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. 2017 Jan 3:8:13958.
doi: 10.1038/ncomms13958.

Cannabinoid CB2 receptor ligand profiling reveals biased signalling and off-target activity

Marjolein Soethoudt  1   2 , Uwe Grether  3 , Jürgen Fingerle  4 , Travis W Grim  5 , Filomena Fezza  6   7 , Luciano de Petrocellis  8 , Christoph Ullmer  3 , Benno Rothenhäusler  3 , Camille Perret  3 , Noortje van Gils  2 , David Finlay  9 , Christa MacDonald  9 , Andrea Chicca  10 , Marianela Dalghi Gens  10 , Jordyn Stuart  11 , Henk de Vries  2 , Nicolina Mastrangelo  12 , Lizi Xia  2 , Georgios Alachouzos  1 , Marc P Baggelaar  1 , Andrea Martella  1   2 , Elliot D Mock  1 , Hui Deng  1 , Laura H Heitman  2 , Mark Connor  11 , Vincenzo Di Marzo  8 , Jürg Gertsch  10 , Aron H Lichtman  5 , Mauro Maccarrone  7   12 , Pal Pacher  13 , Michelle Glass  9 , Mario van der Stelt  1
Affiliations

Cannabinoid CB2 receptor ligand profiling reveals biased signalling and off-target activity

Marjolein Soethoudt et al. Nat Commun. .

Abstract

The cannabinoid CB2 receptor (CB2R) represents a promising therapeutic target for various forms of tissue injury and inflammatory diseases. Although numerous compounds have been developed and widely used to target CB2R, their selectivity, molecular mode of action and pharmacokinetic properties have been poorly characterized. Here we report the most extensive characterization of the molecular pharmacology of the most widely used CB2R ligands to date. In a collaborative effort between multiple academic and industry laboratories, we identify marked differences in the ability of certain agonists to activate distinct signalling pathways and to cause off-target effects. We reach a consensus that HU910, HU308 and JWH133 are the recommended selective CB2R agonists to study the role of CB2R in biological and disease processes. We believe that our unique approach would be highly suitable for the characterization of other therapeutic targets in drug discovery research.

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Conflict of interest statement

Industry authors U.G., J.F., C.U., B.R. and C.P. are full-time employees of Hoffmann-La Roche and P.P. is full time employee of NIH. All academic authors state that they have no conflict of interest.

Figures

Figure 1
Figure 1. CB2R selectivity of cannabinoid reference ligands on mouse and human CBRs.
CB2R selectivity for all cannabinoid receptor reference ligands are presented as the difference in mean pKi values between CB2R and CB1R for both the human (black bars) and mouse (white bars) orthologues. From left to right: ligands with decreasing CB2R selectivity (from HU308 to Gp-1a), nonselective ligands (from HU210 to CP55940), ligands with CB1R selectivity (AM251 and SR141716A). pKi values are obtained from three independent experiments performed in duplicate. Error bars shown in the figure represent the s.e. of the mean.
Figure 2
Figure 2. Radarplots of potencies of cannabinoid receptor reference ligands across different assays.
(a) non-selective CBR agonists, (b) selective CB2R agonists, (c) antagonists, (d) endocannabinoids. These plots are a visualization of the differences in potency across different signalling pathways. All potency values are the mean of three independent experiments performed in duplicate.
Figure 3
Figure 3. Heatmap of ΔΔlogR values resulting from the operational analysis.
The operational analysis was performed using the procedure described in the Supplementary Information, with data obtained from three independent experiments performed in duplicate. Dark blue indicates bias towards the first pathway, while dark red indicates bias towards the second pathway. White boxes are not determined. (a) The operational analysis on hCB2R was done with all agonists, except HU210, which was tested in only two functional assays due to legal restrictions. Because of error propagation in the analysis, only a few were found to be statistically significant (P<0.05). (b) The operational analysis on mCB2R was done with the three most selective and most broadly active compounds on hCB2R; HU308, HU910 and JWH133. Here, all three ligands showed statistically significant bias towards G-protein signalling. Statistics was performed with one-way ANOVA Holm-Sidak's multiple comparisons test using Graphpad Prism 6.
Figure 4
Figure 4. Comparison of in vivo cannabimimetic pharmacological effects.
HU210 dose-dependently elicited catalepsy (a), antinociception (b) and hypothermia (c), but HU308, HU910 and JWH133 lacked appreciable pharmacological effects in each assay. Whereas pretreatment with SR141716A (3 mg kg−1) attenuated the magnitude of cataleptic (d), antinociceptive (e) and hypothermic (f) effects of HU210 (1.7 mg kg−1), HU910 did not significantly reduce HU210-induced catalepsy (g), antinociception (h) or hypothermia (i). Filled symbols denote significance versus the respective vehicle injection for each drug (a–c). ****P<0.0001 HU210 versus respective pretreatment (PTx) (Holm-Sidak's test). ^^^^P<0.0001 versus vehicle/HU210 (Holm-Sidak's test). Sample sizes=8 mice/group (a–c) and 6 mice/group (d–i). All values reflect mean ± s.e.m.
Figure 5
Figure 5. Summary of off-target activity.
Summary of the total amount of off-targets per reference ligand. CP55940 is the most nonselective one with 17 off-targets, whereas JWH133 seems to be the most selective of the available agonists. Of the antagonists, SR144528 seems to be the most selective ligand. Off-target activity in the CEREP panel, on serine hydrolases, or on AEA reuptake inhibition is defined as >50% difference in effect compared to basal levels at a concentration of 10 μM and/or a submicromolar potency on the given off-target.
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