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Selective G protein signaling driven by substance P–neurokinin receptor dynamics

Nature Chemical Biology volume 18, pages 109–115 (2022)Cite this article

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Abstract

The neuropeptide substance P (SP) is important in pain and inflammation. SP activates the neurokinin-1 receptor (NK1R) to signal via Gq and Gs proteins. Neurokinin A also activates NK1R, but leads to selective Gq signaling. How two stimuli yield distinct G protein signaling at the same G protein-coupled receptor remains unclear. We determined cryogenic-electron microscopy structures of active NK1R bound to SP or the Gq-biased peptide SP6–11. Peptide interactions deep within NK1R are critical for receptor activation. Conversely, interactions between SP and NK1R extracellular loops are required for potent Gs signaling but not Gq signaling. Molecular dynamics simulations showed that these superficial contacts restrict SP flexibility. SP6–11, which lacks these interactions, is dynamic while bound to NK1R. Structural dynamics of NK1R agonists therefore depend on interactions with the receptor extracellular loops and regulate G protein signaling selectivity. Similar interactions between other neuropeptides and their cognate receptors may tune intracellular signaling.

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Fig. 1: Cryo-EM structure of active NK1R bound to SP.
Fig. 2: Molecular recognition of SP by NK1R.
Fig. 3: Structural interrogation of SP6–11, a Gq-selective tachykinin.
Fig. 4: Molecular dynamics shows increased mobility of SP6–11.
Fig. 5: Disruption of SP–NK1R ECL2 contacts leads to Gq-selective signaling.

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Data availability

All data generated or analyzed during this study are included in this published article and its Supplementary Information. Coordinates for SP–NK1R–miniGs/q70, SP–NK1R–miniGs399 and the SP6–11–NK1R–miniGs/q70 complex have been deposited in the PDB under accession codes 7RMG, 7RMH and 7RMI, respectively. Unsharpened and sharpened EM density maps and half maps for SP–NK1R–miniGs/q70, SP–NK1R–miniGs399 and the SP6–11–NK1R–miniGs/q70 complex have been deposited in the Electron Microscopy Data Bank under accession codes 24569, 24570 and 24572, respectively. Final particle stacks for SP–NK1R–miniGs/q70, SP–NK1R–miniGs399, and the SP6–11–NK1R–miniGs/q70 complex reconstruction have been uploaded to the Electron Microscopy Public Image Archive under the accession code EMD-EMPIAR 10786. Simulation trajectories for molecular dynamics simulations have been deposited on Zenodo, and are available at https://doi.org/10.5281/zenodo.5113874Source data are provided with this paper.

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Acknowledgements

We thank M. Yeasmin for assisting with IP1 accumulation assays. This work was supported by National Institutes of Health (NIH) grant nos. 1R35GM140847 (Y.C.), DP5OD023048 (A.M.), R01GM127359 (R.O.D.) and a National Health and Medical Research Council (NHMRC) Project Grant APP1138448 (D.M.T.), NHMRC Investigator grant no. APP1196951 (D.M.T), Australian Research Council DECRA grant no. DE170100152 (D.M.T.) and Australian Research Council Centre of Excellence in Convergent Bio-Nano Science and Technology (N.A.V.). This material is based on work supported by the National Science Foundation Graduate Research Fellowship Program (J.A.H.) under grant no. 2034836. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. C.-M.S. was funded by the Human Frontier Science Program (grant no. LT000916/2018-L). Cryo-EM equipment at UCSF is partially supported by NIH grant nos. S10OD020054 and S10OD021741. Some of this work was performed at the Stanford-SLAC Cryo-EM Center (S2C2), which is supported by the NIH Common Fund Transformative High-Resolution Cryo-Electron Microscopy program (grant no. U24 GM129541). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. Y.C. is an Investigator of Howard Hughes Medical Institute. A.M. acknowledges support from the Pew Charitable Trusts, the Esther and A. & Joseph Klingenstein Fund and the Searle Scholars Program. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper.

Author information

Author notes

  1. These authors contributed equally: Julian A. Harris, Bryan Faust, Arisbel B. Gondin, Marc André Dämgen.

Authors and Affiliations

  1. Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA

    Julian A. Harris, Bryan Faust & Aashish Manglik

  2. Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, CA, USA

    Julian A. Harris

  3. Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA

    Bryan Faust & Yifan Cheng

  4. Biophysics Graduate Program, University of California, San Francisco, CA, USA

    Bryan Faust

  5. Drug Discovery Biology, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia

    Arisbel B. Gondin, Nicholas A. Veldhuis & David M. Thal

  6. Australian Research Council Centre of Excellence in Convergent Bio-Nano Science and Technology, Monash University, Parkville, Victoria, Australia

    Arisbel B. Gondin & Nicholas A. Veldhuis

  7. Department of Computer Science, Stanford University, Stanford, CA, USA

    Marc André Dämgen, Carl-Mikael Suomivuori & Ron O. Dror

  8. Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA

    Marc André Dämgen, Carl-Mikael Suomivuori & Ron O. Dror

  9. Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA

    Marc André Dämgen, Carl-Mikael Suomivuori & Ron O. Dror

  10. Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA

    Marc André Dämgen, Carl-Mikael Suomivuori & Ron O. Dror

  11. Howard Hughes Medical Institute, University of California, San Francisco, CA, USA

    Yifan Cheng

  12. Department of Anesthesia and Perioperative Care, University of California, San Francisco, CA, USA

    Aashish Manglik

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  1. Julian A. Harris
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Contributions

J.A.H. purified NK1R constructs, Gβ1γ2 and Nb35, established biochemical approaches to reconstitute a NK1R–miniG protein complex and generated all NK1R mutants. B.F. purified Gβ1γ2 and Nb35, prepared samples for cryo-EM, identified optimal freezing conditions for cryo-EM, screened samples by cryo-EM, collected cryo-EM data and determined high-resolution cryo-EM maps by extensive image processing under the guidance of A.M. and Y.C. J.A.H. built and refined models of NK1R–miniG protein complexes with input from B.F. and A.M. A.B.G. generated NK1R stable cell lines and performed cellular signaling experiments under the guidance of N.A.V. and D.M.T. M.A.D. and C.-M.S. performed and analyzed molecular dynamics simulations under the guidance of R.O.D. The paper was written by J.A.H., B.F., A.B.G., M.A.D., C.-M.S., R.O.D. and A.M., with edits from N.A.V., D.M.T. and Y.C. and with approval from all authors. The overall project was supervised by A.M.

Corresponding authors

Correspondence to Yifan Cheng, Ron O. Dror, David M. Thal or Aashish Manglik.

Ethics declarations

Competing interests

Research in N.A.V.’s laboratory is funded, in part, by Takeda Pharmaceuticals and Endosome Therapeutics.

Additional information

Peer review information Nature Chemical Biology thanks Tao Che, Daniel Wacker and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Extended data

Extended Data Fig. 1 Biochemistry of active-state NK1R–miniG protein complexes.

(a) Size-exclusion chromatography of SP-bound NK1R, NK1R-miniGs/q70 and NK1R-miniGs399 shows an increase in the fraction of monomeric receptor species for NK1R-miniG fusion proteins. Size-exclusion chromatography traces and Coomassie stained SDS-PAGE gels of purified (b) SP-bound NK1R-miniGs/q70 complex, (c) SP-bound NK1R-miniGs399 complex, and (d) SP6-11-bound NK1R-miniGs/q70 complex. Uncropped versions of Coomassie stained SDS-PAGE gels are provided in Supplementary Fig. 1.

Extended Data Fig. 2 CryoEM data processing workflow for SP–NK1R-miniGs/q70 heterotrimeric complex.

(a) Representative micrograph of 3555 collected micrographs. Scale bar, 50 nm. (b) 2D-class averages for SP-NK1R-miniGs/q70 complex. (c) A flowchart representation of the processing pipeline used for structural determination of the SP-NK1R-miniGs/q70 complex. Contrast transfer function (CTF) estimation, 2D classification and all 3D classification jobs with alignment were performed with cryoSPARC. 3D classification without alignment was performed with RELION using a mask encompassing only the receptor transmembrane and final focused refinements were performed with cisTEM. Focused refinement masks are shown as red mesh. Gold-standard fourier shell correlation (GS-FSC) was calculated from a cryoSPARC Local Resolution job using the focused refinement mask encompassing the entire SP-NK1R-miniGs/q70 complex. A viewing distribution plot was generated using scripts from the pyEM software suite and visualized in ChimeraX. Directional FSC curves (dFSCs) are shown as purple lines and were determined as previously described in Dang, S. et al. Nature 552, 426-429 (2017).

Extended Data Fig. 3 Cryo-EM density map for NK1R-miniGs/q70 heterotrimeric complex.

(a) Unsharpened Cryo-EM density map for individual NK1R helices and Substance P density as determined by extending a 2.5 Å radius away from each modeled atom. Local resolution estimation of unsharpened Cryo-EM density maps for (b) SP-NK1R-miniGs/q70 and (c) SP6-11-NK1R-miniGs/q70 heterotrimeric complex from cryoSPARC. SP and SP6-11 density are highlighted in and shown at equivalent enclosed volume thresholds.

Extended Data Fig. 4 Structural hallmarks of NK1R activation.

(a) Alignment of the SP-NK1R-miniGs/q70 structure with an inactive-state NK1R structure (PDB: 6HLP24) reveals rearrangement of NK1R structural motifs indicative of class A GPCR activation, including: (b) displacement of the W6.48 ‘toggle-switch’ and (c) rearrangement of the ‘P5.50I3.40F6.44’ connector motif. (d) The non-canonical E782.50-N3017.49 interaction in NK1R is unchanged between inactive- and active-state structures. We compared the NK1R E782.50-N3017.49 interaction to the D2.50-N7.49 interaction in three class A neuropeptide-binding GPCRs, including: (e) the μ-opioid receptor (Active PDB: 5C1M17, Inactive PDB: 4DKL18), (f) the neurotensin 1 receptor (Active PDB: 6OS922, Inactive PDB: 4BUO23), and (g) the orexin 2 receptor (Active PDB: 7L1U, Inactive PDB: 5WQC). Alignment of the SP-NK1R-miniGs/q70 structure with (h) canonical (PDB: 6OS922) and (i) ‘non-canonical’ (PDB: 6OSA22) active-state NTS1R reveals that the miniGs/q70 protein adopts the canonical G protein coupling orientation.

Extended Data Fig. 5 Comparison of SP-NK1R binding site to related Neuropeptide GPCRs and Inactive-State NK1R Structures.

Comparison of SP-bound NK1R-miniGs/q70 structure to neuropeptide GPCRs bound to peptidergic ligands, including: (a) the neurotensin 1 receptor bound to neurotensin 8-13 (PDB: 6OS922), (b) the μ-opioid receptor bound to the peptide mimetic agonist DAMGO (PDB: 6DDE26), and (c) the orexin 2 receptor bound to orexin B (PDB: 7L1U27). Alignment of SP-bound NK1R with inactive-state NK1R structures, including: (d) netupitant-bound (PDB: 6HLP24), (e) aprepitant-bound (PDB: 6HLO24), (f) L-760,735-bound (PDB: 6E5928), and (g) CP-99,994-bound NK1R (PDB: 6HLL24). (h) Antagonist chemical structures shown with regions that compete with SP binding site in red.

Extended Data Fig. 6 Signaling studies for NK1R mutations in the deep 7TM region.

Ca2+mobilization of wild-type and NK1R mutants after stimulation with (a) SP and (b) SP6-11. Signaling graphs represent the global fit of grouped data ± s.e.m. from at least three independent biological replicates. SP: N85D, n = 4; N85Q, n = 5; N89D, n = 5; H108A, n = 5; H108Q, n = 5; Y287F, n = 5; Y287H, n = 5. SP6-11: N85D, n = 3; N85Q, n = 4; N89D, n = 4; H108A, n = 4; H108Q, n = 4; Y287F, n = 4; Y287H, n = 3. Full quantitative parameters from this experiment are listed in Supplementary Table 1. (c) Cell-surface expression of deep 7TM NK1R mutants as determined by ELISA. Untransfected (UT) control shows low ELISA signal. Bar graphs represent mean ± s.e.m. from n = 4 independent biological replicates. Representative kinetic traces of (d) SP (e) NKA, and (f) SP6-11 elicited Ca2+ mobilization and cAMP accumulation from at least three independent biological replicates. Ca2+ signaling: SP, n = 10; NKA, n = 6; SP6-11, n = 4. IP1 accumulation: SP, n = 5; NKA, n = 3; SP6-11, n = 4. cAMP accumulation: SP, n = 12, NKA, n = 7, SP6-11, n = 4. Full quantitative parameters from this experiment are listed in Supplementary Table 2. (g) Ligand induced coupling of miniGs/q-Venus to hNK1R-RLuc as determined by BRET. Graphs represent the global fit of grouped data ± s.e.m. from n = 3 independent biological replicates. Full quantitative parameters from this experiment are listed in Supplementary Table 3. (h) Representative kinetic traces of SP, NKA, and SP6-11 induced recruitment of miniGs/q-Venus to hNK1R-RLuc as determined by BRET from n = 3 independent biological replicates. (i) Ligand induced coupling of miniGs-Venus to hNK1R-RLuc as determined by BRET. Graphs represent the global fit of grouped data ± s.e.m. from n = 3 independent biological replicates. Full quantitative parameters from this experiment are listed in Supplementary Table 3. (j) Representative kinetic traces of SP, NKA, and SP6-11 induced recruitment of miniGs-Venus to hNK1R-RLuc as determined by BRET from n = 3 independent biological replicates.

Extended Data Fig. 7 CryoEM data processing for SP-NK1R-miniGs399 complex.

(a) Representative micrograph of 3670 collected micrographs. Scale bar, 50 nm. (b) 2D-class averages for SP-NK1R-miniGs399 complex. (c) A flowchart representation of the processing pipeline used for structural determination of the SP-NK1R-miniGs399 complex. CTF Estimation, 2D classification and all 3D classification jobs with alignment were performed with cryoSPARC. 3D classification without alignment was performed with RELION using a mask encompassing only the receptor transmembrane and final focused refinements were performed with cisTEM. Focused refinement masks are shown as red mesh. Gold-standard fourier shell correlation (GS-FSC) was calculated from a cryoSPARC Local Resolution job using the focused refinement mask encompassing the entire SP-NK1R-miniGs399 complex. A viewing distribution plot was generated using scripts from the pyEM software suite and visualized in ChimeraX. Directional FSC (dFSC) are shown as purple lines and were determined as previously described in Dang, S. et al. Nature 552, 426-429 (2017).

Extended Data Fig. 8 CryoEM data processing for SP6-11-NK1R-miniGs/q70 complex.

(a) Representative micrograph of 3878 collected micrographs. Scale bar, 50 nm. (b) 2D-class averages for SP6-11-NK1R-miniGs/q70 complex. (c) A flowchart representation of the processing pipeline used for structural determination of the SP6-11-NK1R-miniGs/q70 complex. CTF Estimation, 2D classification and all 3D classification jobs with alignment were performed with cryoSPARC. 3D classification without alignment was performed with RELION using a mask encompassing only the receptor transmembrane and final focused refinements were performed with cisTEM. Focused refinement masks are shown as red mesh. GS-FSC was calculated from a cryoSPARC Local Resolution job using the focused refinement mask encompassing the entire SP6-11-NK1R-miniGs/q70 complex. A viewing distribution plot was generated using scripts from the pyEM software suite and visualized in ChimeraX. Directional FSC curves (dFSC) are shown in purple lines and were determined as previously described in Dang, S. et al. Nature 552, 426-429 (2017).

Extended Data Fig. 9 Comparison of NK1R G protein-complexes.

Alignment of SP-NK1R-miniGs/q70 and SP6-11-NK1R-miniGs/q70 through NK1R 7TM domain reveals minimal changes in (a) overall 7TM architecture, (b) overall peptide binding poses, and (c) insertion of miniG protein α5 helix in NK1R core. Alignment of SP-NK1R-miniGs/q70 and SP-NK1R-miniGs399 through NK1R 7TM domain reveals minimal changes in (d) overall 7TM architecture, (e) overall SP binding pose, and (f) insertion of miniG protein α5 helix in NK1R core.

Extended Data Fig. 10 Signaling studies for NK1R ECL2 mutations.

(a) Fraction of time R177 is in contact with SP vs. SP6-11 in molecular dynamics simulations. Bar graphs show mean ± s.e.m. from twelve independent molecular dynamics simulations under each condition. SP spent more time in contact with R177 than SP6-11 (p < 0.05, two-sided Welch’s t-test; see Methods). Our simulations are not sufficiently long to guarantee convergence of this quantity. (b) Ca2+ mobilization and (c) cAMP accumulation of wild-type and ECL2 NK1R mutants after stimulation with SP. Signaling graphs represent the global fit of grouped data ± s.e.m. from at least three independent biological replicates. Ca2+ signaling: WT, n = 9; M174V, n = 5; R177K, n = 6; M181F, n = 5; M181V, n = 5. cAMP accumulation: WT, n = 12; M174V, n = 3; R177K, n = 4; M181F, n = 3; M181V, n = 4. Full quantitative parameters from this experiment are listed in Supplementary Table 1. (d) Cell-surface expression of ECL2 NK1R mutants as determined by ELISA. Untransfected (UT) control shows low ELISA signal. Bar graphs represent mean ± s.e.m. from n = 4 independent biological replicates. (e) Ca2+ mobilization and cAMP accumulation of wild-type, M174I, and R177M NK1R mutants after stimulation with SP6-11. Signaling graphs represent the global fit of grouped data ± s.e.m. from at lease three independent biological replicates. Ca2+ signaling: WT, n = 8; M174I, n = 4; R177M, n = 4. cAMP accumulation: WT, n = 11; M174I, n = 3; R177M, n = 4. Full quantitative parameters from this experiment are listed in Supplementary Table 1. Representative kinetic traces of SP-induced Ca2+ mobilization and cAMP accumulation for (f) NK1R M174I and (g) NK1R R177M from at least three independent biological replicates. Ca2+ signaling: WT, n = 9; M174I, n = 5; R177M, n = 9. cAMP accumulation: WT, n = 12, M174I, n = 3, R177M, n = 8. Full quantitative parameters from this experiment are listed in Supplementary Table 1.

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Supplementary Tables 1–4 and Fig. 1.

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Uncropped Coomassie-stained SDS–PAGE gels from Extended Data Fig. 1.

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Harris, J.A., Faust, B., Gondin, A.B. et al. Selective G protein signaling driven by substance P–neurokinin receptor dynamics. Nat Chem Biol 18, 109–115 (2022). https://doi.org/10.1038/s41589-021-00890-8

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