Angiotensin II Type 1 Receptor Tachyphylaxis Is Defined by Agonist Residence Time.
Diego A DuarteLucas Tabajara Parreiras-E-SilvaEduardo B OliveiraMichel BouvierClaudio Miguel da Costa-NetoPublished in: Hypertension (Dallas, Tex. : 1979) (2021)
Several GPCRs (G-protein-coupled receptors) have been reported to exhibit tachyphylaxis, which is an acute loss of functional receptor response after repeated stimuli with an agonist. GPCRs are important clinical targets for a wide range of disorders. Therefore, elucidation of the ligand features that contribute to receptor tachyphylaxis and signaling events underlying this phenomenon is important for drug discovery and development. In this study, we examined the role of ligand-binding kinetics in the tachyphylaxis of AT1R (angiotensin II type 1 receptor) using bioluminescence resonance energy transfer assays to monitor signaling events under both kinetic and equilibrium conditions. We investigated AT1R signal transduction and translocation promoted by the endogenous tachyphylactic agonist Ang II (angiotensin II) and its analogs, described previously for inducing reduced receptor tachyphylaxis. Estimation of binding kinetic parameters of the ligands revealed that the residence time of Ang II was higher than that of the analogs, resulting in more sustained Gq protein activation and recruitment of β-arrestin than that promoted by the analogs. Furthermore, we observed that Ang II led to more sustained internalization of the receptor, thereby retarding its recycling to the plasma membrane and preventing further receptor responses. These results show that the apparent lack of tachyphylaxis in the studied analogs resulted from their short residence time at the AT1R. In addition, our data highlight the relevance of complete characterization of novel GPCR drug candidates, taking into account their receptor binding kinetics as well.
Keyphrases
- angiotensin ii
- angiotensin converting enzyme
- vascular smooth muscle cells
- energy transfer
- binding protein
- computed tomography
- liver failure
- drug discovery
- machine learning
- transcription factor
- magnetic resonance imaging
- molecular dynamics simulations
- hepatitis b virus
- deep learning
- single cell
- electronic health record
- aqueous solution
- high speed