Pharmacological modulation of cannabinoid type 2 receptor (CB2R) holds promise for the treatment of numerous conditions, including inflammatory diseases, autoimmune disorders, pain, and cancer. Despite the significance of this receptor, researchers lack reliable tools to address questions concerning the expression and complex mechanism of CB2R signaling, especially in cell-type and tissue-dependent context. Herein, we report for the first time a versatile ligand platform for the modular design of a collection of highly specific CB2R fluorescent probes, used successfully across applications, species and cell types. These include flow cytometry of endogenously expressing cells, real-time confocal microscopy of mouse splenocytes and human macrophages, as well as FRET-based kinetic and equilibrium binding assays. High CB2R specificity was demonstrated by competition experiments in living cells expressing CB2R at native levels. The probes were effectively applied to FACS analysis of microglial cells derived from a mouse model relevant to Alzheimer's disease and to the detection of CB2R in human breast cancer cells.

Despite its essential role in the (patho)physiology of several diseases, CB2R tissue expression profiles and signaling mechanisms are not yet fully understood. We report the development of a highly potent,...

Cannabinoid type 2 receptor (CB2R) is a fundamental part of the endocannabinoid signaling system (eCB system), and is known to play an important role in tissue injury, inflammation, cancer and pain. In stark contrast to its significance, the underlying signaling mechanisms and tissue expression profiles are poorly understood. Due to its low expression in healthy tissue and lack of reliable chemical tools, CB2R visualization in live cells remains uncharted. Here we report the development of a drug derived toolbox of highly potent, CB2Rselective fluorescent probes based on reverse design. Extensive validation in several applications such as CB2R detection in flow cytometry and time-resolved imaging, and the development of a novel fluorescent-based TR-FRET assay to generate kinetic and equilibrium binding data demonstrate the high versatility of our toolbox. These probes are the first to preserve affinity and efficacy in both human and mouse CB2R, a crucial aspect for preclinical translatability, and to enable imaging of CB2R internalization in living cells using confocal microscopy.

The G-protein-coupled cannabinoid receptor type 2 (CB2R) is a key element of the endocannabinoid (EC) system. EC/CB2R signaling has significant therapeutic potential in major pathologies affecting humans such as allergies, neurodegenerative disorders, inflammation or ocular diseases. CB2R agonism exerts anti-inflammatory and tissue protective effects in preclinical animal models of cardiovascular, gastrointestinal, liver, kidney, lung and neurodegenerative disorders. Existing ligands can be subdivided into endocannabinoids, cannabinoid-like and synthetic CB2R ligands that possess various degrees of potency on and selectivity against the cannabinoid receptor type 1. This review is an account of granted CB2R ligand patents from 2010 up to the present, which were surveyed using Derwent Innovation®.

The broader and systematic application of a novel scaffold is often hampered by the unavailability of a short and reliable synthetic access. We investigated a new strategy for the design and synthesis of an array of N2‐substituted aza‐2H‐indazole derivatives as potential kinase inhibitors. Guided by a rational ligand alignment approach to qualify the so‐far underrepresented aza‐2H‐indazole scaffold, indazoles were connected at the N2 position with a phenyl spacer and an arylsulfonamide or amide linkage. Initial profiling against a panel of 30 kinases confirmed the in silico predicted selectivity bias. A synthesized focused library of 52 different aza‐2H‐indazole derivatives showed good initial selective inhibition against SGK1, Tie2, and SRC kinases, with the best representatives having IC50 values in the range of 500 nm. In a comparative computational study, these data were analyzed and rationalized in light of docking studies.