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:

Structural basis of TRPV5 channel inhibition by econazole revealed by cryo-EM

Nature Structural & Molecular Biology volume 25, pages 53–60 (2018)Cite this article

Subjects

Abstract

The transient receptor potential vanilloid 5 (TRPV5) channel is a member of the transient receptor potential (TRP) channel family, which is highly selective for Ca2+, that is present primarily at the apical membrane of distal tubule epithelial cells in the kidney and plays a key role in Ca2+ reabsorption. Here we present the structure of the full-length rabbit TRPV5 channel as determined using cryo-EM in complex with its inhibitor econazole. This structure reveals that econazole resides in a hydrophobic pocket analogous to that occupied by phosphatidylinositides and vanilloids in TRPV1, thus suggesting conserved mechanisms for ligand recognition and lipid binding among TRPV channels. The econazole-bound TRPV5 structure adopts a closed conformation with a distinct lower gate that occludes Ca2+ permeation through the channel. Structural comparisons between TRPV5 and other TRPV channels, complemented with molecular dynamics (MD) simulations of the econazole-bound TRPV5 structure, allowed us to gain mechanistic insight into TRPV5 channel inhibition by small molecules.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Econazole-bound TRPV5 (TRPV5ECN) structure as determined by cryo-EM.
Fig. 2: Econazole inhibition of TRPV5.
Fig. 3: Ion pore of TRPV5ECN.
Fig. 4: Pore comparison of select Ca2+-selective ion channels.
Fig. 5: Structural comparison of TRPV5ECN to TRPV6*.
Fig. 6: Schematic representation of the proposed TRPV5 inhibition mechanism by econazole.

Similar content being viewed by others

References

  1. Scales, C. D., Smith, A. C., Hanley, J. M., Saigal, C. S. & Urologic Diseases in America Project. Prevalence of kidney stones in the United States. Eur. Urol. 62, 160–165 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Nie, M. et al. Mucin-1 increases renal TRPV5 activity in vitro, and urinary level associates with calcium nephrolithiasis in patients. J. Am. Soc. Nephrol. 27, 3447–3458 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Na, T. & Peng, J. B. TRPV5: a Ca(2+) channel for the fine-tuning of Ca(2+) reabsorption. Handb. Exp. Pharmacol. 222, 321–357 (2014).

    Article  CAS  PubMed  Google Scholar 

  4. Renkema, K. Y. et al. Hypervitaminosis D mediates compensatory Ca2+ hyperabsorption in TRPV5 knockout mice. J. Am. Soc. Nephrol. 16, 3188–3195 (2005).

    Article  CAS  PubMed  Google Scholar 

  5. Venkatachalam, K. & Montell, C. TRP channels. Annu. Rev. Biochem. 76, 387–417 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Hoenderop, J. G. et al. Function and expression of the epithelial Ca(2+) channel family: comparison of mammalian ECaC1 and 2. J. Physiol. (Lond.) 537, 747–761 (2001).

    Article  CAS  Google Scholar 

  7. van der Wijst, J. et al. A gate hinge controls the epithelial calcium channel TRPV5. Sci. Rep. 7, 45489 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  8. van Goor, M. K. C., Hoenderop, J. G. J. & van der Wijst, J. TRP channels in calcium homeostasis: from hormonal control to structure-function relationship of TRPV5 and TRPV6. Biochim. Biophys. Acta 1864, 883–893 (2017).

    Article  PubMed  Google Scholar 

  9. Nilius, B. et al. Pharmacological modulation of monovalent cation currents through the epithelial Ca2+ channel ECaC1. Br. J. Pharmacol. 134, 453–462 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Fecher-Trost, C., Wissenbach, U. & Weissgerber, P. TRPV6: from identification to function. Cell Calcium 67, 116–122 (2017).

    Article  CAS  PubMed  Google Scholar 

  11. Huynh, K. W. et al. Structure of the full-length TRPV2 channel by cryo-EM. Nat. Commun. 7, 11130 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Liao, M., Cao, E., Julius, D. & Cheng, Y. Structure of the TRPV1 ion channel determined by electron cryo-microscopy. Nature 504, 107–112 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Zubcevic, L. et al. Cryo-electron microscopy structure of the TRPV2 ion channel. Nat. Struct. Mol. Biol. 23, 180–186 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Paulsen, C. E., Armache, J. P., Gao, Y., Cheng, Y. & Julius, D. Structure of the TRPA1 ion channel suggests regulatory mechanisms. Nature 520, 511–517 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Grieben, M. et al. Structure of the polycystic kidney disease TRP channel Polycystin-2 (PC2). Nat. Struct. Mol. Biol. 24, 114–122 (2017).

    Article  CAS  PubMed  Google Scholar 

  16. Wilkes, M. et al. Molecular insights into lipid-assisted Ca2+ regulation of the TRP channel Polycystin-2. Nat. Struct. Mol. Biol. 24, 123–130 (2017).

    Article  CAS  PubMed  Google Scholar 

  17. Shen, P. S. et al. The structure of the polycystic kidney disease channel PKD2 in lipid nanodiscs. Cell 167, 763–773 (2016). e11.

    Article  CAS  PubMed  Google Scholar 

  18. Li, M. et al. Structural basis of dual Ca2+/pH regulation of the endolysosomal TRPML1 channel. Nat. Struct. Mol. Biol. 24, 205–213 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Saotome, K., Singh, A. K., Yelshanskaya, M. V. & Sobolevsky, A. I. Crystal structure of the epithelial calcium channel TRPV6. Nature 534, 506–511 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Singh, A. K., Saotome, K. & Sobolevsky, A. I. Swapping of transmembrane domains in the epithelial calcium channel TRPV6. Sci. Rep. 7, 10669 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Catterall, W. A. Ion channel voltage sensors: structure, function, and pathophysiology. Neuron 67, 915–928 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Huynh, K. W. et al. Structural insight into the assembly of TRPV channels. Structure 22, 260–268 (2014).

    Article  CAS  PubMed  Google Scholar 

  23. Cvetkov, T. L., Huynh, K. W., Cohen, M. R. & Moiseenkova-Bell, V. Y. Molecular architecture and subunit organization of TRPA1 ion channel revealed by electron microscopy. J. Biol. Chem. 286, 38168–38176 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Moiseenkova-Bell, V. Y., Stanciu, L. A., Serysheva, I. I., Tobe, B. J. & Wensel, T. G. Structure of TRPV1 channel revealed by electron cryomicroscopy. Proc. Natl. Acad. Sci. USA 105, 7451–7455 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Scheres, S. H. Processing of structurally heterogeneous cryo-EM data in RELION. Methods Enzymol. 579, 125–157 (2016).

    Article  CAS  PubMed  Google Scholar 

  26. Scheres, S. H. W. RELION: implementation of a Bayesian approach to cryo-EM structure determination. J. Struct. Biol. 180, 519–530 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Cao, E., Liao, M., Cheng, Y. & Julius, D. TRPV1 structures in distinct conformations reveal activation mechanisms. Nature 504, 113–118 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Gao, Y., Cao, E., Julius, D. & Cheng, Y. TRPV1 structures in nanodiscs reveal mechanisms of ligand and lipid action. Nature 534, 347–351 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Phelps, C. B., Huang, R. J., Lishko, P. V., Wang, R. R. & Gaudet, R. Structural analyses of the ankyrin repeat domain of TRPV6 and related TRPV ion channels. Biochemistry 47, 2476–2484 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Landowski, C. P., Bolanz, K. A., Suzuki, Y. & Hediger, M. A. Chemical inhibitors of the calcium entry channel TRPV6. Pharm. Res. 28, 322–330 (2011).

    Article  CAS  PubMed  Google Scholar 

  31. Yang, F., Vu, S., Yarov-Yarovoy, V. & Zheng, J. Rational design and validation of a vanilloid-sensitive TRPV2 ion channel. Proc. Natl. Acad. Sci. USA 113, E3657–E3666 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Zhang, F. et al. Engineering vanilloid-sensitivity into the rat TRPV2 channel. eLife 5, e16409 (2016).

    PubMed  PubMed Central  Google Scholar 

  33. Feng, Z. et al. Structural insight into tetrameric hTRPV1 from homology modeling, molecular docking, molecular dynamics simulation, virtual screening, and bioassay validations. J. Chem. Inf. Model. 55, 572–588 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Tang, L. et al. Structural basis for Ca2+ selectivity of a voltage-gated calcium channel. Nature 505, 56–61 (2014).

    Article  PubMed  Google Scholar 

  35. Catterall, W. A., Wisedchaisri, G. & Zheng, N. The chemical basis for electrical signaling. Nat. Chem. Biol. 13, 455–463 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wu, J. et al. Structure of the voltage-gated calcium channel Cav1.1 at 3.6 Å resolution. Nature 537, 191–196 (2016).

    Article  CAS  PubMed  Google Scholar 

  37. Velisetty, P. et al. A molecular determinant of phosphoinositide affinity in mammalian TRPV channels. Sci. Rep. 6, 27652 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Potter, C. S. et al. Leginon: a system for fully automated acquisition of 1000 electron micrographs a day. Ultramicroscopy 77, 153–161 (1999).

    Article  CAS  PubMed  Google Scholar 

  39. Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017).

    Article  CAS  PubMed  Google Scholar 

  40. Zhang, K. Gctf: Real-time CTF determination and correction. J. Struct. Biol. 193, 1–12 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Kucukelbir, A., Sigworth, F. J. & Tagare, H. D. Quantifying the local resolution of cryo-EM density maps. Nat. Methods 11, 63–65 (2014).

    Article  CAS  PubMed  Google Scholar 

  42. Wang, Y., Virtanen, J., Xue, Z. & Zhang, Y. I-TASSER-MR: automated molecular replacement for distant-homology proteins using iterative fragment assembly and progressive sequence truncation. Nucleic Acids Res. https://doi.org/10.1093/nar/gkx349 (2017).

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

    Article  PubMed  Google Scholar 

  44. Adams, P. D. et al. PHENIX: building new software for automated crystallographic structure determination. Acta Crystallogr. D Biol. Crystallogr. 58, 1948–1954 (2002).

    Article  PubMed  Google Scholar 

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

    Article  Google Scholar 

  46. Shen, M. Y. & Sali, A. Statistical potential for assessment and prediction of protein structures. Protein Sci. 15, 2507–2524 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Jo, S., Kim, T., Iyer, V. G. & Im, W. CHARMM-GUI: a web-based graphical user interface for CHARMM. J. Comput. Chem. 29, 1859–1865 (2008).

    Article  CAS  PubMed  Google Scholar 

  48. Lee, J. et al. CHARMM-GUI input generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM simulations using the CHARMM36 additive force field. J. Chem. Theory Comput. 12, 405–413 (2016).

    Article  CAS  PubMed  Google Scholar 

  49. Van Der Spoel, D. et al. GROMACS: fast, flexible, and free. J. Comput. Chem. 26, 1701–1718 (2005).

    Article  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  51. Best, R. B. et al. Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone phi, psi and side-chain chi(1) and chi(2) dihedral angles. J. Chem. Theory Comput. 8, 3257–3273 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Klauda, J. B. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Vanommeslaeghe, K. 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, https://doi.org/10.1002/jcc.21367 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  Google Scholar 

  55. Hoover, W. G. Canonical dynamics: equilibrium phase-space distributions. Phys. Rev. A Gen. Phys. 31, 1695–1697 (1985).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  57. rer, 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).

    Article  Google Scholar 

Download references

Acknowledgements

We thank S. Molugu for support and training of future cryo-EM microscopists at Cleveland Center for Membrane and Structural Biology. We thank D. Major for assistance with hybridoma and cell culture at Department of Ophthalmology and Visual Sciences (supported by the National Institutes of Health Core Grant P30EY11373). We thank A. I. Sobolevsky (Columbia University) for generously providing the structure of TRPV6* before its release. MD simulations were run on resources available through the Scientific Computing Facility at the Icahn School of Medicine at Mount Sinai and the Extreme Science and Engineering Discovery Environment under MCB080077 (to M.F.), which is supported by National Science Foundation grant number ACI-1053575. We acknowledge the use of instruments at the Electron Imaging Center for NanoMachines supported by the NIH (1S10RR23057 and 1S10OD018111), NSF (DBI-1338135) and CNSI at UCLA. This work was supported by grants from the National Institute of Health (R01GM103899 to V.Y.M.-B., R01GM093290 to T.R., and U24 GM116792 to Z.H.Z and V.Y.M.-B).

Author information

Author notes

  1. Vera Y. Moiseenkova-Bell

    Present address: Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

Authors and Affiliations

  1. Department of Pharmacology, School of Medicine, Case Western Reserve University, Cleveland, OH, USA

    Taylor E. T. Hughes, David T. Lodowski, Kevin W. Huynh, Amrita Samanta, Xu Han & Vera Y. Moiseenkova-Bell

  2. Department of Nutrition, School of Medicine, Case Western Reserve University, Cleveland, OH, USA

    David T. Lodowski

  3. California NanoSystems Institute, University of California, Los Angeles, Los Angeles, CA, USA

    Kevin W. Huynh & Z. Hong Zhou

  4. Department of Pharmacology, Physiology and Neuroscience, New Jersey Medical School, Rutgers University, Newark, NJ, USA

    Aysenur Yazici, John Del Rosario & Tibor Rohacs

  5. Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Abhijeet Kapoor & Marta Filizola

  6. Department of Physiology and Biophysics School of Medicine, Case Western Reserve University, Cleveland, OH, USA

    Sandip Basak, Amrita Samanta, Sudha Chakrapani & Vera Y. Moiseenkova-Bell

  7. Pfizer Research and Development, Groton, CT, USA

    Seungil Han

Authors
  1. Taylor E. T. Hughes
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David T. Lodowski
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kevin W. Huynh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aysenur Yazici
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. John Del Rosario
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Abhijeet Kapoor
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sandip Basak
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Amrita Samanta
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Xu Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Sudha Chakrapani
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Z. Hong Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Marta Filizola
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Tibor Rohacs
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Seungil Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Vera Y. Moiseenkova-Bell
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

T.E.T.H. conducted all biochemical and cryo-EM studies, including protein purification, sample preparation, imaging, data analysis, and interpretation; D.T.L. built and refined the atomic model; K.W.H. assisted T.E.T.H. in cryo-EM data collection and analysis; A.Y., J.D.R., and T.R. performed and interpreted electrophysiological data; A.K. performed MD simulations, and M.F. helped interpret the data; A.S. trained T.E.T.H. in cryo-EM sample preparation; X.H. participated in the initial stage of this project; S.B. and S.C. trained T.E.T.H. in data analysis; Z.H.Z. supervised cryo-EM data collection and analysis; S.H. assisted with data analysis; V.Y.M.-B. designed and supervised the execution of all experiments in this manuscript; T.E.T.H. and V.Y.M.-B. drafted the manuscript; all authors reviewed the final manuscript.

Corresponding author

Correspondence to Vera Y. Moiseenkova-Bell.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Figure 1 TRPV5 purification, whole-cell electrophysiology, and data processing

a A size exclusion chromatogram of purified TRPV5. The inset panel depicts a SDS-PAGE image of purified TRPV5. b Whole cell patch clamp experiments were performed as described in the methods section in HEK293 cells transfected with rbTRPV5 using a ramp protocol from −100 to 100 mV; currents are plotted at -100 and 100 mV, zero current is indicated by the dashed line. Representative trace (n = 11), monovalent currents were initiated by removal of extracellular Ca2+ and Mg2+ and the application of 0.33 % DMSO and 3 μM econazole is indicted by the horizontal lines. c Concentration response curve for econazole. Error bars represent ± s.e.m. of the respective n biological replicates. d The first panel is a representative micrograph of TRPV5 incubated with econazole frozen in vitreous ice (n = 3,313). Scale bar = 25 nm. The second panel depicts 2D class averages used when reconstructing the TRPV5ECN structure. e The workflow used to reconstruct TRPV5ECN to 4.8Å. A box around a 3D class indicates that that class was taken for further processing.

Supplementary Figure 2 Resolution data for TRPV5ECN refinement

a FSC curves for masked, unmasked and corrected reconstructions. The dashed line represents an FSC of 0.143. b The angular distribution of 2D views for the final particles used for the reconstruction. High numbers of particles are represented as taller red cylinders while views with a low number of particles are shown as shorter blue cylinders. The final density map of TRPV5ECN is shown in grey. c Multiple views of the local resolution map of TRPV5ECN. Local resolution was determined using ResMap software.

Supplementary Figure 3 TRPV5 model validation

a Various helices of the TRPV5ECN model (cartoon) overlaid with the TRPV5ECN density map (mesh). Select residues are shown as sticks to illustrate the accuracy of the model. All helices shown are within the 3.5–4.0 Å region of the structure. b Other domains of the TRPV5ECN model (cartoon) overlaid with the final TRPV5ECN density map (mesh). The different regions of the TRPV5ECN model are colored based on the diagram in Fig. 1b.

Supplementary Figure 4 Binding sites among TRPV subfamily members

a Density maps of econazole (ECN) bound rabbit TRPV5, capsazepine (CPZ) bound rat TRPV1 solved in nanodiscs and apo rat TRPV1 solved in nanodiscs. Densities attributed to lipids in each structure are colored in blue. The lipid to which each density was ascribed is listed below each structure. b Density maps of econazole (ECN) bound rabbit TRPV5, capsazepine (CPZ) bound rat TRPV1 solved in nanodiscs. ECN densities are shown in yellow. Capsazepine densities are shown in orange.

Supplementary Figure 5 Econazole-binding pocket

a Molecular structure of econazole. The asterisk indicates the location of a chiral center. b Zoomed in view of the econazole binding pocket manually fitted with R-econazole (yellow). The grey mesh represents the cryo-EM density attributed to econazole. c Zoomed in view of the econazole binding pocket manually fitted with S-econazole (yellow). The grey mesh represents the cryo-EM density attributed to econazole. d-e An electrostatic map of TRPV5ECN was calculated via APBS software. The zoomed views depict the econazole binding pocket with R-econazole or S-econazole shown in yellow.

Supplementary Figure 6 Econazole effect on mutant TRPV5

Two electrode voltage clamp (TEVC) experiments were performed similar to that described in Fig. 2 on Xenopus laevis oocytes injected with cRNA encoding the wild type or various mutants of rabbit TRPV5. a-e Representative traces for WT and various TRPV5 mutants (n = 10, n = 7, n = 4, n = 3, n = 7, respectively), currents are shown at −100 and +100 mV, zero current is indicated by the dashed line, the applications of 2.2 % DMSO (solvent) and 20 μM Econazole (ECN) are indicated by the horizontal lines. f Summary of the effects of 20 μM econazole and 2.2 % DMSO. *** p < 0.001 indicates a difference between econazole inhibition in WT (first black column). ##p<0.01, ###p<0.001 indicates a difference from the effect of DMSO on WT channels (first grey column); one way analysis of variance with Bonferroni post hoc comparison. Error bars represent ± s.e.m. of the respective n biological replicates.

Supplementary Figure 7 Comparison of ligand binding pockets within the TRPV subfamily

a The transmembrane domain (TMD) of TRPV5ECN. Bound econazole (ECN) is represented as yellow sticks. The regions of TRPV5ECN are colored based on the diagram in Fig. 1b. b The TMD of rat TRPV1 solved in nanodiscs in the absence of added ligand (purple, PDB: 5IRZ). Bound phosphatidylinositol, a lipid cofactor of TRPV1, is shown in grey sticks. c The TMD of rat TRPV1 solved in nanodiscs in the presence of the inhibitor capsazepine (orange, PDB: 5IS0). The capsazepine molecule (CPZ) is shown in grey. d The TMD of rat TRPV1 solved in nanodiscs in the presence of the potent agonists, resiniferatoxin (RTX) and double-knot toxin (DkTx) is shown in red (PDB: 5IRX). The pocket depicted coordinates an RTX molecule (grey).

Supplementary Figure 8 Econazole flexibility during MD production run

a Time evolution of the RMSD of R-econazole (labeled ECN_1 to ECN_4) with respect to the initial manual docking into the assigned electron density within the four monomers of TRPV5 (monomers A to D, respectively) during the 25 ns production run. b Time evolution of the RMSD of S-econazole (labeled ECN_1 to ECN_4) with respect to the initial manual docking into the assigned electron density within the four monomers of TRPV5 (monomers A to D, respectively) during the 25 ns production run.

Supplementary Figure 9 TRPV5 stability during MD production run

Time evolution of a RMSD of Cα-atoms of TM helices S1 to S6 (blue) and all Cα atoms of the TRPV5 tetramer (red) bound to R-econazole, and b Cα RMSF for each monomer during the 25 ns production run of the TRPV5 complex bound to R-econazole. Panels c and d show the time evolution of RMSD and RMSF values for the TRPV5 complex bound to S-econazole.

Supplementary Figure 10 Flexibility of econazole molecules during MD production run

Binding modes of four R-econazole molecules (grey carbons; labeled ECN_1 to ECN_4 in panels a to d sampled during the 25 ns production run and compared to the initial manually docked pose of R-econazole (yellow carbons) into the assigned electron density. Each panel a to d shows five conformations of R-econazole within the four monomers of TRPV5 (monomers A to D colored blue, red, green, and dark grey, respectively) at simulation times 5 ns, 10 ns, 15 ns, 20 ns, and 25 ns.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1-10, Supplementary Table 1

Life Sciences Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hughes, T.E.T., Lodowski, D.T., Huynh, K.W. et al. Structural basis of TRPV5 channel inhibition by econazole revealed by cryo-EM. Nat Struct Mol Biol 25, 53–60 (2018). https://doi.org/10.1038/s41594-017-0009-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41594-017-0009-1

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing