title: Quantitative modeling of GRK-mediated beta2AR regulation.
abstract: We developed a unified model of the GRK-mediated beta2 adrenergic receptor (beta2AR) regulation that simultaneously accounts for six different biochemical measurements of the system obtained over a wide range of agonist concentrations. Using a single deterministic model we accounted for (1) GRK phosphorylation in response to various full and partial agonists; (2) dephosphorylation of the GRK site on the beta2AR; (3) beta2AR internalization; (4) recycling of the beta2AR post isoproterenol treatment; (5) beta2AR desensitization; and (6) beta2AR resensitization. Simulations of our model show that plasma membrane dephosphorylation and recycling of the phosphorylated receptor are necessary to adequately account for the measured dephosphorylation kinetics. We further used the model to predict the consequences of (1) modifying rates such as GRK phosphorylation of the receptor, arrestin binding and dissociation from the receptor, and receptor dephosphorylation that should reflect effects of knockdowns and overexpressions of these components; and (2) varying concentration and frequency of agonist stimulation "seen" by the beta2AR to better mimic hormonal, neurophysiological and pharmacological stimulations of the beta2AR. Exploring the consequences of rapid pulsatile agonist stimulation, we found that although resensitization was rapid, the beta2AR system retained the memory of the previous stimuli and desensitized faster and much more strongly in response to subsequent stimuli. The latent memory that we predict is due to slower membrane dephosphorylation, which allows for progressive accumulation of phosphorylated receptor on the surface. This primes the receptor for faster arrestin binding on subsequent agonist activation leading to a greater extent of desensitization. In summary, the model is unique in accounting for the behavior of the beta2AR system across multiple types of biochemical measurements using a single set of experimentally constrained parameters. It also provides insight into how the signaling machinery can retain memory of prior stimulation long after near complete resensitization has been achieved.
authors.affiliation: Department of Integrative Biology and Pharmacology, University of Texas Health Science Center, Houston, Texas, United States of America.
authors.forename: Sharat J
authors.initials: SJ
authors.lastname: Vayttaden
authors.forename: Jacqueline
authors.initials: J
authors.lastname: Friedman
authors.forename: Tuan M
authors.initials: TM
authors.lastname: Tran
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Rich
authors.forename: Carmen W
authors.initials: CW
authors.lastname: Dessauer
authors.forename: Richard B
authors.initials: RB
authors.lastname: Clark
mesh_terms: D019393:Arrestin / Q000378:metabolism; D002478:Cells, Cultured; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D054333:Drug Partial Agonism; D054768:G-Protein-Coupled Receptor Kinases / Q000502:physiology*; D006801:Humans; D007700:Kinetics; D008954:Models, Biological; D010744:Phosphoric Monoester Hydrolases / Q000378:metabolism; D010766:Phosphorylation; D011485:Protein Binding; D018343:Receptors, Adrenergic, beta-2 / Q000502:physiology*; D015203:Reproducibility of Results; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D019393:Arrestin; D018343:Receptors, Adrenergic, beta-2; D054768:G-Protein-Coupled Receptor Kinases; D010744:Phosphoric Monoester Hydrolases