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Rational design of agonists for bitter taste receptor TAS2R14: from modeling to bench and back

  • Antonella Di Pizio
  • Lukas A. W. Waterloo
  • Regine Brox
  • Stefan Löber
  • Dorothee Weikert
  • Maik BehrensEmail author
  • Peter GmeinerEmail author
  • Masha Y. NivEmail author
Original Article

Abstract

Human bitter taste receptors (TAS2Rs) are a subfamily of 25 G protein-coupled receptors that mediate bitter taste perception. TAS2R14 is the most broadly tuned bitter taste receptor, recognizing a range of chemically diverse agonists with micromolar-range potency. The receptor is expressed in several extra-oral tissues and is suggested to have physiological roles related to innate immune responses, male fertility, and cancer. Higher potency ligands are needed to investigate TAS2R14 function and to modulate it for future clinical applications. Here, a structure-based modeling approach is described for the design of TAS2R14 agonists beginning from flufenamic acid, an approved non-steroidal anti-inflammatory analgesic that activates TAS2R14 at sub-micromolar concentrations. Structure-based molecular modeling was integrated with experimental data to design new TAS2R14 agonists. Subsequent chemical synthesis and in vitro profiling resulted in new TAS2R14 agonists with improved potency compared to the lead. The integrated approach provides a validated and refined structural model of ligand–TAS2R14 interactions and a general framework for structure-based discovery in the absence of closely related experimental structures.

Keywords

Bitter taste receptor GPCRs Drug design Structure-based modeling Bioisosteric replacement 

Notes

Acknowledgements

This research was supported in part by the German Research Foundation Grants Gm 13/12 (to P.G. and M.Y.N.), GRK 1910 (to P.G.), and ISF 494/16 (to M.Y.N). Lady Davis Fellowship and COST-STSM-CM1207 (GLISTEN) to A.D.P. are gratefully acknowledged. M.Y.N and A.D.P. participate in Mu.Ta.Lig—COST ACTION CA15135. The authors would like to thank Catherine Delaporte for the excellent technical assistance and Tamir Dingjan for the critical reading of the manuscript.

Supplementary material

18_2019_3194_MOESM1_ESM.pdb (390 kb)
Supplementary material 1 (PDB 390 kb)
18_2019_3194_MOESM2_ESM.pdb (387 kb)
Supplementary material 2 (PDB 387 kb)
18_2019_3194_MOESM3_ESM.pdf (4.1 mb)
Supplementary material 3 (PDF 4240 kb)

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.The Robert H. Smith Faculty of Agriculture, Food and Environment, Institute of Biochemistry, Food Science and NutritionThe Hebrew UniversityRehovotIsrael
  2. 2.Section In Silico Biology & Machine LearningLeibniz-Institute for Food Systems Biology at the Technical University of MunichFreisingGermany
  3. 3.Department of Chemistry and PharmacyFriedrich-Alexander-University Erlangen-NürnbergErlangenGermany
  4. 4.Department of Transfusion Medicine and HaemostaseologyUniversity HospitalErlangenGermany
  5. 5.Section Chemoreception and BiosignalsLeibniz-Institute for Food Systems Biology at the Technical University of MunichFreisingGermany

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