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Structural basis of Smoothened regulation by its extracellular domains

Abstract

Developmental signals of the Hedgehog (Hh) and Wnt families are transduced across the membrane by Frizzled-class G-protein-coupled receptors (GPCRs) composed of both a heptahelical transmembrane domain (TMD) and an extracellular cysteine-rich domain (CRD). How the large extracellular domains of GPCRs regulate signalling by the TMD is unknown. We present crystal structures of the Hh signal transducer and oncoprotein Smoothened, a GPCR that contains two distinct ligand-binding sites: one in its TMD and one in the CRD. The CRD is stacked atop the TMD, separated by an intervening wedge-like linker domain. Structure-guided mutations show that the interface between the CRD, linker domain and TMD stabilizes the inactive state of Smoothened. Unexpectedly, we find a cholesterol molecule bound to Smoothened in the CRD binding site. Mutations predicted to prevent cholesterol binding impair the ability of Smoothened to transmit native Hh signals. Binding of a clinically used antagonist, vismodegib, to the TMD induces a conformational change that is propagated to the CRD, resulting in loss of cholesterol from the CRD–linker domain–TMD interface. Our results clarify the structural mechanism by which the activity of a GPCR is controlled by ligand-regulated interactions between its extracellular and transmembrane domains.

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Figure 1: Structure of human SMO.
Figure 2: The cholesterol binding site.
Figure 3: The cholesterol-binding site regulates SMO signalling activity.
Figure 4: SMO activity is regulated by the stability of its extracellular domain.
Figure 5: Structure of SMO in complex with the antagonist vismodegib.

Accession codes

Primary accessions

Protein Data Bank

Data deposits

Atomic coordinates and structure factors for the apo-SMOΔC and vismo–SMOΔC crystal structures have been deposited in the Protein Data Bank (PDB) under accession numbers 5L7D and 5L7I.

References

  1. 1

    Sharpe, H. J., Wang, W., Hannoush, R. N. & de Sauvage, F. J. Regulation of the oncoprotein Smoothened by small molecules. Nat. Chem. Biol. 11, 246–255 (2015).

    CAS  PubMed  Google Scholar 

  2. 2

    Taipale, J. et al. Effects of oncogenic mutations in Smoothened and Patched can be reversed by cyclopamine. Nature 406, 1005–1009 (2000).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  3. 3

    Chen, J. K., Taipale, J., Cooper, M. K. & Beachy, P. A. Inhibition of Hedgehog signaling by direct binding of cyclopamine to Smoothened. Genes Dev. 16, 2743–2748 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4

    Chen, J. K., Taipale, J., Young, K. E., Maiti, T. & Beachy, P. A. Small molecule modulation of Smoothened activity. Proc. Natl Acad. Sci. USA 99, 14071–14076 (2002).

    ADS  CAS  PubMed  Google Scholar 

  5. 5

    Frank-Kamenetsky, M. et al. Small-molecule modulators of Hedgehog signaling: identification and characterization of Smoothened agonists and antagonists. J. Biol. 1, 10 (2002).

    PubMed  PubMed Central  Google Scholar 

  6. 6

    Robarge, K. D. et al. GDC-0449-a potent inhibitor of the hedgehog pathway. Bioorg. Med. Chem. Lett. 19, 5576–5581 (2009).

    CAS  PubMed  Google Scholar 

  7. 7

    Nachtergaele, S. et al. Oxysterols are allosteric activators of the oncoprotein Smoothened. Nat. Chem. Biol. 8, 211–220 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8

    Corcoran, R. B. & Scott, M. P. Oxysterols stimulate Sonic hedgehog signal transduction and proliferation of medulloblastoma cells. Proc. Natl Acad. Sci. USA 103, 8408–8413 (2006).

    ADS  CAS  PubMed  Google Scholar 

  9. 9

    Dwyer, J. R. et al. Oxysterols are novel activators of the hedgehog signaling pathway in pluripotent mesenchymal cells. J. Biol. Chem. 282, 8959–8968 (2007).

    CAS  PubMed  Google Scholar 

  10. 10

    Nachtergaele, S. et al. Structure and function of the Smoothened extracellular domain in vertebrate Hedgehog signaling. eLife 2, e01340 (2013).

    PubMed  PubMed Central  Google Scholar 

  11. 11

    Nedelcu, D., Liu, J., Xu, Y., Jao, C. & Salic, A. Oxysterol binding to the extracellular domain of Smoothened in Hedgehog signaling. Nat. Chem. Biol. 9, 557–564 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12

    Myers, B. R. et al. Hedgehog pathway modulation by multiple lipid binding sites on the smoothened effector of signal response. Dev. Cell 26, 346–357 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13

    Briscoe, J. & Thérond, P. P. The mechanisms of Hedgehog signalling and its roles in development and disease. Nat. Rev. Mol. Cell Biol. 14, 416–429 (2013).

    PubMed  Google Scholar 

  14. 14

    Yauch, R. L. et al. Smoothened mutation confers resistance to a Hedgehog pathway inhibitor in medulloblastoma. Science 326, 572–574 (2009).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  15. 15

    Wang, C. et al. Structure of the human smoothened receptor bound to an antitumour agent. Nature 497, 338–343 (2013).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  16. 16

    Wang, C. et al. Structural basis for Smoothened receptor modulation and chemoresistance to anticancer drugs. Nat. Commun. 5, 4355 (2014).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  17. 17

    Weierstall, U. et al. Lipidic cubic phase injector facilitates membrane protein serial femtosecond crystallography. Nat. Commun. 5, 3309 (2014).

    ADS  PubMed  PubMed Central  Google Scholar 

  18. 18

    Deupi, X. & Standfuss, J. Structural insights into agonist-induced activation of G-protein-coupled receptors. Curr. Opin. Struct. Biol. 21, 541–551 (2011).

    CAS  PubMed  Google Scholar 

  19. 19

    Katritch, V., Cherezov, V. & Stevens, R. C. Structure-function of the G protein-coupled receptor superfamily. Annu. Rev. Pharmacol. Toxicol. 53, 531–556 (2013).

    CAS  PubMed  Google Scholar 

  20. 20

    Rana, R. et al. Structural insights into the role of the Smoothened cysteine-rich domain in Hedgehog signalling. Nat. Commun. 4, 2965 (2013).

    ADS  PubMed  PubMed Central  Google Scholar 

  21. 21

    Chun, E. et al. Fusion partner toolchest for the stabilization and crystallization of G protein-coupled receptors. Structure 20, 967–976 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22

    Bazan, J. F. & de Sauvage, F. J. Structural ties between cholesterol transport and morphogen signaling. Cell 138, 1055–1056 (2009).

    CAS  PubMed  Google Scholar 

  23. 23

    Janda, C. Y., Waghray, D., Levin, A. M., Thomas, C. & Garcia, K. C. Structural basis of Wnt recognition by Frizzled. Science 337, 59–64 (2012).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  24. 24

    Cooper, M. K. et al. A defective response to Hedgehog signaling in disorders of cholesterol biosynthesis. Nat. Genet. 33, 508–513 (2003).

    CAS  PubMed  Google Scholar 

  25. 25

    Blassberg, R., Macrae, J. I., Briscoe, J. & Jacob, J. Reduced cholesterol levels impair Smoothened activation in Smith-Lemli-Opitz syndrome. Hum. Mol. Genet. 25, 693–705 (2016).

    CAS  PubMed  Google Scholar 

  26. 26

    Venkatakrishnan, A. J. et al. Molecular signatures of G-protein-coupled receptors. Nature 494, 185–194 (2013).

    ADS  CAS  Google Scholar 

  27. 27

    Durand, D. et al. NADPH oxidase activator p67(phox) behaves in solution as a multidomain protein with semi-flexible linkers. J. Struct. Biol. 169, 45–53 (2010).

    CAS  PubMed  Google Scholar 

  28. 28

    Rambo, R. P. & Tainer, J. A. Characterizing flexible and intrinsically unstructured biological macromolecules by SAS using the Porod-Debye law. Biopolymers 95, 559–571 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. 29

    Sharpe, H. J. et al. Genomic analysis of smoothened inhibitor resistance in basal cell carcinoma. Cancer Cell 27, 327–341 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  30. 30

    Atwood, S. X. et al. Smoothened variants explain the majority of drug resistance in basal cell carcinoma. Cancer Cell 27, 342–353 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31

    Varjosalo, M., Li, S. P. & Taipale, J. Divergence of hedgehog signal transduction mechanism between Drosophila and mammals. Dev. Cell 10, 177–186 (2006).

    CAS  PubMed  Google Scholar 

  32. 32

    Rohatgi, R., Milenkovic, L. & Scott, M. P. Patched1 regulates hedgehog signaling at the primary cilium. Science 317, 372–376 (2007).

    ADS  CAS  PubMed  Google Scholar 

  33. 33

    Humke, E. W., Dorn, K. V., Milenkovic, L., Scott, M. P. & Rohatgi, R. The output of Hedgehog signaling is controlled by the dynamic association between Suppressor of Fused and the Gli proteins. Genes Dev. 24, 670–682 (2010). 10.1101/gad.1902910

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. 34

    Aricescu, A. R., Lu, W. & Jones, E. Y. A time- and cost-efficient system for high-level protein production in mammalian cells. Acta Crystallogr. D Biol. Crystallogr. 62, 1243–1250 (2006).

    Google Scholar 

  35. 35

    Molday, R. S. & MacKenzie, D. Monoclonal antibodies to rhodopsin: characterization, cross-reactivity, and application as structural probes. Biochemistry 22, 653–660 (1983).

    CAS  PubMed  Google Scholar 

  36. 36

    Oprian, D. D., Molday, R. S., Kaufman, R. J. & Khorana, H. G. Expression of a synthetic bovine rhodopsin gene in monkey kidney cells. Proc. Natl Acad. Sci. USA 84, 8874–8878 (1987).

    ADS  CAS  PubMed  Google Scholar 

  37. 37

    Zacharias, D. A., Violin, J. D., Newton, A. C. & Tsien, R. Y. Partitioning of lipid-modified monomeric GFPs into membrane microdomains of live cells. Science 296, 913–916 (2002).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  38. 38

    Nagai, T. et al. A variant of yellow fluorescent protein with fast and efficient maturation for cell-biological applications. Nat. Biotechnol. 20, 87–90 (2002).

    CAS  PubMed  Google Scholar 

  39. 39

    Rohatgi, R., Milenkovic, L., Corcoran, R. B. & Scott, M. P. Hedgehog signal transduction by Smoothened: pharmacologic evidence for a 2-step activation process. Proc. Natl Acad. Sci. USA 106, 3196–3201 (2009).

    ADS  CAS  PubMed  Google Scholar 

  40. 40

    Miller, P. S. & Aricescu, A. R. Crystal structure of a human GABAA receptor. Nature 512, 270–275 (2014).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  41. 41

    Kawate, T. & Gouaux, E. Fluorescence-detection size-exclusion chromatography for precrystallization screening of integral membrane proteins. Structure 14, 673–681 (2006).

    CAS  PubMed  Google Scholar 

  42. 42

    Bailey, E. C., Milenkovic, L., Scott, M. P., Collawn, J. F. & Johnson, R. L. Several PATCHED1 missense mutations display activity in patched1-deficient fibroblasts. J. Biol. Chem. 277, 33632–33640 (2002).

    CAS  PubMed  Google Scholar 

  43. 43

    Pear, W. S., Nolan, G. P., Scott, M. L. & Baltimore, D. Production of high-titer helper-free retroviruses by transient transfection. Proc. Natl Acad. Sci. USA 90, 8392–8396 (1993).

    ADS  CAS  PubMed  Google Scholar 

  44. 44

    Ciepla, P. et al. New chemical probes targeting cholesterylation of Sonic Hedgehog in human cells and zebrafish. Chem. Sci. (Camb.) 5, 4249–4259 (2014).

    CAS  Google Scholar 

  45. 45

    Chung, S.-K., Shim, J.-Y., Kang, M. G., Lee, K. W. & Kang, H. I. Studies of steroids as potential antifungal agent 2. Side chain modified cholesterols. Korean J. Med. Chem. 8, 14–17 (1998).

    CAS  Google Scholar 

  46. 46

    Caffrey, M. & Cherezov, V. Crystallizing membrane proteins using lipidic mesophases. Nat. Protocols 4, 706–731 (2009).

    CAS  PubMed  Google Scholar 

  47. 47

    Winter, G. xia2: an expert system for macromolecular crystallography data reduction. J. Appl. Crystallogr. 43, 186–190 (2010).

    CAS  Google Scholar 

  48. 48

    Kabsch, W. Xds. Acta Crystallogr. D 66, 125–132 (2010).

    CAS  Google Scholar 

  49. 49

    Evans, P. R. & Murshudov, G. N. How good are my data and what is the resolution? Acta Crystallogr. D 69, 1204–1214 (2013).

    CAS  Google Scholar 

  50. 50

    Winn, M. D. et al. Overview of the CCP4 suite and current developments. Acta Crystallogr. D 67, 235–242 (2011).

    CAS  Google Scholar 

  51. 51

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

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52

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

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  53. 53

    Cowtan, K. Recent developments in classical density modification. Acta Crystallogr. D Biol. Crystallogr. 66, 470–478 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54

    Cowtan, K. The Buccaneer software for automated model building. 1. Tracing protein chains. Acta Crystallogr. D 62, 1002–1011 (2006).

    PubMed  Google Scholar 

  55. 55

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

    Google Scholar 

  56. 56

    BUSTER v. 2.10.2 (Global Phasing Ltd., Cambridge, United Kingdom, 2011).

  57. 57

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

    CAS  Google Scholar 

  58. 58

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

    CAS  Google Scholar 

  59. 59

    Baker, N. A., Sept, D., Joseph, S., Holst, M. J. & McCammon, J. A. Electrostatics of nanosystems: application to microtubules and the ribosome. Proc. Natl Acad. Sci. USA 98, 10037–10041 (2001).

    ADS  CAS  Google Scholar 

  60. 60

    Eisenberg, D., Schwarz, E., Komaromy, M. & Wall, R. Analysis of membrane and surface protein sequences with the hydrophobic moment plot. J. Mol. Biol. 179, 125–142 (1984).

    CAS  PubMed  Google Scholar 

  61. 61

    Schrodinger, L.L.C. The PyMOL Molecular Graphics System, Version 1.3r1 (2010).

    Google Scholar 

  62. 62

    Krissinel, E. & Henrick, K. Inference of macromolecular assemblies from crystalline state. J. Mol. Biol. 372, 774–797 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63

    Corpet, F. Multiple sequence alignment with hierarchical clustering. Nucleic Acids Res. 16, 10881–10890 (1988).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64

    Robert, X. & Gouet, P. Deciphering key features in protein structures with the new ENDscript server. Nucleic Acids Res. 42, W320–W324 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65

    Chovancova, E. et al. CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures. PLOS Comput. Biol. 8, e1002708 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. 66

    Tribet, C., Audebert, R. & Popot, J. L. Amphipols: polymers that keep membrane proteins soluble in aqueous solutions. Proc. Natl Acad. Sci. USA 93, 15047–15050 (1996).

    ADS  CAS  PubMed  Google Scholar 

  67. 67

    Gohon, Y. et al. Bacteriorhodopsin/amphipol complexes: structural and functional properties. Biophys. J. 94, 3523–3537 (2008).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  68. 68

    Hess, B., Kutzner, C., van der Spoel, D. & Lindahl, E. GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. J. Chem. Theory Comput. 4, 435–447 (2008).

    CAS  Google Scholar 

  69. 69

    Olsson, M. H. M., Søndergaard, C. R., Rostkowski, M. & Jensen, J. H. PROPKA3: consistent treatment of internal and surface residues in empirical pKa predictions. J. Chem. Theory Comput. 7, 525–537 (2011).

    CAS  PubMed  Google Scholar 

  70. 70

    Søndergaard, C. R., Olsson, M. H. M., Rostkowski, M. & Jensen, J. H. Improved treatment of ligands and coupling effects in empirical calculation and rationalization of pKa values. J. Chem. Theory Comput. 7, 2284–2295 (2011).

    PubMed  Google Scholar 

  71. 71

    de Jong, D. H. et al. Improved parameters for the martini coarse-grained protein force field. J. Chem. Theory Comput. 9, 687–697 (2013).

    CAS  PubMed  Google Scholar 

  72. 72

    Scott, K. A. et al. Coarse-grained MD simulations of membrane protein-bilayer self-assembly. Structure 16, 621–630 (2008).

    CAS  PubMed  Google Scholar 

  73. 73

    Stansfeld, P. J. et al. MemProtMD: automated insertion of membrane protein structures into explicit lipid membranes. Structure 23, 1350–1361 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. 74

    Stansfeld, P. J. & Sansom, M. S. Molecular simulation approaches to membrane proteins. Structure 19, 1562–1572 (2011).

    CAS  PubMed  Google Scholar 

  75. 75

    Marrink, S. J., Risselada, H. J., Yefimov, S., Tieleman, D. P. & de Vries, A. H. The MARTINI force field: coarse grained model for biomolecular simulations. J. Phys. Chem. B 111, 7812–7824 (2007).

    CAS  PubMed  Google Scholar 

  76. 76

    Monticelli, L., Sorin, E. J., Tieleman, D. P., Pande, V. S. & Colombo, G. Molecular simulation of multistate peptide dynamics: a comparison between microsecond timescale sampling and multiple shorter trajectories. J. Comput. Chem. 29, 1740–1752 (2008).

    CAS  PubMed  Google Scholar 

  77. 77

    Periole, X., Cavalli, M., Marrink, S. J. & Ceruso, M. A. Combining an elastic network with a coarse-grained molecular force field: structure, dynamics, and intermolecular recognition. J. Chem. Theory Comput. 5, 2531–2543 (2009).

    CAS  PubMed  Google Scholar 

  78. 78

    Berendsen, H. J. C., Postma, J. P. M., Vangunsteren, W. F., Dinola, A. & Haak, J. R. Molecular-dynamics with coupling to an external bath. J. Chem. Phys. 81, 3684–3690 (1984).

    ADS  CAS  Google Scholar 

  79. 79

    Hess, B., Bekker, H., Berendsen, H. J. C. & Fraaije, J. G. E. M. LINCS: A linear constraint solver for molecular simulations. J. Comput. Chem. 18, 1463–1472 (1997).

    CAS  Google Scholar 

  80. 80

    Oostenbrink, C., Villa, A., Mark, A. E. & van Gunsteren, W. F. A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J. Comput. Chem. 25, 1656–1676 (2004).

    CAS  PubMed  Google Scholar 

  81. 81

    Pol-Fachin, L., Verli, H. & Lins, R. D. Extension and validation of the GROMOS 53A6(GLYC) parameter set for glycoproteins. J. Comput. Chem. 35, 2087–2095 (2014).

    CAS  PubMed  Google Scholar 

  82. 82

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

    ADS  PubMed  PubMed Central  Google Scholar 

  83. 83

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

    ADS  CAS  Google Scholar 

  84. 84

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

    ADS  CAS  Google Scholar 

  85. 85

    Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996).

    CAS  Google Scholar 

  86. 86

    Karplus, P. A. & Diederichs, K. Linking crystallographic model and data quality. Science 336, 1030–1033 (2012).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  87. 87

    Zoonens, M. & Popot, J. L. Amphipols for each season. J. Membr. Biol. 247, 759–796 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank the staff of beamlines I24 and B21 (MX10627) at the DLS, UK for assistance. We thank S. Masiulis, D. Staunton, K. Jungnickel, A. R. Aricescu and G. Schertler for discussions. The work was supported by Cancer Research UK (C20724/A14414), the US National Institutes of Health (GM106078, HL067773), the Wellcome Trust (102890/Z/13/Z, 092970/Z/10/Z and 090532/Z/09/Z), and the Taylor Family Institute for Psychiatric Research. Further support by NDM Oxford (E.F.X.B.), Medical Research Council UK (G.H.), Ford Foundation (G.L.) and National Science Foundation (S.Na.) is acknowledged.

Author information

Affiliations

Authors

Contributions

E.F.X.B. produced the protein with P.S.M, and carried out crystallization with S.Ne. C.S. and E.F.X.B. determined the crystal structures. R.S., S.Na., and G.L. performed Hh signalling and biochemical assays. L.M.-M. and D.F.C. synthesized sterol analogues. G.H. and M.S.P.S performed MD analysis. M.D.T and R.P.R. carried out SAXS analysis. C.S. and R.R. supervised the project. E.F.X.B., R.R. and C.S. wrote the paper, with input from all authors.

Corresponding authors

Correspondence to Rajat Rohatgi or Christian Siebold.

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Competing interests

The authors declare no competing financial interests.

Additional information

Reviewer Information Nature thanks J. Briscoe, R. Dror, F. de Sauvage and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Figure 1 Sequence alignment of SMO orthologues.

Numbering corresponds to that of human SMO. Secondary structure assignments are displayed above the alignment and colour-coded as in Fig. 1. Black arrows and numbers (fX.50) below alignment show class F Ballesteros–Weinstein nomenclature for GPCR helices16. Residues interacting with cholesterol are highlighted in red. Disulfide bridges are highlighted in yellow and numbered. N-linked glycosylation sites are depicted by a hexagon. The position of the Val329Phe point mutation is highlighted in purple.

Extended Data Figure 2 Characterization of the SMO Val329Phe mutation.

a, Superposition of SMOΔC structure (blue) with the SMO-SANT-1 complex structure, which lacks the CRD (green, PDB 4N4W (ref. 16)), showing the TMD ligand-binding pocket as a yellow surface. Inset shows Val329, mutated to Phe in our structure. b, SEC analysis of fluorescently labelled SMOΔC showing difference in expression levels of wild-type and Val329Phe variant (main protein peak ~20 min). c, 20(S)-OHC beads can bind both mouse wild-type SMO and Val333Phe (mouse Val333 corresponds to human Val329). Immunoblots, using an anti-SMO antibody directed against the ICD, were used to measure SMO captured on 20(S)-OHC beads. Adding 50 μM free 20(S)-OHC as a competitor reduced binding. d, Purified human SMOΔC (the crystallization construct) binds to 20(S)-OHC beads. e, Smo−/− mouse fibroblasts stably expressing SMO-WT or SMO-Val333Phe were exposed to SHH, SAG or 20(S)-OHC. Levels of endogenous Gli1 mRNA (mean arbitrary units ± s.d., n = 4), measured by qRT–PCR, were used as a metric of Hh pathway activity because Gli1 is a direct Hh target. Asterisks indicate statistical significance (****P ≤ 0.0001) based on one-way ANOVA for the difference in Gli1 mRNA levels between identically treated SMO-WT and SMO-Val333Phe cells. f, Immunoblot shows SMO and GLI1 protein levels in these stable cell lines, with p38 as loading control. Each experiment was replicated ≥2 times with similar results.

Extended Data Figure 3 Crystallization, structure solution and oligomeric state of SMOΔC.

a, SMOΔC crystal packing. Asymmetric unit consists of two antiparallel SMOΔC chains. Chain A coloured as in Fig. 1 with BRIL fusion in yellow; Chain B in grey. LCP crystal packing with alternating hydrophobic and hydrophilic layers perpendicular to the c axis. Molecules coloured as for Chain A. b, Pearson correlation coefficient (CC) analysis86 used to relate data quality with model quality. A CCwork and CCfree smaller than CC* indicates that the model does not account for all of the signal in the data (and is therefore not overfit). ce, SigmaA-weighted 2FoFc electron density maps of final refinement at 1.0σ contour level. c, Val329Phe mutation. d, Extra density within TMD ligand-binding pocket (FoFc maps shown at contour level of +3σ (green) and –3σ (red)) (This density could not be confidently assigned, probably because of low occupancy within the crystal.). e, ‘Connector’ region linking the CRD and linker domain, with Asn188 and linked N-acetyl glycosamine moiety. f, SEC–MALS analysis of amphipol-solubilized SMOΔC. Molar masses (MW, black lines) and 280 nm absorption (grey line) plotted against elution time. MW derived from protein-conjugate analysis indicated in parentheses. For clarity, graphs of MW are shown only around main absorption peak. Theoretical MW of SMOΔC based on sequence is 71 kDa with the extra mass observed in MALS (~13 kDa) probably due to three N-linked glycosylation sites. Expected mass of protein-bound amphipol (A8–35) was previously determined to be 40–75 kDa (ref. 87), in agreement with our data. This analysis suggests that SMOΔC is a monomer under our purification conditions.

Extended Data Figure 4 Interfaces of the SMO CRD.

a, b, Detailed interactions of the CRD with the connector region (a) and with the linker domain–TMD segment (b). The number of interactions are indicated in the top panel and coloured as indicated in the key box. For non-bonded contacts, the width of the striped line is proportional to the number of atomic contacts. Residue colouring is according to amino acid: blue, positive (H,K,R); red, negative (D,E); green, neutral (S,T,N,Q); grey, aliphatic (A,V,L,I,M); purple, aromatic (F,Y,W); orange, proline (P) or glycine (G); yellow, cysteine (C). The figure is adopted from the PDBSUM server (http://www.ebi.ac.uk/pdbsum/).

Extended Data Figure 5 Comparison of SMOΔC with previously determined SMO TMD structures.

Superposition of the SMOΔC structure with SMO TMD structures. Structural alignment was performed using the 7TM bundle as template (not including the linker domain or TMD helix 8). SMOΔC (red), SMO TMD complexed with cyclopamine (light orange, PDB 4O9R, r.m.s.d. 0.598 Å for 243 equivalent Cα positions), antaXV (light blue, PDB 4QIM, r.m.s.d. 0.515 Å for 233 equivalent Cα positions), SANT1 (pale cyan, PDB 4N4W, r.m.s.d. 0.483 Å for 240 equivalent Cα positions), LY2940680 (pale green, PDB 4JKV, r.m.s.d. 0.493 Å for 230 equivalent Cα positions), SAG1.5 (pale yellow, PDB 4QIN, r.m.s.d. 0.623 Å for 262 equivalent Cα positions). The box shows a close-up view of the linker domain region revealing a structural rearrangement in the SMOΔC structure compared to the previously determined SMO TMD structures lacking the native extracellular domain.

Extended Data Figure 6 Cholesterol stabilizes SMO.

ae, MD simulations of SMO in a lipid bilayer. a, SMO embedded in a lipid bilayer with the CRD in orange, the seven-pass transmembrane region excluding intra- and extracellular loops (7TM) in blue and cholesterol in cyan. bd, Relative r.m.s. fluctuations of the Cα atoms over the course of 5 × 100 ns of atomistic MD simulation in the presence and absence of cholesterol. The structures in b and c are shown as putty representations coloured from high conformational stability (that is, low r.m.s. fluctuations; blue/thin) to low stability (that is, high r.m.s. fluctuations; red/thick). e, Secondary structure DSSP matrices for each of the simulations. The asterisks in b, c and e all mark the helix spanning residues 155–160, which is destabilized in the absence of bound cholesterol. f, g, Thermostability of purified SMOΔC. See Supplementary Discussion for details. f, Compiled peak heights from thermostability SEC analysis of purified SMOΔC after treatment with different MBCD concentrations. g, Example of raw SEC data used for the analysis in f. Samples were incubated at 35 °C for 1 h before loading onto the SEC column.

Extended Data Figure 7 Effect of domain interface mutations on expression levels and 20(S)-OHC binding.

a, Protein levels of SMO and also of PTCH1 and GLI1 (each of which is encoded by a direct Hh target gene) measured by immunoblot from Smo−/− mouse fibroblasts stably expressing one of five SMO variants: wild-type SMO (WT); SMO lacking the entire CRD (ΔCRD); SMO with two mutations (Pro120Ser or Ile160Asn/Glu162Thr) that introduce glycosylation sites in the linker domain–CRD interface; and SMO lacking a conserved disulfide bond (Cys197Ser/Cys217Ser, marked 6 in Fig. 4c) in the linker domain. Elevated levels of GLI1 and PTCH1 reflect high constitutive signalling activity of each mutant. NS, a non-specific band detected by anti-PTCH1 antibody; SUFU, loading control. Different patterns seen in SMO panel are caused by different numbers of N-linked glycosylation sites. b, Gli1 mRNA levels (mean arbitrary units ± s.d., n = 3) were used to assess Hh signalling activity in Smo−/− cells stably expressing the indicated mouse SMO variants. One-way ANOVA was used to assess statistical significance (****P ≤ 0.0001). D477R and M2 (Trp539Leu) are two previously described mutations in the TMD that increase constitutive signalling. c, Oxysterol-binding capacity of each SMO variant was determined (right blot) by its ability to bind to 20(S)-OHC beads in the absence or presence of 50 μM free 20(S)-OHC. Inputs for each binding reaction are shown on the left. Each experiment was repeated 2 or more times with similar results.

Extended Data Figure 8 SAXS analysis of SMOΔC.

a, Overlay of size-exclusion chromatograms monitored at 280 nm (A280) collected during SAXS measurements for apo-SMOΔC (red), (+)20(S)-OHC SMOΔC (blue), amphipol (green) and BSA standard (black). Amphipol and BSA were injected at 10 mg ml−1. Inset shows curves normalized to peak height. BSA was used as a reference with a radius-of-hydration of 3.7 nm. Absorbance of the free amphipol is negligible and elutes ~5 min after the amphipol-stabilized SMOΔC samples. b, Dimensionless Kratky plot of apo- and (+)20(S)-OHC-loaded SMOΔC SAXS data. Cross-hairs denote the Guinier–Kratky point (√3, 1.1), the peak position for an ideal, globular particle. The slower decay of the transformed scattering intensities for (+)20(S)-OHC (blue) indicate a comparably less spherical particle.

Extended Data Figure 9 Crystal structure of the SMOΔC–vismodegib complex and structural analysis of mutations found in vismodegib-resistant cancers.

a, Chemical structure of vismodegib. b, Close-up view of vismodegib-binding site. Colour-coding follows Fig. 5b. Composite omit map calculated with PHENIX at 1.0σ shown as magenta chicken-wire. c, Mapping of residues that are mutated in vismodegib-resistant tumours (yellow highlights). Brackets indicate mutant residues. df, Close-up views of selected interactions. Native residues in blue and mutated residues in yellow. Arrows indicate position of potential clashes that could disrupt vismodegib binding. d, Gln477/Asp473 hot spot. The Gln477Glu mutation leads to a loss of the potential hydrogen bond of the glutamine sidechain to the chloride of the vismodegib chlorophenyl-methylsulfone moiety. The Asp473His mutation potentially destabilizes the hydrogen-bonding network around Arg400 that coordinates the vismodegib chlorophenyl-methylsulfone moiety. e, The imidazole ring of His231 is within hydrogen-bonding distance of two carbonyl main-chain atoms of residues Ser385 and Val386 located on a loop coordinating the interaction of Asp384 with vismodegib’s amide linker. f, Trp281 forms a key hydrophobic interaction with the vismodegib pyrimidine ring that is deeply buried in the SMO helical bundle core. Mutation to cysteine would significantly destabilize this interaction while mutation of nearby Val321 to the bulkier methionine would probably result in a rearrangement of the Trp281 side chain. g, h, SMOΔC captured on cholesterol beads in the presence of increasing concentrations of free vismodegib or 20(S)-OHC (h). Results from one of two independent pull-down experiments are shown.

Extended Data Table 1 Crystallographic data collection and refinement statistics

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Byrne, E., Sircar, R., Miller, P. et al. Structural basis of Smoothened regulation by its extracellular domains. Nature 535, 517–522 (2016). https://doi.org/10.1038/nature18934

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