For the CB 1 receptor, the potency for internalization increased over time 25. For example, biased signaling of the D 2 dopamine receptor was shown to be time-dependent 24. Of potential concern, drug effect can be dependent on the time point at which the response is measured. Signaling kinetics can also affect quantification of drug activity. Sustained signaling after agonist washout by parathyroid hormone, sphingosine 1-phosphate and thyroid-stimulating hormone receptors revealed signaling by internalized receptors 16, 17, 18, a new spatiotemporal paradigm of GPCR signaling of potential therapeutic utility 19, 20, 21, 22, 23. The classic rise-and-fall time course of cAMP in S49 cells indicated desensitization of β 2 adrenoceptor signaling 15. Measuring the time course of receptor signaling revealed fundamental mechanisms of GPCR function. The time course of GPCR response has been measured since the earliest studies of muscle contraction 1, through the discovery of G-protein-mediated signaling 10, the application of Ca 2+ indicator dyes 11, and the most recent advances in biosensor technology that enable high-throughput signaling kinetic analysis 12, 13, 14. the kinetics/dynamics of response, is currently of considerable interest in quantitative pharmacology. The manner in which GPCR signaling changes over time, i.e.
Signaling assay data are fit to concentration–response equations and the empirical parameters EC 50 and E max used to calculate mechanistic parameters of biased signaling, such as transducer coefficients and log efficacy ratios (reviewed in 9). Biased agonism measurement is an example of this process currently in use by many laboratories. These chemical parameters aid the translation of drug effect measurement from in vitro test systems to animal models and human disease, for example by minimizing the effect of tissue-specific parameters on the quantification of drug activity. efficacy and macroscopic affinity) 3, 4, 5, 6, 7, 8. These parameters can then be used to calculate mechanistic drug parameters that define the effect of the drug on the system in chemical terms (e.g. This analysis is described as “Model-free” because it makes minimal assumptions regarding the mechanism of signal transduction. This yields empirical drug parameters, usually the potency (EC 50) and a measure of the maximal signaling capacity (E max). In the typical analysis process, activity is measured at various drug concentrations and the data fit to a concentration–response equation by curve fitting, for example to a sigmoid curve equation 1, 2, 3. Pharmacological data analysis provides the drug activity parameters used to optimize the biological activity of new therapeutics and to identify mechanisms of receptor-mediated signal transduction for G-protein-coupled receptors (GPCRs). This study extends the empirical and mechanistic approach used in classical pharmacology to kinetic signaling data, facilitating optimization of new therapeutics in kinetic terms. Regulation of signaling parameters such as the receptor desensitization rate constant can be estimated if the mechanism is known. Signaling efficacy is the initial rate of signaling by agonist-occupied receptor ( k τ), simply the rate of signal generation before it becomes affected by regulation mechanisms, measurable using the model-free analysis. receptor desensitization, signal degradation).
It is shown that the four shapes are consistent with a mechanistic model of signaling, based on enzyme kinetics, with the shape defined by the regulation of signaling mechanisms (e.g. In the model-free approach, the initial rate of signaling is quantified and this is done by curve-fitting to the whole time course, avoiding the need to select the linear part of the curve.
A literature survey indicated signaling time course data usually conform to one of four curve shapes: the straight line, association exponential curve, rise-and-fall to zero curve, and rise-and-fall to steady-state curve. Experimental data are analyzed using general time course equations (model-free approach) and mechanistic model equations (mechanistic approach) in the commonly-used curve-fitting program, GraphPad Prism. Here we used a similar approach for kinetic, time course signaling data, to allow empirical and chemical definition of signaling by G-protein-coupled receptors in kinetic terms. EC 50 and E max), which are then used to calculate chemical parameters such as affinity and efficacy. the dose response equation) to determine empirical drug parameters (e.g. In classical pharmacology, bioassay data are fit to general equations (e.g.