Abstract

Activation of the μ-opioid receptor (μOR) is responsible for the efficacy of the most effective analgesics. To shed light on the structural basis for μOR activation, here we report a 2.1 Å X-ray crystal structure of the murine μOR bound to the morphinan agonist BU72 and a G protein mimetic camelid antibody fragment. The BU72-stabilized changes in the μOR binding pocket are subtle and differ from those observed for agonist-bound structures of the β2-adrenergic receptor (β2AR) and the M2 muscarinic receptor. Comparison with active β2AR reveals a common rearrangement in the packing of three conserved amino acids in the core of the μOR, and molecular dynamics simulations illustrate how the ligand-binding pocket is conformationally linked to this conserved triad. Additionally, an extensive polar network between the ligand-binding pocket and the cytoplasmic domains appears to play a similar role in signal propagation for all three G-protein-coupled receptors.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Accessions

Primary accessions

Protein Data Bank

Data deposits

Coordinates and structure factors for the μOR–BU72–Nb39 complex have been deposited in the Protein Data Bank under accession code 5C1M.

References

  1. 1.

    et al. Loss of morphine-induced analgesia, reward effect and withdrawal symptoms in mice lacking the µ-opioid-receptor gene. Nature 383, 819–823 (1996)

  2. 2.

    A brief history of opiates, opioid peptides, and opioid receptors. Proc. Natl Acad. Sci. USA 90, 5391–5393 (1993)

  3. 3.

    , & (McGraw-Hill Medical, 2015)

  4. 4.

    , & Morphine side effects in β-arrestin 2 knockout mice. J. Pharmacol. Exp. Ther. 314, 1195–1201 (2005)

  5. 5.

    , , , & μ-Opioid receptor desensitization by β-arrestin-2 determines morphine tolerance but not dependence. Nature 408, 720–723 (2000)

  6. 6.

    et al. Enhanced morphine analgesia in mice lacking β-arrestin 2. Science 286, 2495–2498 (1999)

  7. 7.

    & Mu opioids and their receptors: evolution of a concept. Pharmacol. Rev. 65, 1257–1317 (2013)

  8. 8.

    & Specific receptor for the opioid peptide dynorphin: structure–activity relationships. Proc. Natl Acad. Sci. USA 78, 6543–6547 (1981)

  9. 9.

    et al. Crystal structure of the μ-opioid receptor bound to a morphinan antagonist. Nature 485, 321–326 (2012)

  10. 10.

    et al. Structure of the δ-opioid receptor bound to naltrindole. Nature 485, 400–404 (2012)

  11. 11.

    et al. Molecular control of δ-opioid receptor signalling. Nature 506, 191–196 (2014)

  12. 12.

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

  13. 13.

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

  14. 14.

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

  15. 15.

    et al. GPCR engineering yields high-resolution structural insights into β2-adrenergic receptor function. Science 318, 1266–1273 (2007)

  16. 16.

    et al. Structure of the human M2 muscarinic acetylcholine receptor bound to an antagonist. Nature 482, 547–551 (2012)

  17. 17.

    et al. Activation and allosteric modulation of a muscarinic acetylcholine receptor. Nature 504, 101–106 (2013)

  18. 18.

    et al. Crystal structure of rhodopsin: a G protein-coupled receptor. Science 289, 739–745 (2000)

  19. 19.

    et al. Crystal structure of metarhodopsin II. Nature 471, 651–655 (2011)

  20. 20.

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

  21. 21.

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

  22. 22.

    & The role of protein dynamics in GPCR function: insights from the β2AR and rhodopsin. Curr. Opin. Cell Biol. 27, 136–143 (2014)

  23. 23.

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

  24. 24.

    , & 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)

  25. 25.

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

  26. 26.

    et al. Synthesis and in vitro opioid activity profiles of DALDA analogues. Eur. J. Med. Chem. 35, 895–901 (2000)

  27. 27.

    et al. Characterization of the complex morphinan derivative BU72 as a high efficacy, long-lasting mu-opioid receptor agonist. Eur. J. Pharmacol. 499, 107–116 (2004)

  28. 28.

    Crystallizing membrane proteins for structure determination: use of lipidic mesophases. Annu. Rev. Biophys. 38, 29–51 (2009)

  29. 29.

    & Integrated methods for the construction of three-dimensional models and computational probing of structure-function relations in G protein-coupled receptors. Methods Neurosci. 25, 366–428 (1995)

  30. 30.

    et al. Structure of the human κ-opioid receptor in complex with JDTic. Nature 485, 327–332 (2012)

  31. 31.

    et al. Propagation of conformational changes during μ-opioid receptor activation. Nature (2015)

  32. 32.

    , & μ Opioid receptor: role for the amino terminus as a determinant of ligand binding affinity. Brain Res. Mol. Brain Res. 76, 64–72 (2000)

  33. 33.

    et al. Probing the activation-promoted structural rearrangements in preassembled receptor-G protein complexes. Nature Struct. Mol. Biol. 13, 778–786 (2006)

  34. 34.

    et al. BU74, a complex oripavine derivative with potent kappa opioid receptor agonism and delayed opioid antagonism. Eur. J. Pharmacol. 509, 117–125 (2005)

  35. 35.

    , & The irreversible narcotic antagonistic and reversible agonistic properties of the fumaramate methyl ester derivative of naltrexone. Eur. J. Pharmacol. 70, 445–451 (1981)

  36. 36.

    et al. High-resolution crystal structure of human protease-activated receptor 1. Nature 492, 387–392 (2012)

  37. 37.

    et al. Structural basis for allosteric regulation of GPCRs by sodium ions. Science 337, 232–236 (2012)

  38. 38.

    et al. The 2.1 Å resolution structure of cyanopindolol-bound β1-adrenoceptor identifies an intramembrane Na+ ion that stabilises the ligand-free receptor. PLoS ONE 9, e92727 (2014)

  39. 39.

    , & Opiate agonists and antagonists discriminated by receptor binding in brain. Science 182, 1359–1361 (1973)

  40. 40.

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

  41. 41.

    , , , & Crystal structure of the ligand-free G-protein-coupled receptor opsin. Nature 454, 183–187 (2008)

  42. 42.

    , , , & Rhodopsin and 9-demethyl-retinal analog: effect of a partial agonist on displacement of transmembrane helix 6 in class A G protein-coupled receptors. J. Biol. Chem. 283, 4967–4974 (2008)

  43. 43.

    et al. A general protocol for the generation of nanobodies for structural biology. Nature Protocols 9, 674–693 (2014)

  44. 44.

    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)

  45. 45.

    et al. Purification and functional reconstitution of monomeric mu-opioid receptors: allosteric modulation of agonist binding by Gi2. J. Biol. Chem. 284, 26732–26741 (2009)

  46. 46.

    & The kinetics of competitive radioligand binding predicted by the law of mass action. Mol. Pharmacol. 25, 1–9 (1984)

  47. 47.

    & Crystallizing membrane proteins using lipidic mesophases. Nature Protocols 4, 706–731 (2009)

  48. 48.

    XDS. Acta Crystallogr. D 66, 125–132 (2010)

  49. 49.

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

  50. 50.

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

  51. 51.

    et al. Towards automated crystallographic structure refinement with phenix.refine. Acta Crystallogr. D 68, 352–367 (2012)

  52. 52.

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

  53. 53.

    , , & OPM: orientations of proteins in membranes database. Bioinformatics 22, 623–625 (2006)

  54. 54.

    et al. CHARMM: The biomolecular simulation program. J. Comput. Chem. 30, 1545–1614 (2009)

  55. 55.

    , & Automated builder and database of protein/membrane complexes for molecular dynamics simulations. PLoS ONE 2, e880 (2007)

  56. 56.

    , , & CHARMM-GUI: a web-based graphical user interface for CHARMM. J. Comput. Chem. 29, 1859–1865 (2008)

  57. 57.

    et al. CHARMM-GUI Membrane Builder toward realistic biological membrane simulations. J. Comput. Chem. 35, 1997–2004 (2014)

  58. 58.

    et al. AMBER 14. (University of California, San Francisco, 2014)

  59. 59.

    , & SPFP: Speed without compromise—A mixed precision model for GPU accelerated molecular dynamics simulations. Comput. Phys. Commun. 184, 374–380 (2013)

  60. 60.

    , , , & Routine microsecond molecular dynamics simulations with Amber on GPUs. 2. Explicit solvent particle mesh Ewald. J. Chem. Theory Comput. 9, 3878–3888 (2013)

  61. 61.

    et al. Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone ϕ, ψ and side-chain χ1 and χ2 dihedral angles. J. Chem. Theory Comput. 8, 3257–3273 (2012)

  62. 62.

    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)

  63. 63.

    et al. All-atom empirical potential for molecular modeling and dynamics studies of proteins. J. Phys. Chem. B 102, 3586–3616 (1998)

  64. 64.

    , & Extending the treatment of backbone energetics in protein force fields: limitations of gas‐phase quantum mechanics in reproducing protein conformational distributions in molecular dynamics simulations. J. Comput. Chem. 25, 1400–1415 (2004)

  65. 65.

    et al. CHARMM general force field: a force field for drug-like molecules compatible with the CHARMM all-atom additive biological force fields. J. Comput. Chem. 31, 671–690 (2010)

  66. 66.

    , & VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996)

Download references

Acknowledgements

We acknowledge support from the Stanford Medical Scientist Training Program and the American Heart Association (A.M.), National Institutes of Health grants R37DA036246 (B.K.K. and S.G.) and R01GM083118 (B.K.K.), a Terman Faculty Fellowship (R.O.D.), Eli Lilly and Company through the Lilly Research Program (R.O.D.), and the Mathers Foundation (B.K.K. and W.I.W). We also acknowledge the National Institute of Drug Abuse Drug Supply Program for providing [Dmt1]DALDA. We thank D. Maurel and S. Agnel from the ARPEGE facility (Institut de Génomique Fonctionnelle) for assistance with cell-based Gi coupling assays, H. El Hassan for expert technical assistance, and S. Hertig, N. Latorraca and K. Cavalotti for assistance with molecular dynamics simulations and analysis.

Author information

Author notes

    • Weijiao Huang
    •  & Aashish Manglik

    These authors contributed equally to this work.

Affiliations

  1. Department of Molecular and Cellular Physiology, Stanford University School of Medicine, 279 Campus Drive, Stanford, California 94305, USA

    • Weijiao Huang
    • , Aashish Manglik
    • , A. J. Venkatakrishnan
    • , Evan N. Feinberg
    • , Adrian L. Sanborn
    • , Hideaki E. Kato
    • , Thor S. Thorsen
    • , William I. Weis
    • , Ron O. Dror
    •  & Brian K. Kobilka
  2. Department of Computer Science, Stanford University, 318 Campus Drive, Stanford, California 94305, USA

    • A. J. Venkatakrishnan
    • , Evan N. Feinberg
    • , Adrian L. Sanborn
    •  & Ron O. Dror
  3. Institute for Computational and Mathematical Engineering, Stanford University, 475 Via Ortega, Stanford, California 94305, USA

    • A. J. Venkatakrishnan
    • , Evan N. Feinberg
    • , Adrian L. Sanborn
    •  & Ron O. Dror
  4. Structural Biology Brussels, Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium

    • Toon Laeremans
    •  & Jan Steyaert
  5. Structural Biology Research Center, VIB, Pleinlaan 2, B-1050 Brussels, Belgium

    • Toon Laeremans
    •  & Jan Steyaert
  6. Department of Pharmacology, University of Michigan, Ann Arbor, Michigan 48109, USA

    • Kathryn E. Livingston
    •  & John R. Traynor
  7. Department of Chemistry and Pharmacy, Friedrich Alexander University, Schuhstrasse 19, 91052 Erlangen, Germany

    • Ralf C. Kling
    •  & Peter Gmeiner
  8. Institut de Génomique Fonctionnelle, CNRS UMR-5203 INSERM U1191, University of Montpellier, F-34000 Montpellier, France

    • Sébastien Granier
  9. Department of Pharmacy and Pharmacology, University of Bath, Bath BA2 7AY, UK

    • Stephen M. Husbands
  10. Department of Structural Biology, Stanford University School of Medicine, 299 Campus Drive, Stanford, California 94305, USA

    • William I. Weis

Authors

  1. Search for Weijiao Huang in:

  2. Search for Aashish Manglik in:

  3. Search for A. J. Venkatakrishnan in:

  4. Search for Toon Laeremans in:

  5. Search for Evan N. Feinberg in:

  6. Search for Adrian L. Sanborn in:

  7. Search for Hideaki E. Kato in:

  8. Search for Kathryn E. Livingston in:

  9. Search for Thor S. Thorsen in:

  10. Search for Ralf C. Kling in:

  11. Search for Sébastien Granier in:

  12. Search for Peter Gmeiner in:

  13. Search for Stephen M. Husbands in:

  14. Search for John R. Traynor in:

  15. Search for William I. Weis in:

  16. Search for Jan Steyaert in:

  17. Search for Ron O. Dror in:

  18. Search for Brian K. Kobilka in:

Contributions

W.H. developed functional purification protocols, expressed and purified μOR, characterized the effect of nanobodies and Gi on μOR ligand affinity, identified Nb39 for crystallography of the μOR–Nb complex, performed crystallization trials, data collection, structure determination and refinement. A.M. established the project with biochemistry of active μOR, prepared samples for llama immunization, validated nanobody activity, performed crystallization trials, and identified initial crystals of the μOR–BU72–Nb complex suitable for diffraction studies. A.J.V. analysed the polar network. A.J.V., E.F. and A.S. performed and analysed molecular dynamics simulations with supervision from R.O.D. T.L. identified μOR-binding nanobodies with supervision from J.S. S.G. established the biochemistry for purification of agonist-bound μOR and prepared samples for μOR immunization. H.E.K. helped with data collection and processing. T.S.T helped with the characterization of the amino-terminal region. R.K. and P.G. analysed BU72 and assessed alternative ligand structures. S.M.H. synthesized BU72. K.E.L. and J.R.T. helped with selection of opioid ligands including BU72 and performed dissociation kinetics experiments. W.I.W. supervised structure refinement. A.M. and B.K.K. provided overall project supervision and wrote the manuscript with W.H. and R.O.D.

Competing interests

A.M., T.L., J.S. and B.K.K. have filed a patent for active-state stabilizing nanobodies for opioid receptors.

Corresponding authors

Correspondence to Aashish Manglik or Brian K. Kobilka.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains an overview of molecular dynamics simulations and ligand parameterization.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature14886

Further reading

Comments

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.