes. In this experiment, signal associated with states undergoing conformational exchange comparable to or faster than the refocusing frequency will become decoherent and not be fully refocused such that an exchange rate can be derived75. The overall effect is the removal from the apparent spectra of any such homogeneous line broadening. Here, a delay of 150 μs between refocusing pulses was used in the T2-filtered spectroscopy, corresponding to a refocusing frequency (1/4τ) of 1.67 kHz.
Extended Data Fig. 3 RMSD of heavy atoms from the initial structures during MD simulations.
(a) RMSD of heavy atoms associated with A2AR only for the A2AR-Gs complex. Note that the 10 different colors designate separate 1 µs trajectories for a total sampling time of 10 µs. (b) RMSD of A2AR heavy atoms for the A2AR-Go complex. (c) RMSD of heavy atoms of Gs in the A2AR-Gs complex (d) RMSD of Go in the A2AR-Go complex. RMSD is calculated after first superimposing structures to the initial energy minimized reference structure. In general, the simulated structures were judged to converge after 500 ns. Note that one trajectory undergoes a significant departure at ~ 500 ns (orange in d), indicative of a global rearrangement of Go. (e) Overlay of A2A-Gs in cyan (in (c) at 990 ns indicated by the arrow) and the outlier A2AR-Gs (shown in red in (c) at 990 ns indicated by the arrow). The difference is largely a consequence of rearrangement of the αN helix of Gα and the Ras domain. (f) Overlay of A2A-Go in magenta (in (d) at 990 ns indicated by the arrow) and the outlier A2AR-Go (shown in orange in (d) at 990 ns indicated by the arrow). Here, the outlier is distinguished by a reorientation of the αN helix as well as that of Gγ.
Extended Data Fig. 4 Evaluation of direct interactions in the A2AR-Gs and A2AR-Go complexes.
a) Connectivity map showing residues making direct contact with Gαs. Magenta and grey lines designate hydrogen bonds or hydrophobic contacts respectively. b) A2AR-Gαo connectivity map.
Extended Data Fig. 5 Calculation of binding free energies for the A2AR-Gs and A2AR-Go complexes by dPaCS-MD/MSM.
(a, c) The dissociation process of G proteins from A2AR shown by the inter-center of mass distances between A2AR and Gs/Go, d, as a function of dPaCS-MD cycle. The results for a) A2AR-Gs and c) A 2AR-Go. (b, d) The potential of mean force (PMF) as a function of d for (b) A2AR-Gs and (d) A2AR-Go obtained from the Markov State Model (MSM). The results of five trials (dots) and the average (thick lines) are shown. The PMF of the bound state is −22.1 ± 1.6 (A2AR-Gs) and −19.7 ± 1.5 (A2AR-Go) kcal/mol compared to that of the completely unbound states. Considering the volume correction of 1.8 ± 0.1 (A2AR-Gs) and 1.7 ± 0.2 (A2AR-Go) kcal/mol, the standard binding free energies are −20.3 ± 1.6 (A2AR-Gs) and −18.0 ± 1.5 (A2AR-Go) kcal/mol. (e, f) The implied time scale versus lag time plots of MSM for (e) A2AR-Gs and (f) A2AR-Go. The lag time of 50 ps was used to construct MSM.
Extended Data Fig. 6 A2AR-Gs and A2AR-Go have distinct features of the NPxxY motif and conformational dynamics.
a) MD simulations reveal an ensemble of NPxxY A2AR-Gs and A2AR-Go dihedral angle configurations in a nucleotide-free or GDP-bound states. b) Difference in Root Mean Square Fluctuations as a function of residue across A2AR between A2AR-Gs and A2AR-Go complexes during MC simulation. Note that cutoff energies of 1, 2, and 3 kcal/mol refer to the extent of sampling of conformers and give rise to predictably greater excursions in the Gs and Go complexes, particularly in the vicinity of ECL2 and ICL3. c) MC-derived distances between R2938.48 and E378H5.24/G352H5.24.
Extended Data Fig. 7 Principal component analysis (PCA) of A2AR conformations sampled by 10 μs MD simulations.
Projections onto the space spanned by the first two principal components (PCs) and conformational changes along these PCs, showing the distributions of the snapshots from each cluster with different color. The stars indicate the representative structures of the most populated clusters (Cluster 1) and the crosses signify the representative structures from the rest of the clusters. The x- and y-axes are scaled by the standard deviations (σ) of PC1 and PC2 (1.0 and 0.7 Å for A2AR-Gs and 1.1 and 0.8 Å for A2AR-Go) (a) Superposition of A2AR-Gs structures (right) and corresponding PCA mapping (left). Structures were generated by moving the average structure at (PC1, PC2) = (0,0) from −0.5 σ to 0.5 σ along PC1 or PC2. (b) Superposition of A2AR-Go structures (right) and corresponding PCA mapping (left).
Extended Data Fig. 8 The volume of the H5-helix dictates TM6 position.
a) Superposition of 56 Gs coupled receptors(orange) and 15 Go coupled receptors (blue) shows TM6 adopts a more outward orientation by 2 Å in the case of Gs. b-c) H5 volume of Gs (b) and Go (c) on all structures shown in a protein modeled by MD simulations with volume calculations for the last 5 and 8 amino acids and full H5 on all structures showing a bigger volume for Gs.
Extended Data Fig. 9 Validation of Gα constructs.
a-b) GloSensor assays of A2AGs and A2AGo heterotrimers, utilizing the 19F-labeled Δ5 Gαs and Δ5 Gαo constructs. Data are presented as mean values +/− SEM of n = 4 independent experiments. c) Native tryptophan residues and the conserved FH5.08 are overlayed between GDP-bound Gαs (PDB: 6eg8, dark red and brown) and GTPγS-bound Gαs (PDB: 1AZT, red and orange). d) 19F NMR spectra of 5FW-enriched Gαs. Individual unassigned resonances are resolved (P1S-P4S) for each of the four native tryptophan residues for the WT Gαs (dark red spectra). GTPγS substitution (light red spectra) produces no changes aside from a downfield shift in resonance P2S. The mutant F362WG.H5.08Gαs produces spectra with an additional severely broadened resonance (P5S, −128.25 ppm). GTPγS for GDP substitution (orange and brown spectra, respectively) reveals no large-scale changes in H5 helix topology related to the bound nucleotide, however, significant line broadening suggests local exchange processes at the H5 helix. e) Native tryptophan residues and the conserved FH5.08 are shown in the GDP-bound state (PDB: 3c7k, Blue and teal, respectively). f) 19F NMR spectra of 5FW-enriched Gαo. Unassigned resonances for the two native tryptophan residues are resolved for the WT Gαo in the GDP-bound (dark blue) and GTPγS-bound (light blue) states (P1O, P2O) where, only one tryptophan is sensitive to nucleotide exchange. Finer resolution of minor state conformers in the GDP-bound state alongside the dominant peak P2O indicate plasticity around the nucleotide core which is abrogated upon exchange for GTPγS. Mutant F336WG.H5.08 Gαo, similarly to Gαs, is insensitive to the presence of either GDP (teal spectra) or GTPγS (aqua spectra). The results reflect the higher basal activity of Go, where the dominant resonance of the nucleotide sensitive tryptophan associated with GTPγS binding is also dominant in the GDP-bound state.
Extended Data Fig. 10 Allosteric pathways in the A2AR-Gs and A2AR-Go complexes and commonalities with the serotonin-G protein complexes.
(a-b) Predicted allosteric pathway propagating through the G-protein upon rigidification of the nucleotide binding pocket in the A2AR-Gs (a) and A2AR-Go (b) complexes. (c-d) Predicted allosteric pathway propagating through the receptor in the 5HT4-Gs (c) and 5HT4-Gi (d) complexes, upon rigidification of the agonist binding contacts.
Supplementary information
Supplementary Information
Supplementary Tables 1 and 2.
Supplementary Video 1
Video of the A2AR-Gs complex and associated principal components: PC1, PC2 and PC3. Significant conformational changes are observed within ECL2, ICL3 and NPxxY motifs through the trajectories.
Supplementary Video 2
Video of the A2AR-Go complex and associated principal components: PC1, PC2 and PC3. Significant conformational changes are observed within ECL2, ICL3 and NPxxY motifs through the trajectories.
Source data
Source Data Fig. 1
Statistical source data.
Source Data Fig. 2
Statistical source data.
Source Data Fig. 3
Statistical source data.
Source Data Extended Data Fig. 1
Statistical source data.
Source Data Extended Data Fig. 2
Statistical source data.
Source Data Extended Data Fig. 3
Statistical source data.
Source Data Extended Data Fig. 5
Statistical source data.
Source Data Extended Data Fig. 6
Statistical source data.
Source Data Extended Data Fig. 7
Statistical source data.
Source Data Extended Data Fig. 9
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.
About this article
Cite this article
Picard, LP., Orazietti, A., Tran, D.P. et al. Balancing G protein selectivity and efficacy in the adenosine A2A receptor. Nat Chem Biol (2024). https://doi.org/10.1038/s41589-024-01682-6
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41589-024-01682-6