13.10.2020 | Webinar: Profiling the pharmacology of G-Protein coupled receptors (GPCR) in cell-based assays using label-free impedance analysis
CardioExcyte 96 Webinar
Date: October 13. 2020
Michael Skiba (University Hospital Regensburg; Germany)
This is an on-demand webinar from Nan]i[on and Friends 2020.
G-protein coupled receptors (GPCRs) are among the most heavily addressed drug targets in medicinal chemistry and pharmacology. It has been estimated that about 40 % of all prescription pharmaceuticals on the market address GPCRs in different target tissues. The screening for new agonists or antagonists has been largely based on assays studying genetically engineered cells for the (i) potential binding of the ligand to their receptors or (ii) the production of second messengers upon receptor activation. Both approaches require invasive experimental procedures. Thus, they need to be performed as endpoint assays that do not reveal the time course of the cell response or details about intrinsic signal amplification. In contrast to that, non-invasive and label-free impedance monitoring has been developed over the last decades providing the response of target cells to receptor activation in real time. The technique is referred to as electric cell-substrate impedance sensing or short ECIS. In ECIS the cells are grown on planar gold-film electrodes that are integrated into regular cell culture dishes. Most recently, these electrode bearing dishes have been made commercially available in standard 96well format. The impedance of the cell-covered electrodes is measured with non-invasive electrical signals and reports on the cell response with a time resolution that is adjustable from minutes to milliseconds. This article will highlight several different approaches how non-invasive impedance measurements are used to characterize the pharmacology of GPCRs in cell-based assays comprising agonist assays, antagonist assays, dose-response relationships, signal transduction profiling and it will introduce a new dosing scheme that increases the experimental throughput significantly.
(Starting at 29:40)