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Luciferase Complementation Approaches to Measure GPCR Signaling Kinetics and Bias

G蛋白偶联受体 效应器 荧光素酶 互补 受体 兴奋剂 化学 功能选择性 计算生物学 信号转导 细胞生物学 生物物理学 生物 生物化学 转染 表型 基因
作者
Nicola C. Dijon,Desislava N. Nesheva,Nicholas D. Holliday
出处
期刊:Methods in molecular biology [Springer Science+Business Media]
卷期号:: 249-274 被引量:17
标识
DOI:10.1007/978-1-0716-1221-7_17
摘要

An understanding of the kinetic contributions to G protein-coupled receptor pharmacology and signaling is increasingly important in compound profiling. Nonequilibrium conditions are commonly present in vivo, for example, as the drug competes with dynamic changes in hormone or neurotransmitter concentration for the receptor. Under such conditions individual binding kinetic properties of the ligands can influence duration of action, local ligand concentration, and functional properties such as the degree of insurmountable inhibition. Mapping the kinetic patterns of GPCR signaling events elicited by agonists, rather than a peak response at a single timepoint, is often key to predicting their functional impact. This is also a path to a better understanding of the origins of ligand bias, and whether such ligands demonstrate their effects through selection of distinct GPCR conformations, or via their kinetic properties. Recent developments in complementation approaches, based on a small bright shrimp luciferase Nanoluc, provide a new route to kinetic analysis of GPCR signaling in living cells that is amenable to the throughput required for compound profiling. In the NanoBiT luciferase complementation system, GPCRs and effector proteins are tagged with Nanoluc fragments optimized for their low interacting affinity and stability. The interactions brought about by GPCR recruitment of the effector are reproduced by a rapid and reversible increase in NanoBiT luminescence, in the presence of its substrate furimazine. Here we discuss the methods for optimizing and validating the GPCR NanoBiT assays, and protocols for their application to study endpoint and kinetic aspects of agonist and antagonist pharmacology. We also describe how timecourse families of agonist concentration response curves, derived from a single NanoBiT assay experiment, can be used to evaluate the kinetic components in operational model derived parameters of ligand bias.
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