Cover Page. The handle holds various files of this Leiden University dissertation

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1 Cover Page The handle holds various files of this Leiden University dissertation Author: Soethoudt, Marjolein Title: Chemical tools to study the cannabinoid receptor type 2 Date:

2 Chapter 4 Cannabinoid Receptor Ligand Profiling Reveals Biased Signaling and Off-target Activity 1 Published in Nature Communications, 2017, 8, 13958

3 Chapter Introduction Target validation is an essential element of pharmacological research and drug discovery (Chapter 1). 2 Pharmacological intervention using chemical probes provides a powerful means to assess the temporal consequences of acute modulation of protein function under both physiological and pathological conditions. 2 High selectivity and a well-defined molecular mode of action of chemical probes are essential to translate the preclinical studies on non-human species to the patient. However, this type of information is often lacking and reproducibility across different laboratories is sometimes difficult to obtain. There is a great interest in the development of selective type-2 cannabinoid receptor (CB2R) agonists as potential drug candidates for various pathophysiological conditions, 3 which include chronic and inflammatory pain, 4,5 pruritus, 6 diabetic neuropathy and nephropathy, 7,8 liver cirrhosis, 9 and protective effects after ischemic-reperfusion injury CB2R belongs to the cannabinoid receptor family of G protein-coupled receptors, which also includes type-1 cannabinoid receptor (CB1R). Both CBRs are the biological target of Δ 9 - tetrahydrocannabinol (Δ 9 -THC), the main psychoactive component in cannabis. 14,15 CB1R and CB2R share an overall sequence homology of 44%, but the 7-transmembrane spanning region, which contains the ligand-binding domain, exhibits 68% similarity. 16 CB2R is predominantly expressed on immune cells and its expression level is believed to increase in tissues upon pathological stimuli, 3 whereas the CB1R is highly expressed in the brain. 17 Both receptors are coupled to Gi/o proteins and modulate various intracellular signal transduction pathways, such as inhibition of camp-production, activation of perk and G protein-coupled inwardly rectifying K + -channels (GIRKs), and recruitment of β-arrestin to the receptor It is currently unknown which signal transduction pathways (or combinations thereof) are relevant for therapeutic purposes. In addition, some compounds may act as biased and/or protean agonists, 19,20 and remarkable differences between rodent and human receptor orthologues have been noted, which are complicating the translation of results from preclinical animal models to human trials. Different chemical classes have been described as CBR ligands (e.g., mixed CBR agonists: Δ 9 -THC (henceforth referred to as THC), CP55940, WIN , HU210, and the endogenous ligands 2-arachidonoyl glycerol (2-AG) and anandamide (AEA, N- arachidonoylethanolamine); CB1R antagonists: SR141716A (rimonabant), and AM251; CB2R agonists: HU308, HU910, Gp-1a, JWH015, JWH133 and AM1241; and CB2R antagonists: AM630 and SR144528; see Figure 1 for structures). 3,21 These ligands are used to explore CBR biology and to obtain preclinical target validation of the CBR subtypes. 22 The high homology between the ligand binding domains of the two receptors and the overall higher tissue expression of CB1R pose challenges to develop selective ligands that target only CB2R. Yet, high selectivity is required to determine the exact role of each receptor in various (patho)physiological processes and to avoid CB1R-mediated (psychotropic) side effects caused by THC and other CB1R ligands. 60

4 Cannabinoid Receptor Ligand Profiling Reveals Biased Signaling and Off-target Activity The need for highly selective CB2 ligands is exemplified by the scientific dispute whether the CB2R plays an important role in normal brain function or not. This whole avenue of research is currently being hampered by possible bias of using non-selective pharmacological and immunological tools and has delayed the development of novel CB2R-based drugs. 23,24 Currently, most ligands are only characterized in a binding assay and/or in a limited set of functional assays using recombinant human receptors. The results are scattered among various publications and are derived from different experimental settings, which may have led to apparent contradictory results. 24 Conflicting results from in vivo models that employ some of the above mentioned ligands have also been described in the literature. 3,25 Often, information about potential off-targets and pharmacokinetics of ligands is also lacking. 20 This has complicated the comparison and interpretation of the data and led to confusion about which are the preferred ligands to be used for in vivo experiments aimed at validating the CB2 receptor as a therapeutic target. Unfortunately, this situation, which has resulted in a loss of resources and unnecessary use of animals, is not unique to the CB2 receptor field. The US National Institutes of Health (NIH) shares these concerns from many scientists about the reproducibility issues in biomedical research and required action to counter this problem. 26 To improve target validation and to guide the selection of the best ligand for preclinical studies, a fully detailed profile of the current gold standard ligands is needed. To provide important guidance for the field and to address potential speciesdependent differences, the most widely used CB2R ligands were comprehensively profiled. Receptor binding of both human and mouse CB2R was investigated in several independent academic and industry laboratories, as well as multiple signal transduction pathways (GTPγS, camp, β-ar, perk and GIRK). Selectivity of the ligands was determined towards a customized panel of proteins associated with cannabinoid ligand pharmacology, which includes the CB1R and the major proteins of the endocannabinoid system (ECS): N-Acyl ethanolamines biosynthesizing enzyme N-acyl phosphatidylethanolamine-specific phospholipase D (NAPE-PLD) and AEA hydrolyzing enzyme fatty acid amide hydrolase (FAAH); 2-AG bio-synthesizing enzyme diacylglycerol lipase (DAGL) and -hydrolyzing enzymes monoacylglycerol lipase (MAGL) and α/β-hydrolase domain 6 and 12 (ABHD6 and ABHD12), as well as towards the putative endocannabinoid transporters; AEA and 2-AGbinding transient receptor potential channels (TRP-channels, TRPV1-4, TRPM8, and TRPA1). 27 In addition, off-target activity on GPR55, a receptor that binds CBR-type ligands, and on COX-2, which oxygenates AEA and 2-AG, was also determined. Determination of the selectivity of CB2R ligands over these other proteins and processes involved in the endocannabinoid system, as well as over the TRP channels (which are involved in similar biological processes as the CBRs) is essential for the development of selective CB2R ligands and to avoid complications in the interpretation of the in vivo results obtained with these compounds. Chapter 4 61

5 Chapter 4 To assess which ligands are best suited for in vivo studies, all 18 compounds were profiled for their physico-chemical properties, in vitro ADME (absorption, distribution, metabolism, elimination) and pharmacokinetic parameters and cross-reactivity in the CEREP panel of 64 common off-targets. Commonly used non-selective ligands, including Δ9-THC and the endocannabinoids 2-AG and anandamide were also tested in vitro. All ligands were high quality grade material, provided to each laboratory by the industry collaborator. The top three candidate CB2R agonists were further investigated at high doses in vivo to infer potential interactions with CNS CB1R. All data together results in the largest dataset generated so far under the same experimental conditions for all cannabinoid receptor ligands, leading to a consensus that HU910, HU308 and JWH133 possess the best CB2R agonist profiles among the ligands tested on the basis of selectivity, balanced signaling, pharmacokinetic profile and off-target activity, and may be considered golden standards for CB2R validation studies in mice. Figure 1. Structures of references ligands divided per class as described in the introduction 4.2 Results Physico-chemical properties The physico-chemical properties of the 18 compounds tested are listed in Table 1. 62

6 Cannabinoid Receptor Ligand Profiling Reveals Biased Signaling and Off-target Activity Molecular weights span a range from 312 g/mol for JWH133 up to 555 g/mol for AM251 and the polar surface area values are overall very low (8 Å for JWH133 up to 63 Å for (S)- AM1241), due to a low number of heteroatoms present in the ligands. Importantly, all CBR ligands are very lipophilic molecules, which negatively affects their solubility, ADMEproperties and off-target profile. Even the lowest lipophilicity value (clogp), calculated to be 4.9 for WIN , is relatively high. The most lipophilic CBR ligand is SR144528, which exhibits an extremely high clogp value of 9.2. Consequently, only CP55940 and (rac)- AM1241 were soluble in an aqueous phosphate buffer system (ph 6.5). Despite the fact that the membrane permeation coefficient (PAMPA) Peff is low for several of the molecules, most compounds may be able to cross biological barriers as high percentages of the substances were found in membranes. Table 1. Physicochemical properties of ligands MW (g/mol) Polar surface area a (Å) Kow clogp b logd c, j PAMPA Peff d, j [cm/s*10-6 ] Pct acceptor e, j [%] Pct donor f, j [%] Pct membrane g, j [%] Kinetic solubility h, k [µg/ml] Kinetic solubility h, k [µmol/ml] Solubility in 15% DMSO, 85% PEG400 i, l [µg/ml] Solubility in 15% DMSO, 85% PEG400 i, l [µmol/ml] WIN ± ± <0.3 < CP ND ± ND ND Δ 9 -THC ND ND ND ND ND ND ND ND ND HU precipitation <0.2 < ND ND SR141716A > ± < < AM ND <0.3 < JWH ND ND ND ND ND <0.2 < JWH >3 precipitation <0.4 < HU <0.75 < Gp-1a ND <0.2 < HU out of range < ND ND (rac)- AM ± ± ± ±0.004 ND ND (R)-AM ND ND (S)-AM AM <0.3 < SR > <0.2 < Anandamide out of range <1.1 < ND ND 2-AG ND ND ND ND ND <0.5 < ND ND a Surface sum of all polar atoms in the molecule; b Calculated partition coefficient values (clogp) from experimentally determined octanolwater partition coefficient values (Kow); c Distribution coefficient values; d Parallel artificial membrane permeability assay (PAMPA) was used to determine membrane permeation coefficient values (Peff); e Percentage of molecule that is able to act as a hydrogen bond acceptor; f Percentage of molecule that is able to act as a hydrogen bond donor; g Percentage of compounds found in membranes; h Solubility of the compound when diluted into aqueous environment from DMSO superstock; i Solubility of the compound in the formulation used for in vivo administration of the ligands; j Mean ± SD of three independent experiments; k Mean of two independent experiments; l Single experiment Chapter Affinity and selectivity in CBR binding studies To determine the affinity and selectivity of the 18 substances, [ 3 H]-CP55940 displacement assays using membrane fractions of Chinese Hamster Ovary (CHO) cells overexpressing recombinant human CB2R and CB1R were performed in two independent laboratories. In addition, mouse brain and spleen were used as source of mouse CB1R and CB2R, respectively. 63

7 Chapter 4 Using the Pearson correlation analysis, a statistically significant correlation was found between the binding affinities between the different labs (Pearson coefficient: (hcb1r), (hcb2r) and (mcb2r), see Figure 2). Figure 2. Correlation of binding affinities between labs. The affinities of THC and HU210 could not be compared since these were not measured in all labs due to legal restrictions. A-B) Correlation of binding affinities of reference compounds separately determined by the labs of Roche and Leiden on hcb1r (A) and hcb2r (B). C) Correlation of binding affinities of reference compounds separately determined by the labs of Roche and Mauro Maccarronne on mcb2r. A-C) Statistics performed was two-tailed Pearson correlation analysis. All pki values presented here are displayed as mean ± SEM of three independent experiments performed in duplicate (N=3, n=2). Figure 3 depicts the selectivity of the ligands for the CB2R versus CB1R. HU210 > CP55940, WIN > 9 -THC were found as the highest affinity non-selective human CBR ligands. Figure 3. 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, Leiden data) and mouse (white bars, Maccarrone data) 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). 64

8 Cannabinoid Receptor Ligand Profiling Reveals Biased Signaling and Off-target Activity Conversely, HU308, HU910 and JWH133 were the most selective human CB2R ligands (Table 2), possessing 278-, 166-, and 153-fold higher respective affinities for CB2R than for CB1R. Notably, JWH015 and Gp-1a were less than 30-fold selective for CB2R. Importantly, the binding selectivity of the ligands for mouse CB2R over mouse CB1R appeared to be greatly reduced for all ligands (<100 fold), except AM630 and SR144528, which are actually more selective on mcb2r than on hcb2r. The most selective agonists on mcb2r were (rac)- AM1241 (66-fold), JWH133 (40-fold) and Gp-1a (20-fold). As expected, AEA and 2-AG, the endogenous ligands of CB1R and CB2R, were non-selective and showed moderate binding affinities towards both receptors (pki ~7). Table 2. Binding affinity and selectivity of reference ligands on human and mouse cannabinoid receptors. hcb2r hcb1r CB2R Selectivity* mcb2r mcb1r CB2R Selectivity* WIN ± ± ± ± CP ± ± ± ± Δ 9 -THC 8.16 ± ± ND ND HU ± 0.04 a 9.55 ± 0.06 a ± ± SR141716A 5.60 ± ± ± ± AM ± ± ± ± JWH ± ± ± ± JWH ± 0.34 < ± ± HU ± 0.12 < ± ± Gp-1a 7.66 ± ± ± ± HU ± 0.31 < ± ± (rac)-am ± ± ± ± (R)-AM ± ± ± ± (S)-AM ± 0.15 < ± ± AM ± ± ± ± SR ± 0.06 a 5.77 ± 0.09 a ± ± Anandamide 6.91 ± ± 0.28# ± ± AG 6.94 ± ± 0.47# ± ± pki values are presented as the mean ± SEM (N=3, n=2), unless stated otherwise; Data sets from Leiden (human) and Maccarrone (mouse), unless stated otherwise; *CB2R selectivity was calculated as follows: 10^(pKi CB2R-pKi CB1R); # Mean ± SEM of 4 independent experiments performed in duplicate; a Dataset from Roche Chapter Functional activity and selectivity of CBR signaling pathways To determine the functional activity and selectivity (towards CB2R over CB1R) of the ligands five different assays (GTPγS, camp, β-ar, perk and GIRK) were performed on both human CB2R and human CB1R (Tables 3-7). All ligands were tested on camp signaling on both mouse CBRs and HU910, HU308 and JWH133 were tested on G protein activation and β- Arrestin recruitment on mcb2r, to determine interspecies behaviour of the ligands. Efficacy of the ligands is normalized to the effect produced by CP55940 (10 µm) in all assays. However, it should be noted that efficacy is relative by definition, and is dependent on the reference ligand used as well as the assay conditions. For both human and mouse CB2R, the potency of the ligands correlated with their binding affinity in most assays, except for β-ar and GIRK signaling (Figure 4). 65

9 Chapter 4 Figure 4. Correlation between binding affinity and functional potency. (A-E) Correlation between hcb2r affinity (Leiden dataset) of the reference compounds with their functional potencies in the different assays. F) Correlation between mcb2r affinity of the reference compounds with their functional potencies in the camp assay. Maccarrone dataset (P-value , Pearson coefficient ); Roche dataset (P-value , Pearson coefficient After exclusion of compounds (Rac)-AM1241 and (R)-AM1241, which seem to be inactive in their mouse camp assay: P-value , Pearson coefficient ). Statistics performed was twotailed Pearson correlation analysis. All values are presented as mean ± SEM (N=3, n=2). Graphs showing the pec50 values of the reference ligands on CB2R in all assays are shown in Figure 5A-D. CP55940 and HU308 behaved as potent full agonists at hcb2r in the GTPγS assay (Table 3), while WIN acted as a partial agonist. HU910 behaved as a partial CB2R agonist as well, but was, together with HU308, the most selective for CB2R in this assay (185- and 193-fold, respectively). Of note, JWH133 was considered functionally inactive on hcb1r, because its maximal effect was only 20% at 10 µm. On mcb2r, both HU308 and JWH133 were full agonists, but HU910 remained partially active. The potency of all three ligands was similar for human and mouse receptors. In contrast to previous reports, 28,29 Gp- 1a acted as an inverse agonist on CB2R, but was inactive at CB1R. Both THC and the endocannabinoids AEA and 2-AG acted as partial agonists on both receptors with similar potency. 66

10 Figure 5. CB2R potencies of cannabinoid receptor reference ligands across different assays. A) Mixed CBR agonists, B) selective CB2R agonists, C) antagonists, D) endocannabinoids. Chapter 4 67

11 Chapter 4 Table 3. Functional potency, efficacy and selectivity in the GTPγS assay. hcb2r hcb1r mcb2r hcb2r Selectivity* pec50 ± SEM Emax ± SEM pec50 ± SEM Emax ± SEM pec50 ± SEM Emax ± SEM WIN ± ± ± ± 6 2 ND ND CP ± ± ± ± ± ± 1 Δ9-THC 7.07 ± ± ± ± ND ND HU210 ND ND ND ND ND ND SR141716A 5.66 ± ± ± ± ND ND AM ± ± ± ± ND ND JWH ± ± 16 <5 19 ± 2 51 ND ND JWH ± ± ± ± ± ± 7 HU ± ± 12# <5 17 ± ± ± 3 Gp-1a 7.09 ± ± 5 <5-7 ± ND ND HU ± ± 13 <5-16 ± ± ± 4 (rac)- AM ± ± ± ± ND ND (R)-AM ± ± ± ± 8 4 ND ND (S)-AM ± 5# <5 9 ± 4 ND ND AM ± ± 2 <5-1 ± 1 56 ND ND SR ± ± 2 <5 10 ± ND ND Anandamide 6.37 ± ± 4# 6.35 ± ± 8# 1 ND ND 2-AG 6.19 ± ± 11# 6.85 ± ± 20# 0.2 ND ND All values are presented as the mean ± SEM (N=3, n=2), unless stated otherwise; *CB2R selectivity was calculated as follows: 10^(pEC50 CB2R-pEC50 CB1R); The effect of agonists is normalized to the effect of 10 µm CP55940; Negative Emax values represent inverse agonism; #Emax, but no plateau observed; Effect at 10 µm; ND = not determined In the camp assay (Table 4) all CB 2R agonists displayed higher selectivity (> 1000-fold) and higher efficacy, than in the GTPγS-assay, reflecting substantial signal amplification in this pathway. Only (rac)-am1241 remained a partial agonist in the camp assay. Upon comparison of the efficacy of the ligands between species, in general it appears that many ligands on the mouse CBRs are partial agonists on camp, in contrast to the human CBRs. This difference in efficacy might be a result of a difference in CBR expression levels. Differences in expression levels may also account for the interspecies differences displayed by (rac)-am1241, which was previously reported as a protean agonist (a protean agonist shows differences in signaling due to differences in experimental conditions, whereas a true biased agonist has signaling preference due to conformational changes of the receptor). 30 HU910 was found to bind with similar affinity to both mouse CBRs, but was inactive on mcb 1R in the camp assay. HU308, JWH015 and (rac)-am1241 were the most selective agonists for hcb 2R in this assay, whereas CP55940, WIN and HU210 displayed the highest potency. HU910, HU308 and JWH133 were the most selective on the mcb 2R. Of note, AEA and 2-AG were relatively weak partial agonists, especially on human and mouse CB 1R (pec 50 <5.2 and E max <70%). All ligands modulated β-ar recruitment (Table 5) to the membrane in CHO cells expressing human CB2R or CB1R (Chapter 3). CP55940 was the most potent ligand in this assay, followed by WIN CP55940 acted as full agonist at both receptors, but WIN displayed partial agonism at CB2R, as in the GTPγS assay. The other agonists, including the ligands JWH133, JWH015, HU308, HU910 (Emax 50-70%) and the endocannabinoids (Emax 40-80%), only partially recruited β-ar. The most selective CB2R agonists were HU308, JWH133 and HU910, which were found to be 282-, 275- and 274-fold more potent for CB2R than CB1R. Of note, JWH133, HU308 and HU910 were all significantly less potent on mcb2r in β-ar recruitment. 68

12 Table 4. Functional potency, efficacy and selectivity in the camp assay. hcb2r hcb1r mcb2r mcb1r pec50 ± SEM Emax ± SEM pec50 ± SEM Emax ± SEM hcb2r Selectivity* pec50 ± SEM Emax ± SEM pec50 ± SEM Emax ± SEM mcb2r Selectivity* WIN ± ± ± ± ± ± CP ± ± ± ± ± ± Δ 9 -THC ND ND ND ND ND ND - ND - ND HU ± ± ± ± ± ± SR141716A 6.83 ± ± ± ± ± ± AM ± ± ± ± ± < JWH ± ± 1 <5 28 ± ± < JWH ± ± 1 <5 37 ± ± < HU ± ± 1 <5 18 ± ± < Gp-1a 7.52 ± ± 10 <5 19 ± ± ± HU ± ± 1 <5 28 ± ± < (rac)-am ± ± 3 <5 n.a ± < (R)-AM ± ± ± ± ± ± (S)-AM ± ± 1 <5 16 ± ± ± AM ± ± 13 <5 28 ± ± < SR ± ± 10 <5 n.a ± ± Anandamide 5.93 ± ± 7 <5 39 ± ± ± AG 6.82 ± ± 1 <5 n.a ± ± All values are presented as the mean ± SEM (N=3, n=2), unless stated otherwise; Human dataset from Roche, mouse data set from Maccarrone; *CB2R selectivity was calculated as follows: 10^(pEC50 CB2R-pEC50 CB1R); The effect of agonists is normalized to the effect of 10 µm CP55940; The potency of antagonists/inverse agonists is determined in presence of the EC80 of CP55940; Effect at 10 µm; n.a.: not active; ND = not determined Chapter 4 69

13 Chapter 4 Table 5. Functional potency, efficacy and selectivity in the β-ar recruitment assay. hcb2r hcb1r CB2R mcb2r pec50 ± SEM Emax ± SEM pec50 ± SEM Emax ± SEM Selectivity* pec50 ± SEM Emax ± SEM WIN ± ± ± ± 2 15 ND ND CP ± ± ± ± ± ± 1 Δ 9 -THC - 31 ± 3# 6.29 ± ± 3 - ND ND HU210 ND ND ND ND ND ND ND SR141716A 5.61 ± ± ± ± ND ND AM ± ± ± ± ND ND JWH ± ± ± ± 2 51 ND ND JWH ± ± ± ± ± ± 7 HU ± ± 10 <5 5.0 ± ± ± 3 Gp-1a 5.86 ± ± 11 <5-83 ± 7 13 ND ND HU ± ± ± ± ± ± 1 (rac)-am1241 <5 14 ± 2 <5 6 ± 5 1 ND ND (R)-AM ± ± ± ± 2 86 ND ND (S)-AM ± ± 8 <5 2 ± 1 35 ND ND AM ± ± ± ± 25 4 ND ND SR ± ± ± ± ND ND Anandamide 6.21 ± ± 3-36 ± 13# - ND ND 2-AG 5.70 ± ± ± 21# - ND ND All values are presented as the mean ± SEM (N=3, n=2), unless stated otherwise; *CB2R selectivity was calculated as follows: 10^(pEC50 CB2R-pEC50 CB1R); The effect of agonists is normalized to the effect of 10 µm CP55940; The potency of antagonists/inverse agonists is determined in presence of the EC80 of CP55940; Negative values represent inhibition of the EC80 of CP55940 (>-100, indication of inverse agonism); Effect at 10 µm; # Emax at 10 µm treatment, no plateau observed; n.a.: not active; ND = not determined WIN was a full agonist in the perk assay (Table 6) and demonstrated 85-fold selectivity for the human CB2R, whereas CP55940 lacked selectivity in this assay. HU308 and JWH133 were potent and selective CB2R full agonists, whereas Δ 9 -THC and (rac)-am1241 acted as partial agonists on the perk signaling cascade. Interestingly, HU910, AEA and 2-AG had low potency in this assay (pec50 < 5.5), but HU910 and 2-AG acted as full agonists at high concentrations. Table 6. Functional potency, efficacy and selectivity in the perk assay. hcb2r hcb1r pec50 ± SEM Emax ± SEM pec50 ± SEM Emax ± SEM CB2R Selectivity* WIN ± ± ± ± 7 85 CP ± ± ± ± 8 1 Δ 9 -THC 6.7 ± ± ± ± HU ± ± ± ± SR141716A 4.13 ± ± ± ± AM ± ± ± ± JWH015 ND ND ND ND - JWH ± ± 13 <4 10 ± HU ± ± 2 <4 18 ± Gp-1a n.a. 5 ± 6 n.a. 2 ± 3 1 HU ± ± 9 <4 12 ± 4 32 (rac)-am ± ± ± ± (R)-AM ± ± ± ± (S)-AM ± ± 11 <4 17 ± AM ± ± 4 <4-40 ± 2 12 SR ± ± 3 <4-21 ± 2 74 Anandamide 5.41 ± ± ± ± AG 5.41 ± ± ± ± 10 2 All values are presented as the mean ± SEM (N=3, n=2), unless stated otherwise; *CB2R selectivity was calculated as follows: 10^(pEC50 CB2R-pEC50 CB1R); The effect of agonists is normalized to the effect of 10 µm CP55940; The potency of antagonists/ inverse agonists is determined in presence of the EC80 of CP55940; Effect at 10 µm; n.a.: not active; ND = not determined 70

14 Cannabinoid Receptor Ligand Profiling Reveals Biased Signaling and Off-target Activity Most ligands appeared to be less potent and less CB2R-selective in the GIRK assay (Table 7). For example, neither JWH133 nor THC activated the GIRK pathway at all. JWH015 was the most selective agonist in this assay, followed by HU308. WIN and CP55940 activated the GIRK channels with the highest potency, but as expected, both were highly potent and efficacious at CB1R as well. Table 7. Functional potency, efficacy and selectivity in the GIRK assay. hcb2r hcb1r pec50 ± SEM Emax ± SEM pec50 ± SEM Emax ± SEM CB2R Selectivity* WIN ± ± ± ± 6 15 CP ± ± Δ 9 -THC <5 10 ± ± ± HU ± ± ± ± 8 1 SR141716A 5.24 ± ± AM ± ± JWH ± ± 3 <5 18 ± JWH133 <5 31 ± 12 <5 5 ± 1 1 HU ± ± 6 <5 15 ± Gp-1a 5.99 ± ± HU ± ± 2 <5 7 ± 5 7 (rac)-am ± ± 14 <5 36 ± 4 2 (R)-AM1241 <5 47 ± ± ± 3 1 (S)-AM ± ± 13 <5 19 ± 3 4 AM ± ± SR ± <5 9 ± 4 2 Anandamide 5.29 ± ± ± ± AG 6.51 ± ± ± ± 11 1 All values are presented as the mean ± SEM (N=3, n=2), unless stated otherwise; *CB2R selectivity was calculated as follows: 10^(pEC50 CB2R-pEC50 CB1R); The effect of agonists is normalized to the effect of 10 µm CP55940; The potency of antagonists/inverse agonists is determined in presence of the EC80 of CP55940; Effect at 10 µm; ND = not determined Chapter 4 The high variability in potency and efficacy that the CB2R agonists displayed across the different signaling pathways strongly suggests biased signaling. To quantify this ligand bias towards distinct signal transduction pathways, operational analysis was performed based on van der Westhuizen et al. (Tables 8-11). 31 This analysis is based on the operational model of Black and Leff, 32 which calculates signal transduction strength on a given pathway, taking into account a) the maximal effect of the system used, b) the agonist concentration, c) the agonist s maximum efficacy, d) the ligand affinity for the receptor and e) the transducer slope. 71

15 Table 8. Transduction ratios (logr) of the cannabinoid ligand library on hcb2r. β-ar GTPγS perk GIRK camp LogR ΔLogR LogR ΔLogR LogR ΔLogR LogR ΔLogR LogR ΔLogR WIN ± ± ± ± ± ± ± ± ± ± 0.10* JWH ± ± ± ± 0.39* 7.07 ± ± 0.24* 5.98 ± ± 0.41* 8.28 ± ± 0.09* HU ± ± ± ± ± ± 0.26* 5.90 ± ± 0.18* 8.37 ± ± 0.09* CP ± ± ± ± ± ± ± ± ± ± 0.09 HU ± ± ± ± ± ± 0.26* 6.281± ± 0.14* 8.49 ± ± 0.08* (rac)-am ± ± ± ± 0.42* 8.67 ± ± ± ± 0.20* ND ND (S)-AM ± ± 0.28* 6.9 ± ± ± ± 0.33* 5.70 ± ± 0.17* ND ND (R)-AM ± ± 0.27* 7.3 ± ± ± ± ± ± 0.25* ND ND JWH ± ± 0.13* 5.96 ± ± 0.4* ND ND 6.78 ± ± 0.11* 8.45 ± ± 0.09* AEA 5.54 ± ± 0.23* 4.54 ± ± 0.58* 6.03 ± ± 0.32* 4.53 ± ± 0.29* 5.96 ± ± 0.18* 2-AG 5.9 ± ± 0.15* 4.63 ± ± 0.43* 6.37 ± ± 0.26* 6.40 ± ± 0.12* 6.99 ± ± 0.18# Δ 9 -THC 5.5 ± ± 0.28* 4.51 ± ± 0.77* 7.89 ± ± 0.51 ND ND ND ND HU210 ND ND ND ND 8.22 ± ± ± ± 0.11* ND ND Normalized dose-response data (N=3, n=2, or camp: AEA (N=2, n=2), camp: 2-AG (N=1, n=2)) were analyzed using the operational model to determine LogR values. ΔlogR values were calculated for each ligand using CP55940 as the reference ligand with equation 1 and the standard errors of the ΔlogR values with equation 2 (See Experimental Section). Statistics performed was one-way ordinary ANOVA; ND = not determined; * P-value < 0.05; # No statistical analysis performed Table 9. Transduction ratios (logr) of the cannabinoid ligand library on mcb2r. β-ar GTPγS camp LogR ΔLogR LogR ΔLogR LogR ΔLogR CP ± ± ± ± ± ± 0.20 HU ± ± 0.12* 6.77 ± ± 0.07* 8.07 ± ± 0.26* HU ± ± 0.12* 7.15 ± ± 0.08* 8.48 ± ± 0.23* JWH ± ± 0.13* 7.07 ± ± 0.07* 8.07 ± ± 0.17* Normalized dose-response data (N=3, n=2) were analyzed using the operational model to determine LogR values. ΔlogR values were calculated for each ligand using CP55940 as the reference ligand with equation 1 and the standard errors of the ΔlogR values with equation 2 (See Experimental Section). Statistics performed was one-way ordinary ANOVA; * P-value <

16 Table 10. ΔΔlogR values and bias factor for the reference library between pathways on hcb2r. β-ar-gtpγs β-ar-perk β-ar-girk β-ar-camp perk-gtpγs perk-girk perk-camp GIRK-GTPγS GIRK-cAMP GTPγS-cAMP ΔΔlogR (BF) ΔΔlogR (BF) ΔΔlogR (BF) ΔΔlogR (BF) ΔΔlogR (BF) ΔΔlogR (BF) ΔΔlogR (BF) ΔΔlogR (BF) ΔΔlogR (BF) ΔΔlogR (BF) WIN JWH133 HU910 CP55940 HU308 (rac)-am1241 (S)-AM1241 (R)-AM1241 JWH015 AEA 2-AG Δ 9 -THC 0.4 ± 0.47 (2.49) 1.53 ± 0.41 (33.81) 0.67 ± 0.32 (4.71) 0 ± 0.34 (1.00) 0.55 ± 0.32 (3.54) 1.83 ± 0.61 (68.30) ± 0.57 (0.07) ± 0.54 (0.49) 1.44 ± 0.42 (27.80) 0.79 ± 0.62 (6.10) 1.05 ± 0.45 (11.27) 0.77 ± 0.82 (5.90) ± 0.27 (0.22) 1.48 ± 0.27 (30.41) 1.31 ± 0.29 (20.56) 0 ± 0.25 (1.00) 0.71 ± 0.29 (5.08) ± 0.81 (0.65) ± 0.44 (0.09) ± 0.39 (0.41) ND 0.04 ± 0.39 (1.11) 0.07 ± 0.3 (1.16) ± 0.58 (0.01)* ± 0.15 (0.70) 1.41 ± 0.43 (25.53)* 1.18 ± 0.22 (15.07) 0 ± 0.1 (1.00) 0.80 ± 0.19 (6.37) 1.8 ± 0.49 (62.37)* ± 0.33 (0.43) 1.08 ± 0.36 (12.13) 0.21 ± 0.17 (1.61) 0.38 ± 0.37 (2.37) ± 0.19 (0.07) 0.91 ± 0.15 (8.2)* 1.96 ± 0.15 (90.36)* 1.57 ± 0.15 (36.90)* 0 ± 0.12 (1.00)* 1.43 ± 0.16 (27.16)* ND ND ND 1.38 ± 0.15 (24.10)* 1.80 ± 0.29 (62.52)* 1.12 ± 0.23 (13.03)# ND ND 1.05 ± 0.51 (11.30) 0.05 ± 0.46 (1.11) ± 0.39 (0.23) 0 ± 0.41 (1.00) ± 0.39 (0.70) 2.01 ± 0.8 (103.28) ± 0.59 (0.77) 0.07 ± 0.55 (1.18) 0.51 ± 0.26 (3.24) ± 0.48 (0.84) ± 0.32 (0.73) 0 ± 0.25 (1.00) 0.1 ± 0.3 (1.25) 1.98 ± 0.71 (95.72)* 0.68 ± 0.37 (4.72) 1.47 ± 0.37 (29.32) 1.57 ± 0.26 (37.24)* 0.47 ± 0.26 (2.97) 0.25 ± 0.28 (1.77) 0.55 ± 0.46 (3.55) 0.12 ± 0.57 (1.32) ± 0.34 (0.31) 1.07 ± 0.14 (11.69)* 0.55 ± 0.42 (3.54) 0.38 ± 0.20 (2.42) 0.52 ± 0.46 (3.30) 0.43 ± 0.40 (2.67) 0.89 ± 0.31 (7.73) 0 ± 0.26 (1.00) 0 ± 0.34 (1.00) 0 ± 0.12 (1.00) 0 ± 0.34 (1.00) 0.73 ± 0.27 (5.42) ND ND ND ND ND ND 0.74 ± 0.66 (5.50) 0.99 ± 0.5 (9.68) 2.63 ± 0.92 (426.58)* HU210 ND ND ND ND ND 0.33 ± 0.43 (2.14) -1.2 ± 0.29 (0.06) 1.75 ± 0.37 (56.36)* 1.05 ± 0.31 (11.19)# ± 0.32 (0.56) 0.03 ± 0.46 (1.08) ± 0.52 (0.16) ± 0.53 (0.04) 1.24 ± 0.42 (17.26) 0.41 ± 0.65 (2.57) 2.19 ± 0.44 (154.53)* 0.64 ± 0.17 (4.33) 0.89 ± 0.30 (7.78) ND ND ND ND ND ND 1.18 ± 0.14 (14.96)* 1.42 ± 0.34 (26.36)* 2.25 ± 0.21 (178.65)# ± 0.41 (0.87) 1.01 ± 0.41 (10.26) 0.06 ± 0.46 (1.16)# ND ND ND ND ND ± 0.27 (0.71) ND ND ND ND Normalized dose-response data (N=3, n=2, or camp: AEA (N=2, n=2), camp: 2-AG (N=1, n=2)) were analyzed using the operational model to determine LogR values. ΔlogR values were calculated for each ligand using CP55940 as the reference ligand with equation 1 and the standard errors of the ΔlogR values with equation 2 (See Experimental Section), ΔΔlogR values are calculated using the ΔlogR values (Table 8) using equation 4, the standard errors of the ΔΔlogR values with equation 5, and the bias factor (BF) using equation 6. Statistics performed was one-way ordinary ANOVA; ND = not determined; * P-value < 0.05; # No statistical analysis performed Chapter 4 73

17 Chapter 4 Table 11. ΔΔlogR values and bias factor for the cannabinoid ligand library between pathways on mcb2r. β-ar-gtpγs β-ar-camp GTPγS-cAMP ΔΔlogR (BF) ΔΔlogR (BF) ΔΔlogR (BF) CP ± 0.10 (1) 0 ± 0.21 (1) 0 ± 0.21 (1) HU ± 0.13 (0.19)* 0.69 ± 0.28 (4.9) 1.41 ± 0.27 (25.8)* HU ± 0.15 (0.18)* 0.63 ± 0.26 (4.2) 1.37 ± 0.24 (23.6)* JWH ± 0.15 (0.21)* 1.04 ± 0.21 (10.9)* 1.71 ± 0.18 (50.9)* Normalized dose-response data (N=3, n=2) from different assays were analyzed using the operational model to determine LogR values (see Experimental Section Table 9) using equation 4, the standard errors of the -way ordinary ANOVA.* P-value < 0.05 In order to eliminate system and observation bias, such as the level of amplification between signaling pathways or assay sensitivity, CP55940 was used as a reference compound, because it was the only compound that behaved as a full agonist with comparable potency in all assays, except for the camp assay. The logr values resulting from this operational analysis are graphically shown in Figure 6. Figure 6. Heatmap of ΔΔlogR values resulting from the operational analysis. The operational analysis was performed with normalized data (N=3, n=2) using the procedure described in the Experimental Section. Blue indicates bias towards the first pathway, while 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. Statistics was performed with one-way ANOVA Holm-. 74

18 Cannabinoid Receptor Ligand Profiling Reveals Biased Signaling and Off-target Activity The operational analysis on hcb2r revealed that THC showed statistically significant bias towards perk signaling compared to β-arrestin and GTPγS. In addition, THC did not activate GIRK, indicative of high bias against this pathway. (rac)-am1241 was biased towards β- arrestin coupling and perk signaling compared to GIRK channel activation. JWH133 was moderately biased towards β-arrestin compared to GIRK, whereas both WIN and JWH015 showed preference for GIRK compared to camp signaling. AEA showed preference for perk and GIRK signaling compared to camp, whereas 2-AG was significantly biased towards GIRK compared to G protein signaling. Upon comparison between β-ar coupling and camp signaling, all ligands appear to be significantly biased. This observation is, however, confounded by the fact that CP55940, which is used as the reference ligand, has an exceptionally high potency in the camp assay compared to the other signal transduction pathways, and might be in fact biased itself towards the camp pathway. Of note, HU910 and HU308 were well-balanced ligands without significant bias towards any signal transduction pathway on hcb2r. Of note, HU910, HU308 and JWH133 were significantly biased towards G protein signaling over β-ar coupling and camp signaling on the mcb2r highlighting a potentially important species difference Off-target activity in the Endocannabinoid System To rule out any indirect effects of the ligands on CB1R and CB2R, off-target activity was investigated on endocannabinoid-regulating enzymes, as well as their effects on AEA reuptake inhibition. None of the ligands showed any off-target activity on a panel of serine hydrolases, determined in a competitive activity-based protein profiling (ABBP) assay in mouse brain proteome up to a concentration of 10 µm (Figure 7). Chapter 4 Figure 7. Off-target activity of reference ligands on a panel of serine hydrolases. A) The reference ligands were tested in a panel of serine hydrolases in a competitive ABBP assay in mouse brain proteome at a concentration of 10 µm. Shown is an example gel, with MB064 as the probe used in a concentration of 250 nm, as described previously in Baggelaar et al. 33 Gel experiments were repeated twice with independently weighed compounds stocks In addition, none of the ligands showed any significant effect at a concentration of 10 µm when tested on lysate of NAPE-PLD, DAGL and MAGL-overexpressing cells (Table 12). 75

19 Chapter 4 The compounds were also tested on FAAH activity using U937 cell homogenate at a concentration of 5 µm. Only AM251 and Gp-1a showed partial inhibition of FAAH activity (~30-40%, Table 12). Table 12. Off-target activity on ECS enzymes. NAPE-PLD (% inhibition at 10 µm ± SD) DAGL (% inhibition at 10 µm ± SD) MAGL (% inhibition at 10 µm ± SD) FAAH (% inhibition at 5 µm) ABHD6 (% inhibition at 10 µm) ABHD12 IC50 in µm (95% CI) or % inhibition at 10 µm) COX2 (% inhibition at 5 µm) WIN ± 6-9 ± 12 3 ± 18 <25 <20 <40 <20 CP ± 8 20 ± 16 5 ± 16 ND ND ND ND Δ 9 -THC 0 ± 12-9 ± 12 7 ± 17 ND ND ND ND HU210 ND ND ND ND ND ND ND SR141716A 0 ± 7 20 ± 10 4 ± 18 <25 < ( ) <20 AM ± ± 6 0 ± 16 <50 < ( ) <20 JWH015-4 ± 12-8 ± 5 0 ± 17 ND ND ND ND JWH133 3 ± 4 30 ± 7-20 ± 5 ND ND ND ND HU308 2 ± 7 42 ± 3 7 ± 13 <25 <20 <25 <20 Gp-1a 3 ± 5 ND -1 ± 15 <50 < ( ) <20 HU910 8 ± ± 1 20 ± 12 <25 <20 <25 <20 (rac)-am ± 11 3 ± 10-2 ± 17 ND ND ND ND (R)-AM ± 5 10 ± 12-2 ± 18 <25 <20 <25 <20 (S)-AM ± 7 9 ± 9-4 ± 18 <25 <20 <25 <20 AM630-4 ± 11 6 ± 12 4 ± 16 ND <20 <25 <40 SR ± ± 11 3 ± 16 ND <20 <25 <20 Anandamide 17 ± 9 32 ± 22-2 ± 19 ND ND ND ND 2-AG -1 ± ± 16 3 ± 15 ND ND ND ND Data from single-dose experiments are obtained from two independent experiments performed in duplicate. Data from full dose-response experiments were obtained from three independent experiments performed in duplicate; FAAH inhibition was measured using URB597 (1 µm) as the positive control; ABHD6 or ABHD12 inhibition was measured using WWL70 (10 µm) and THL (20 µm) as the positive control, respectively. COX2 inhibition was measured using either 10 µm AEA or 10 µm as a substrate, using DuP-697 as the positive control; ND = not determined In addition, none of the agonists had significant activity on ABHD6-, ABHD12- and COX2 activity up to a concentration of 5 µm for COX2 and 10 µm for the ABHDs (Table 12). In contrast, the antagonists SR141716A, AM251 and Gp-1a, which are the structurally most similar ligands in this panel of ligands, inhibited ABHD12 in the micromolar range with IC50 values of 6.1, 1.6 and 0.8 µm, respectively (Table 12). AM251 was the only compound of the ligands tested that had high efficacy on GPR55 in β-arrestin recruitment (82 ± 9%), albeit with low potency (pec50 = 5.49 ± 0.09, Table 13). AEA reuptake inhibition was determined in three different human cell lines: monocyte-like U937 cells, mast cell-like HMC-1 cells, and keratinocyte-like HaCaT cells. In U937 and HaCaT cells, some of the ligands possessed micromolar potency, including AM251, SR141716A, Gp-1a, HU308 and HU910 (Table 14). In HMC-1 cells, which lack FAAH expression, 34 all tested ligands, except SR141716A, were weakly active or inactive at a concentration of 5 µm, which indicates a potential role of FAAH in the inhibition of AEA uptake in U937 and HaCaT cells. 76

20 Cannabinoid Receptor Ligand Profiling Reveals Biased Signaling and Off-target Activity In agreement with this, the most active AEA reuptake inhibitors AM251 and Gp-1a partially inhibited FAAH at 5 µm in U937 cell homogenate (Table 12). Of note, SR was inactive up to a concentration of 10 µm in all cell lines, whereas SR141716A showed FAAHindependent micromolar effects on AEA reuptake in all cells. Table 13. Off-target activity data on GPR55. pec50 ± SEM) Emax ± SEM (%) or % effect at 10 µm WIN <5 5 CP55940 <5 8 ± 18 Δ 9 -THC ND ND HU210 ND ND SR141716A ND ND AM ± ± 9 JWH015 <5 2 JWH133 <5-2 ± 3 HU308 <5-6 ± 5 Gp-1a <5-10 HU910 <5-10 ± 3 (rac)-am1241 ND ND (R)-AM1241 ND ND (S)-AM1241 ND ND AM630 <5-19 SR <5-14 Anandamide <5-9 2-AG ND ND Data from single-point experiments are obtained from two independent experiments performed in duplicate. Data from full doseresponse experiments are obtained from three independent experiments performed in duplicate; ND = not determined GPR55 Chapter 4 Table 14. AEA reuptake inhibition data. HaCaT cells U937 cells HMC-1 cells IC50, µm (95% CI) Emax (% inhibition) IC50, µm (95% CI) Emax (% inhibition) IC50, µm (95% CI) WIN >5 24* 4.65 ( ) 52 > 5 CP55940 >10 13* ND ND ND Δ 9 -THC ND ND ND ND ND HU210 >5 44* ND ND ND SR141716A 2.90 ( ) ( ) ( ) AM ( ) (ND) 67 > 5 JWH015 >5 64* ND ND ND JWH133 >10 39* ND ND ND HU ( ) ( ) 62 > 5 Gp-1a 3.27 ND (ND) 64 > 5 HU910 >10 38* 1.56 ( ) 70 > 5 (rac)-am ND 80 ND ND ND (R)-AM1241 >5 25* 4.81 ( ) 77 > 5 (S)-AM ( ) ( ) 97 > 5 AM ( ) 65 > 10 23* > 10 SR >10 20* > 10 30* > 10 Anandamide 0.27 ( ) 86 ND ND ND 2-AG >5 60* ND ND ND Data from single-dose experiments are obtained from two independent experiments performed in duplicate. Data from full dose-response experiments are obtained from three independent experiments performed in duplicate; *Effect at 10 µm; ND = not determined 77

21 Chapter TRP-channels As AEA and 2-AG activate some transient receptor potential (TRP) channels, these channels may be regarded as ionotropic cannabinoid receptors. Here, the ligands were tested on six different TRP channels (TRPV1-4, TRPA1 and TRPM8). Most TRP channels were found to be activated by one or more ligands, apart from TRPA1 that was activated by all of them (Table 15). HU308 was the most selective agonist that activated only TRPV1 and TRPA1 in the high micromolar range, whereas HU910 activated TRPV3 with submicromolar potency (0.12 ± 0.05 µm). However, to date, TRPV3-related effects and toxicity (hypothermia and reduced blood pressure) have not been observed after in vivo administration of HU JWH133 only activated TRPA1. Although its efficacy was fairly high (76.8 ± 3.8% activation), its potency was low (8.5 ± 2.3 µm). Whereas SR did not target any of the TRP channels, AM630 was a full agonist at TRPA1 (118 ± 2%). Of note, SR141716A targeted three out of six TRP channels tested and, remarkably, nanomolar potency was observed at TRPM Off-target panel (CEREP panel) The CEREP panel served to screen off-target activity on 64 proteins, which are associated with common adverse side effects in humans. JWH133 was identified as the most selective ligand with no off-targets detected in this panel. The summary of all off-targets is shown in Table 16, all CEREP data is shown in Table 20 (Experimental section). In contrast, CP55940 was the least selective ligand of which 17 off-targets were detected with more than 50% inhibition at 10 µm. HU910 and HU308 hit nine and four off-targets in this panel, respectively. However, of the 9 off-targets of HU910 in this panel only the dopamine uptake reporter displayed an IC50 of <10 µm (IC50 = 1.40 µm). Therefore, the other off-targets are not likely to be physiologically relevant at 10 µm. The CB2R-selective antagonist SR had only two off-targets. Of note, the adenosine A3 receptor was the most common offtarget (Table 16). The physiological relevance of this observation is currently unclear, although it has previously been published that the endocannabinoid 2-AG has allosteric activity on this receptor

22 Table 15. TRP channel data. Rat TRPV2 Rat TRPV3 Rat TRPV4 Rat TRPM8 Rat TRPA1 Human TRPV1 IC50 h IC50 g Efficacy c Potency EC50 μm IC50 f Efficacy c Potency EC50 (μm) IC50 d IC50 e Efficacy c Potency EC50 (μm) IC50 b Efficacy c Potency EC50 (μm) Efficacy a Potency EC50 (μm) 17.0 ± ± ± ± ± 0.9 > 100 < 10 n.a ± ± ± ± 0.9 nm 18.4 ± ± ± ± ± ± ± ± 2.2 WIN ± ± 1.5 SR141716A < 10 n.a. > ± ± ± 0.4 < 10 n.a. 2.0 ± ± ± ± ± ± 0.6 AM251 < 10 n.a ± ± ± 0.1 > 50 < 10 n.a. 1.2 ± ± ± ± 2.2 < 10 n.a. > 50 HU ± ± 3.9 > 100 < 10 n.a ± 5.7 > 100 < 10 n.a. > 100 < 10 n.a. > 100 < 10 n.a. > 100 Gp-1a 83.6 ± ± ± 1.4 < 10 n.a. 3.0 ± 0.1 > 50 < 10 n.a ± 0.7 < 10 n.a ± 3.9 < 10 n.a. 2.2 ± 0.1 HU ± ± 1.1 > 100 < 10 n.a. > 100 > 100 < 10 n.a. > ± ± ± 4.2 < 10 n.a. > 100 (R)-AM ± ± 5.8 > ± 1.5 > 50 > 50 > ± ± ± ± ± 0.1 > 50 < 10 n.a. 8.7 ± 0.5 (S)-AM ± ± ± ± 1.2 > 50 > 50 > ± ± ± ± ± 0.1 > 50 < 10 n.a. 8.6 ± 0.3 AM630 < 10 n.a ± 1.4 < 10 n.a. > 100 < 10 n.a. 3.2 ± ± ± ± ± ± 0.5 < 10 n.a. > 100 SR ± ± 1.2 > 100 < 10 n.a. > ± 1.3 < 10 n.a. > 50 < 10 n.a. > 100 < 10 n.a. > 100 JWH ± ± ± ± ± ± ± 3.5 < 10 n.a. > 100 < 10 n.a ± ± ± 3.0 > 100 Data from single-point experiments are obtained from two independent experiments performed in duplicate. Data from full dose-response experiments are obtained from three independent experiments performed in duplicate; a (% AITC 100 µm); b IC50 in µm for antagonism or desensitization on (*AITC 100 µm); c (% ionomycin 4 µm); d IC50 in µm for antagonism or desensitization (*capsaicin, 0.1μM, or capsaicin, 10 nm); e IC50 in µm (unless stated otherwise) for antagonism of icilin, 0.25μM, or icilin, 0.1μM); f IC50 in µm for antagonism or desensitization (*LPC, 3μM); g IC50 in μm for antagonism or desensitization (*thymol, 100μM); h IC50 in μm for desensitization (*4αPDD, 1μM); *5 min pre-incubation with indicated compound; n.a. not active 79 Chapter 4