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Precise druggability of the PTH type 1 receptor

Nature Chemical Biology volume 18, pages 272–280 (2022)Cite this article

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Abstract

Class B G protein-coupled receptors (GPCRs) are notoriously difficult to target by small molecules because their large orthosteric peptide-binding pocket embedded deep within the transmembrane domain limits the identification and development of nonpeptide small molecule ligands. Using the parathyroid hormone type 1 receptor (PTHR) as a prototypic class B GPCR target, and a combination of molecular dynamics simulations and elastic network model-based methods, we demonstrate that PTHR druggability can be effectively addressed. Here we found a key mechanical site that modulates the collective dynamics of the receptor and used this ensemble of PTHR conformers to identify selective small molecules with strong negative allosteric and biased properties for PTHR signaling in cell and PTH actions in vivo. This study provides a computational pipeline to detect precise druggable sites and identify allosteric modulators of PTHR signaling that could be extended to GPCRs to expedite discoveries of small molecules as novel therapeutic candidates.

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Fig. 1: ESSA points to an extracellularly-exposed pocket as an essential site that can potentially alter the allosteric dynamics of PTHR on ligand binding.
Fig. 2: Identification of druggable sites and drug-like small molecules targeting PTHR.
Fig. 3: Actions of Pitt12 on PTH signaling.
Fig. 4: Refinement and validation of Pitt12 binding site in PTHR.
Fig. 5: Conformational change of PTHR due to Pitt12 binding.
Fig. 6: In vivo action of Pitt12.

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Data availability

Source of datasets analyzed during this study for figures (Figs. 1–6, Extended Data Figs. 2–4, and Supplementary Figs. 1–5) are provided with this paper. Materials and associated protocols will be made available to all qualified investigators from the corresponding authors upon reasonable request. Source data are provided with this paper.

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Acknowledgements

Research reported in this publication was supported by the National Institute of Diabetes and Digestive and Kidney Disease, the National Institute of General Medical Sciences, the National Institute on Drug Abuse and the National Center for Advancing Translational Sciences of the US National Institutes of Health (NIH) under grant awards nos. R01-DK116780 (to J.-P.V.), R01-DK122259 (to W.C. and J-P.V.), P41 GM103712 and R01 GM139297 (to I.B. and P.D.), P01-DK011794 (to T.J.G.) and by the University of Pittsburgh Clinical and Translational Science Institute (grant no. NIH UL1TR001857).

Author information

Author notes

  1. Hongchun Li

    Present address: Research Center for Computer-Aided Drug Discovery, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Beijing, China

  2. Saifei Lei

    Present address: Center for Pharmacogenetics, University of Pittsburgh, School of Pharmacy, Pittsburgh, PA, USA

  3. Lisa J. Clark

    Present address: Department of Biological Chemistry, University of California, Los Angeles, CA, USA

  4. These authors contributed equally: Ji Young Lee, Alex D. White.

Authors and Affiliations

  1. Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

    Ieva Sutkeviciute, Alex D. White, Karina A. Peña, Sofya Savransky, Saifei Lei, Lisa J. Clark, Subramaniam Sanker & Jean-Pierre Vilardaga

  2. Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

    Ji Young Lee, Pemra Doruker, Hongchun Li, Burak Kaynak & Ivet Bahar

  3. Endocrine Research Unit, Department of Veterans Affairs Medical Center, University of California, San Francisco, CA, USA

    Christian Santa Maria, Chialing Tu & Wenhan Chang

  4. Graduate Program in Molecular Pharmacology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA

    Sofya Savransky

  5. Endocrine Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Thomas J. Gardella

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Contributions

A.D.W., S.L., S.Savransky, S.Sanker and K.A.P. performed signaling studies. A.D.W., I.S. and J.-P.V. performed signaling data analyses. J.Y.L. and H.L. performed druggability simulations. J.Y.L. performed pharmacophore modeling. B.K. and P.D. performed ESSA. T.J.G. provided guidance for radioligand binding assays. L.J.C. conducted docking studies. W.C., C.S.M. and C.T. conducted mouse studies. I.S., I.B. and J.-P.V. oversaw the project, designed the study and provided guidance. J.-P.V., I.B., I.S. and A.D.W. wrote the paper.

Corresponding authors

Correspondence to Ieva Sutkeviciute, Ivet Bahar or Jean-Pierre Vilardaga.

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Competing interests

I.S., J.Y.L., B.K., I.B. and J.-P.V. acknowledge potential competing financial interests. No conflicts of interest were disclosed by other authors.

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Peer review information Nature Chemical Biology thanks Lei Shi, Celine Valant 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 Close-up view of the pocket at the EC vestibule.

The pocket is lined by TM1 (red) and TM2 (cyan). Essential residues R1811.33b and Y2452.72b, whose interaction with ligands is predicted to affect the global dynamics of the overall PTHR, are shown in yellow sticks. Two additional residues, D252ECL1 and F1841.36b are also shown, which may help attract or coordinate the ligands through electrostatic interactions. The role of F184 in complementing R1811.33b and Y2452.72b to line a druggable pocket is further corroborated by druggability simulations.

Extended Data Fig. 2 Probe molecules used in druggability simulations.

(a) Seven probe molecules used in PTHR druggability simulations. The structure of each probe is shown along with its 4-letter acronym, its name and main chemical properties. Also shown is the percentage of drugs containing those fragments based on the SMILES data of 2,453 approved drugs in DrugBank. (b) An example of a common drug, benzyl-penicillin, containing four types of fragments represented by the probe molecules. (c) Binding score profile for PTHR residues near Site 1 (labeled along the abscissa), evaluated for different probe molecules (bars in different colors). The binding score is defined as Σ (1/𝑑ki)2 where k is frame/snapshot index and 𝑑ki is corresponding distance between the probe and the residue i summed over all snapshots n (12,000 compiled from six independent runs), provided that they make atom-atom contacts of 𝑑ki < 4.0 Å. Residues with score above 1500/Å2 (dashed line) are selected as high affinity residues for each probe type: R1811.33b for acetate, and F1841.36b and Y2452.72b for isopropanol. (d) Close-up view of site 1 preferentially sampled by three probes (two isopropanol and an acetic acid, shown in yellow and red sticks respectively), and associated residues R1811.33b, F1841.36b and Y2452.72b (right). (e, f) Construction of pharmacophore model (PM) composed of a hydrogen bond acceptor, a negatively charged region, and two hydrophobic sites (spheres), based on the preferential positions observed in (c), and overlay of a hit compound Pitt12 (aquamarine sticks, extracted from the ZINC database) and the PM. The box on the left in panel (f) shows the partial charges for the carboxylate group atoms O, C, O’, and H in Pitt12 in its protonated and deprotonated forms. In line with the use of acetate probe molecule to construct the PM, we used the deprotonated form in further analyses and simulations.

Source data

Extended Data Fig. 3 Actions of Pitt8 on PTH signaling.

(a, b) Binding isotherms showing competitive inhibition of radio-labeled peptide ligand binding to PTHR by PTH or Pitt8, using plasma membrane extracts from HEK293 cells expressing recombinant PTHR. Inhibition of [125I]-LAPTH binding to G protein-independent conformational R0 state of PTHR (that is, in the absence of G proteins) by PTH1-34 (black) or Pitt8 (pink) (a). Inhibition of [125I]-M-PTH1-15 binding to G protein-dependent RG conformational state of PTHR (that is, in the presence of G proteins) by M-PTH1-15 (black) or Pitt8 (pink). Mean ± s.d. of N = 6 experiments. (c) Concentration-response curves for cAMP production by PTH alone or together with Pitt8. Data are mean ± s.e.m. of N = 3 independent experiments. (d, e) Averaged cAMP time-courses following brief stimulation with 1 nM PTH without (Ctrl, black) or with 10 µM Pitt12 measured by FRET changes from HEK293 cells stably expressing PTHR and a FRET-based cAMP sensor EpacCFP/YFP in the absence (d) or presence of the dominant-negative dynamin mutant (DynK44A) tagged with RFP (e). (f) Time course of β-arrestin 2 interaction with PTHR measured by FRET in HEK293 cells transiently expressing PTHRCFP and βarr-2YFP following brief stimulation with 10 nM PTH without (Ctrl) or with 10 µM Pitt8. Cells were continuously perfused with control buffer or PTH alone or together with Pitt8 (horizontal bar). Data are the mean ± s.e.m. of N = 3 experiments with n = 52 (DMSO) and 47 (Pitt8) cells examined. (g) Time courses of Ca2+ release in response to PTH (100 nM) with or without Pitt8 (10 µM) in live HEK-293 cells expressing recombinant PTHR. Data are the mean ± s.e.m. of N = 3 experiments with n = 32 (DMSO) and 32 (Pitt8) cells examined.

Source data

Extended Data Fig. 4 Statistics for integrated responses from Fig. 3 and Extended Data Fig. 3.

(a) pKi values for Pitt12 for the RG state were: -10.77 ± 0.15 (M-PTH1-15) and -4.39 ± 0.96 (Pitt12); for the R0 state: -8.26 ± 0.14 (PTH1-34) and -5.15 ± 0.63. pKi values for Pitt8 the RG state were: -10.77 ± 0.15 (M-PTH1-15) and -5.25 ± 0.48 (Pitt8); for the R0 state: -8.26 ± 0.14 (PTH1-34) and -4.79 ± 0.30 (Pitt8). Mean ± s.d. of N = 6 experiments. (b) Quantitation of cAMP responses by measuring the area under the curve (A.U.C.) from 0 to 20 min for Fig. 3e,f, and Extended Data Fig. 3d,e. Data are mean ± s.d. of N = 6 (PTH), 3 (Pitt12), and 3 (Pitt8) experiments for control, and N = 4 (PTH), 4 (Pitt12), and 4 (Pitt8) experiments for DynK44A. NS, not significant, **P < 0.002 and ***P < 0.0002 by two-way ANOVA with Tukey-Kramer post-hoc test. (c, d) Data are from Fig. 3h and Extended Data Fig. 3g. Mean ± s.e.m. of N = 3 independent experiments. P values were assessed by two-tailed Student’s t-test with *P < 0.05, **P < 0.005.

Source data

Supplementary information

Supplementary Information

Supplementary Tables 1 and 2 and Figs. 1–5.

Reporting Summary

Supplementary Video 1

A video from initial druggability simulations showing persistent contacts between Pitt12 and PTHR residues E1801.32b and R1811.33b.

Supplementary Data 1

Source data spreadsheet for Supplementary Fig. 1.

Supplementary Data 2

Source data spreadsheet for Supplementary Fig. 2.

Supplementary Data 3

Source data spreadsheet for Supplementary Fig. 3.

Supplementary Data 4

Source data spreadsheet for Supplementary Fig. 4.

Supplementary Data 5

Source data spreadsheet for Supplementary Fig. 5.

Source data

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Sutkeviciute, I., Lee, J.Y., White, A.D. et al. Precise druggability of the PTH type 1 receptor. Nat Chem Biol 18, 272–280 (2022). https://doi.org/10.1038/s41589-021-00929-w

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