Skip to main content

Thank you for visiting nature.com. 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.

  • Article
  • Published:

In silico design of novel probes for the atypical opioid receptor MRGPRX2

Abstract

The primate-exclusive MRGPRX2 G protein-coupled receptor (GPCR) has been suggested to modulate pain and itch. Despite putative peptide and small-molecule MRGPRX2 agonists, selective nanomolar-potency probes have not yet been reported. To identify a MRGPRX2 probe, we first screened 5,695 small molecules and found that many opioid compounds activated MRGPRX2, including (−)- and (+)-morphine, hydrocodone, sinomenine, dextromethorphan, and the prodynorphin-derived peptides dynorphin A, dynorphin B, and α- and β-neoendorphin. We used these to select for mutagenesis-validated homology models and docked almost 4 million small molecules. From this docking, we predicted ZINC-3573—a potent MRGPRX2-selective agonist, showing little activity against 315 other GPCRs and 97 representative kinases—along with an essentially inactive enantiomer. ZINC-3573 activates endogenous MRGPRX2 in a human mast cell line, inducing degranulation and calcium release. MRGPRX2 is a unique atypical opioid-like receptor important for modulating mast cell degranulation, which can now be specifically modulated with ZINC-3573.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Validation of MRGPRX2 and MRGPRB2 Agonists.
Figure 2: PRESTO-Tango Screening of MRGPRX2 reveals new agonists.
Figure 3: MRGPRX2 is activated by many opioid scaffolds.
Figure 4: MRGPRX2 is preferentially activated by prodynorphin-derived peptides.
Figure 5: In silico MRGPRX2 homology modeling predicts a selective agonist.
Figure 6: MRGPRX2 mediates intracellular calcium release and degranulation in the LAD2 human mast cell line.

Similar content being viewed by others

Accession codes

Accessions

Protein Data Bank

References

  1. Allen, J.A. & Roth, B.L. Strategies to discover unexpected targets for drugs active at G protein-coupled receptors. Annu. Rev. Pharmacol. Toxicol. 51, 117–144 (2011).

    CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  3. Huang, X.P. et al. Allosteric ligands for the pharmacologically dark receptors GPR68 and GPR65. Nature 527, 477–483 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Rask-Andersen, M., Masuram, S. & Schiöth, H.B. The druggable genome: evaluation of drug targets in clinical trials suggests major shifts in molecular class and indication. Annu. Rev. Pharmacol. Toxicol. 54, 9–26 (2014).

    CAS  PubMed  Google Scholar 

  5. Fredriksson, R. & Schiöth, H.B. The repertoire of G-protein-coupled receptors in fully sequenced genomes. Mol. Pharmacol. 67, 1414–1425 (2005).

    CAS  PubMed  Google Scholar 

  6. Kroeze, W.K. et al. PRESTO-Tango as an open-source resource for interrogation of the druggable human GPCRome. Nat. Struct. Mol. Biol. 22, 362–369 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Ngo, T. et al. Identifying ligands at orphan GPCRs: current status using structure-based approaches. Br. J. Pharmacol. 173, 2934–2951 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Isberg, V. et al. Computer-aided discovery of aromatic l-α-amino acids as agonists of the orphan G protein-coupled receptor GPR139. J. Chem. Inf. Model. 54, 1553–1557 (2014).

    CAS  PubMed  Google Scholar 

  9. Mason, J.S., Bortolato, A., Congreve, M. & Marshall, F.H. New insights from structural biology into the druggability of G-protein-coupled receptors. Trends Pharmacol. Sci. 33, 249–260 (2012).

    CAS  PubMed  Google Scholar 

  10. Zylka, M.J., Dong, X., Southwell, A.L. & Anderson, D.J. Atypical expansion in mice of the sensory neuron-specific Mrg G-protein-coupled receptor family. Proc. Natl. Acad. Sci. USA 100, 10043–10048 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Dong, X., Han, S., Zylka, M.J., Simon, M.I. & Anderson, D.J. A diverse family of GPCRs expressed in specific subsets of nociceptive sensory neurons. Cell 106, 619–632 (2001).

    CAS  PubMed  Google Scholar 

  12. Lembo, P.M. et al. Proenkephalin A gene products activate a new family of sensory neuron-specific GPCRs. Nat. Neurosci. 5, 201–209 (2002).

    CAS  PubMed  Google Scholar 

  13. Tatemoto, K. et al. Immunoglobulin E-independent activation of mast cell is mediated by Mrg receptors. Biochem. Biophys. Res. Commun. 349, 1322–1328 (2006).

    CAS  PubMed  Google Scholar 

  14. Kamohara, M. et al. Identification of MrgX2 as a human G-protein-coupled receptor for proadrenomedullin N-terminal peptides. Biochem. Biophys. Res. Commun. 330, 1146–1152 (2005).

    CAS  PubMed  Google Scholar 

  15. Subramanian, H. et al. β-Defensins activate human mast cells via Mas-related gene X2. J. Immunol. 191, 345–352 (2013).

    CAS  PubMed  Google Scholar 

  16. Robas, N., Mead, E. & Fidock, M. MrgX2 is a high potency cortistatin receptor expressed in dorsal root ganglion. J. Biol. Chem. 278, 44400–44404 (2003).

    CAS  PubMed  Google Scholar 

  17. Malik, L. et al. Discovery of non-peptidergic MrgX1 and MrgX2 receptor agonists and exploration of an initial SAR using solid-phase synthesis. Bioorg. Med. Chem. Lett. 19, 1729–1732 (2009).

    CAS  PubMed  Google Scholar 

  18. Johnson, T. & Siegel, D. Complanadine A, a selective agonist for the Mas-related G protein-coupled receptor X2. Bioorg. Med. Chem. Lett. 24, 3512–3515 (2014).

    CAS  PubMed  Google Scholar 

  19. McNeil, B.D. et al. Identification of a mast-cell-specific receptor crucial for pseudo-allergic drug reactions. Nature 519, 237–241 (2015).

    CAS  PubMed  Google Scholar 

  20. Southern, C. et al. Screening β-arrestin recruitment for the identification of natural ligands for orphan G-protein-coupled receptors. J. Biomol. Screen. 18, 599–609 (2013).

    PubMed  Google Scholar 

  21. Sromek, A.W. et al. Preliminary pharmacological evaluation of enantiomeric morphinans. ACS Chem. Neurosci. 5, 93–99 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Wang, M.H. et al. Activation of opioid mu-receptor by sinomenine in cell and mice. Neurosci. Lett. 443, 209–212 (2008).

    CAS  PubMed  Google Scholar 

  23. Nagase, H. et al. The pharmacological profile of delta opioid receptor ligands, (+) and (−) TAN-67 on pain modulation. Life Sci. 68, 2227–2231 (2001).

    CAS  PubMed  Google Scholar 

  24. White, K.L. et al. Identification of novel functionally selective κ-opioid receptor scaffolds. Mol. Pharmacol. 85, 83–90 (2014).

    PubMed  PubMed Central  Google Scholar 

  25. Horn, F. et al. GPCRDB: an information system for G-protein-coupled receptors. Nucleic Acids Res. 26, 275–279 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Lin, H., Sassano, M.F., Roth, B.L. & Shoichet, B.K. A pharmacological organization of G protein-coupled receptors. Nat. Methods 10, 140–146 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Irwin, J.J. & Shoichet, B.K. ZINC--a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model. 45, 177–182 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Eswar, N. et al. Comparative protein structure modeling using MODELLER. Curr. Protoc. Protein Sci. 50, 2.9.1–2.9.31 (2007).

    Google Scholar 

  29. Yang, Q. & Sharp, K.A. Building alternate protein structures using the elastic network model. Proteins 74, 682–700 (2009).

    CAS  PubMed  Google Scholar 

  30. Mysinger, M.M. & Shoichet, B.K. Rapid context-dependent ligand desolvation in molecular docking. J. Chem. Inf. Model. 50, 1561–1573 (2010).

    CAS  PubMed  Google Scholar 

  31. Mysinger, M.M. et al. Structure-based ligand discovery for the protein–protein interface of chemokine receptor CXCR4. Proc. Natl. Acad. Sci. USA 109, 5517–5522 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Carlsson, J. et al. Ligand discovery from a dopamine D3 receptor homology model and crystal structure. Nat. Chem. Biol. 7, 769–778 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Jacobson, M.P., Friesner, R.A., Xiang, Z. & Honig, B. On the role of the crystal environment in determining protein side chain conformations. J. Mol. Biol. 320, 597–608 (2002).

    CAS  PubMed  Google Scholar 

  34. 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. 25, 366–428 (1995).

    CAS  Google Scholar 

  35. O'Connor, C. et al. NMR structure and dynamics of the agonist dynorphin peptide bound to the human kappa opioid receptor. Proc. Natl. Acad. Sci. USA 112, 11852–11857 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Irwin, J.J. & Shoichet, B.K. Docking screens for novel ligands conferring new biology. J. Med. Chem. 59, 4103–4120 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Jacquet, Y.F., Klee, W.A., Rice, K.C., Iijima, I. & Minamikawa, J. Stereospecific and nonstereospecific effects of (+)- and (−)-morphine: evidence for a new class of receptors? Science 198, 842–845 (1977).

    CAS  PubMed  Google Scholar 

  38. Baldo, B.A. & Pham, N.H. Histamine-releasing and allergenic properties of opioid analgesic drugs: resolving the two. Anaesth. Intensive Care 40, 216–235 (2012).

    CAS  PubMed  Google Scholar 

  39. Rosow, C.E., Moss, J., Philbin, D.M. & Savarese, J.J. Histamine release during morphine and fentanyl anesthesia. Anesthesiology 56, 93–96 (1982).

    CAS  PubMed  Google Scholar 

  40. Kumar, K. & Singh, S.I. Neuraxial opioid-induced pruritus: an update. J. Anaesthesiol. Clin. Pharmacol. 29, 303–307 (2013).

    PubMed  PubMed Central  Google Scholar 

  41. Hutchinson, M.R. et al. Exploring the neuroimmunopharmacology of opioids: an integrative review of mechanisms of central immune signaling and their implications for opioid analgesia. Pharmacol. Rev. 63, 772–810 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Yamasaki, H. Pharmacology of sinomenine, an anti-rheumatic alkaloid from Sinomenium acutum. Acta Med. Okayama 30, 1–20 (1976).

    CAS  PubMed  Google Scholar 

  43. Zajac, M. et al. [Recreational usage of dextromethorphan—analysis based on internet users experiences]. Przegl. Lek. 70, 525–527 (2013).

    PubMed  Google Scholar 

  44. Scimemi, A. & Beato, M. Determining the neurotransmitter concentration profile at active synapses. Mol. Neurobiol. 40, 289–306 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Podvin, S., Yaksh, T. & Hook, V. The emerging role of spinal dynorphin in chronic pain: a therapeutic perspective. Annu. Rev. Pharmacol. Toxicol. 56, 511–533 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Sweetnam, P.M., Neale, J.H., Barker, J.L. & Goldstein, A. Localization of immunoreactive dynorphin in neurons cultured from spinal cord and dorsal root ganglia. Proc. Natl. Acad. Sci. USA 79, 6742–6746 (1982).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Rojewska, E., Makuch, W., Przewlocka, B. & Mika, J. Minocycline prevents dynorphin-induced neurotoxicity during neuropathic pain in rats. Neuropharmacology 86, 301–310 (2014).

    CAS  PubMed  Google Scholar 

  48. Bienenstock, J. et al. Mast cell/nerve interactions in vitro and in vivo. Am. Rev. Respir. Dis. 143, S55–S58 (1991).

    CAS  PubMed  Google Scholar 

  49. Barelier, S., Sterling, T., O'Meara, M.J. & Shoichet, B.K. The recognition of identical ligands by unrelated proteins. ACS Chem. Biol. 10, 2772–2784 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Akuzawa, N., Obinata, H., Izumi, T. & Takeda, S. Morphine is an exogenous ligand for MrgX2, a G-protein-coupled receptor for cortistatin. J. Cell Animal Biol. 2, 004–009 (2007).

    Google Scholar 

  51. Wu, H.E., Schwasinger, E.T., Terashvili, M. & Tseng, L.F. dextro-Morphine attenuates the morphine-produced conditioned place preference via the sigma(1) receptor activation in the rat. Eur. J. Pharmacol. 562, 221–226 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Kirshenbaum, A.S. et al. Characterization of novel stem cell factor responsive human mast cell lines LAD 1 and 2 established from a patient with mast cell sarcoma/leukemia; activation following aggregation of FcepsilonRI or FcgammaRI. Leuk. Res. 27, 677–682 (2003).

    CAS  PubMed  Google Scholar 

  53. Jordan, M., Schallhorn, A. & Wurm, F.M. Transfecting mammalian cells: optimization of critical parameters affecting calcium-phosphate precipitate formation. Nucleic Acids Res. 24, 596–601 (1996).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Staats, H.F. et al. A mast cell degranulation screening assay for the identification of novel mast cell activating agents. MedChemComm 4, 88–94 (2013).

    CAS  Google Scholar 

  55. Pei, J., Kim, B.H. & Grishin, N.V. PROMALS3D: a tool for multiple protein sequence and structure alignments. Nucleic Acids Res. 36, 2295–2300 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. Jacobson, M.P. Epilepsy in aging populations. Curr. Treat. Options Neurol. 4, 19–30 (2002).

    PubMed  Google Scholar 

  57. Sharp, K.A. Polyelectrolyte electrostatics: salt dependence, entropic, and enthalpic contributions to free energy in the nonlinear Poisson–Boltzmann model. Biopolymers 36, 227–243 (1995).

    CAS  Google Scholar 

  58. Meng, E.C., Shoichet, B.K. & Kuntz, I.D. Automated docking with grid-based energy evaluation. J. Comput. Chem. 13, 505–524 (1992).

    CAS  Google Scholar 

  59. Li, J., Zhu, T., Cramer, C.J. & Truhlar, D.G. New class IV charge model for extracting accurate partial charges from wave functions. J. Phys. Chem. A 102, 1820–1831 (1998).

    CAS  Google Scholar 

  60. Chambers, C.C., Hawkins, G.D., Cramer, C.J. & Truhlar, D.G. Model for aqueous solvation based on class IV atomic charges and first solvation shell effects. J. Phys. Chem. 100, 16385–16398 (1996).

    CAS  Google Scholar 

  61. Paruch, K. et al. Discovery of Dinaciclib (SCH 727965): a potent and selective inhibitor of cyclin-dependent kinases. ACS Med. Chem. Lett. 1, 204–208 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Support was given by National Institutes of Health (NIH) grants U01104974 (B.L.R., B.K.S. and W.K.K.), the NIH Department of Pharmacology Training Grant (K.L.), a Genentech Foundation Pre-doctoral Fellowship (J.K.), and a PhRMA Foundation Predoctoral Fellowship (K.L.). We thank the National Institute on Drug Abuse Drug Supply Program for supplying the morphine and codeine analogs and the glucuronidated or acetylated metabolites used in this study.

Author information

Authors and Affiliations

Authors

Contributions

K.L. performed the in vitro pharmacology and molecular biology and wrote the paper. J.K. designed and developed homology models, carried out docking screens, analyzed results, and wrote the paper. J.L. synthesized the probe enantiomers. X.-P.H. performed GPCRome screening and assisted with in vitro pharmacology experiments. J.D.M. performed binding studies and in vitro pharmacology. W.K.K. assisted in the in vitro small-molecule screening and helped with data and statistical analyses. T.C. performed in vitro pharmacology experiments. H.N. synthesized (+)-TAN-67 and KNT-127. F.I.C. synthesized several compounds and advised structure–activity relationship studies. J.J. supervised chemical synthesis of probe enantiomers. B.L.R. and B.K.S. coordinated and supervised the project, and with the other authors wrote the paper.

Corresponding author

Correspondence to Bryan L Roth.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Results, Supplementary Tables 1–3 and Supplementary Figures 1–12 (PDF 3279 kb)

Supplementary Note

Chemical compound characterization for selective probes (R)-ZINC-3573 and (S)-ZINC-3573 (PDF 348 kb)

Supplementary Data Set 1

PDB file for viewing ZINC-9232 docked in the MRGPRX2 model structure (TXT 207 kb)

Supplementary Data Set 2

PDB file for viewing dextromethorphan docked in the MRGPRX2 model structure (TXT 207 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lansu, K., Karpiak, J., Liu, J. et al. In silico design of novel probes for the atypical opioid receptor MRGPRX2. Nat Chem Biol 13, 529–536 (2017). https://doi.org/10.1038/nchembio.2334

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nchembio.2334

This article is cited by

Search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research