University of Nottingham, UK
Use of NanoBiT complementation technology to investigate ligand signalling and binding kinetics at the human β2 adrenoceptor
The ability to extract fundamental measures of agonist affinity and efficacy from functional data remains a key goal in G protein-coupled receptor (GPCR) pharmacological analysis. Hoare et al (2018)  have described a kinetic operational model (kOM) that enables derivation of agonist binding affinities from functional biosensor data. We and others have previously described a NanoBiT luciferase complementation assay to report real time β-arrestin2 recruitment to GPCRs (NanoBiT  ), and here we evaluate the application of the kOM to these data to estimate β 1 and β 2 adrenoceptor (β 1 AR/β 2 AR) agonist affinities.
In both β 1 and β 2 AR NanoBiT recruitment assays, β-arrestin2 recruitment by ≥5 representative agonists displayed a transient recruitment profile best analysed by the rise and fall kOM. This obtained estimates of each agonist’s affinity as log K A . At both βAR subtypes these estimates were highly correlated with binding data under whole cell conditions  , as well as membrane conditions, with particularly close agreement in actual affinity parameters at the β 2 AR.
The kOM accurately predicted orders of affinity of βAR agonists at multiple βAR subtypes, when applied to real time NanoBiT arrestin assay data. In contrast to other methods, K A estimates are possible from a single agonist concentration response curve experiment, provided timecourses are collected during the assay read. Given the rise and fall kOM assumes instantaneous equilibration of agonist binding to the receptor  , this version of the method may be best suited to GPCR agonists with rapid binding kinetics.
University of California, San Francisco, USA
Large-scale virtual docking screens against GPCRs
Maria Dolores Garcia Fernandez,
Institut de Biologie Structurale Grenoble, France
Peking University, China
Spying on in vivo neuromodulation by constructing GPCR based fluorescent sensors