Novel Insights Into Cb1 Receptor Signaling and the Anabolic Role of Cannabinoid Receptors in Bone

NOVEL INSIGHTS INTO CB1 RECEPTOR SIGNALING AND THE ANABOLIC ROLE OF CANNABINOID RECEPTORS IN BONE

A Dissertation Submitted to the Temple University Graduate Board

In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

By Jahan Marcu

May 2013

Advisory Committee

Mary Abood, Center for Substance Abuse Research

Ellen Unterwald, Center for Substance Abuse Research

Steven Popoff, Anatomy and Cell Biology

Lynn Kirby, Center for Substance Abuse Research

Scott Rawls, Center for Substance Abuse Research

ABSTRACT

Activation of the CB1 receptor is modulated by aspartate residue D2.63176 in transmembrane helix (TMH) II. Interestingly, D2.63 does not affect the affinity for ligand binding at the CB1 receptor. Studies in class A GPCRs have suggested an ionic interaction between residues of TMHII and VII. In this report, modeling studies identified residue K373, in the extracellular (EC)-3 loop, in charged interactions with

D2.63. We investigated this possibility by performing reciprocal mutations and biochemical studies. D2.63176A, K373A, D2.63176A-K373A, and the reciprocal mutant with the interacting residues juxtaposed, D2.63176K-K373D were characterized using radioligand binding and guanosine 5'-3-O-(thio)triphosphate functional assays. None of the mutations resulted in a significant change in the binding affinity of CP55,940 or

SR141716A. Computational results indicate that the D2.63176-K373 ionic interaction strongly influences the conformation(s) of the EC-3 loop, providing a structure-based rationale for the importance of the EC-3 loop to signal transduction in CB1. Specifically, the putative ionic interaction results in the EC-3 loop pulling over the top (extracellular side) of the receptor; this EC-3 loop conformation may serve protective and mechanistic roles. These results suggest that the ionic interaction between D2.63176 and K373 is crucial for CB1 signal transduction. This work may help to aide drug design efforts for the effective treatment of different diseases.

The cannabinoid receptors of osteoblasts may represent a target for the treatment of bone disorders such as osteoporosis. Our research demonstrates that cannabinoids can affect important signaling molecules in osteoblasts. In MC3T3-E1 osteoblastic cells, the

CB1 antagonist, AM251, has been reported to induce increases in Runx2 mRNA,

ii mineralized bone nodule formation, and activation of signaling molecules such as ERK and AKT (Wu et al., 2011). Studies from our lab characterizing mice in which both CB1 and CB2 receptors were inactivated by homologous recombination have demonstrated increased bone mass coupled with enhanced osteoblast differentiation of bone marrow stromal cells in culture (manuscript in preparation). We explored the effect of antagonizing CB1 and CB2 cannabinoid receptors in osteoblastic cells to gain insights into molecular pathways that may help to explain the effects of the endocannabinoid system

(ECS) in bone development.

Our data was generated by running time course experiments with MC3T3-E1 cells under the influence of SR141716A, SR144528 or both in combination. The cells were harvested with a lysis buffer at specific time points and analyzed by western blot analysis. Quantification of protein activation was calculated using LiCor imaging equipment and software. Within 15 minutes, treatment with the CB1 receptor antagonist

SR141716A resulted in several fold increases in pERK, pSMAD158, and pAKT.

SR144528, a CB2 receptor antagonist, caused increases in pERK and pSMAD158, but not pAKT. When both antagonists were applied together, pERK and pSMAD158 levels increased, while pAKT signaling was diminished compared to SR141716A alone. The finding that cannabinoid receptor antagonists alter the activity of the SMAD158 complex is a novel finding, which suggests that cannabinoids can influence bone morphogenic signaling pathways, and therefore play a significant role in osteoblast differentiation and function.

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ACKNOWLEDGMENTS

There are many people who contributed to my success in the Ph.D program. Above all, I would like to thank my mentor, Mary Abood for accepting me into her laboratory. Under her mentorship my technical skills were refined and knowledgebase vastly expanded, allowing me to take my passion for science further than I ever thought possible.

I would also like to thank the Department of Anatomy and the Center for Substance Abuse

Research for giving me opportunities to share my research and collaborate with faculty members and other students. I also appreciated the ability to network with visiting researchers and guest speakers.

Each member of Dr. Abood’s lab (Linda, Ping Wei, Halleli, Megan, and Margaret) offered me their time, energy, and support. It takes an entire laboratory to craft a Ph.D student.

Thank you.

TABLE OF CONTENTS

• ABSTRACT.…...... ii • ACKNOWLEDGEMENTS…....……..……...... iv • LIST OF FIGURES……...…....….....………………....…...... ……...…...…..vi • LIST OF TABLES…....…...……………………...... …...... viii

CHAPTERS

1. LITERATURE REVIEW...... 1 2. NOVEL INSIGHTS INTO CB1 CANNABINOID RECEPTOR SIGNALING: A CRUCIAL INTERACTION IDENTIFIED BETWEEN EC3-LOOP AND TMH2 (Journal of Pharmacology and Experimental Therapeutics 2013)...... 48 3. THE ANABOLIC ROLE OF CANNABINOID RECEPTORS IN BONE: TARGETING CANNABINOID RECEPTORS IN OSTEOBLASTS...... 77 4. SUMMARY...... 90

REFERENCES……………………………………………………………………95

LIST OF FIGURES

FIGURE 1.1 CLASSIFICATION AND STRUCTURE OF CANNABINOID LIGANDS

WITH KI VALUES…...... …....…9

FIGURE 1.2 AMINO ACID SEQUENCE OF CB1 RECECPTOR…...... 12

FIGURE 1.3 HYPOTHETICAL PATHWAY OF CANNABINOID SIGNALING CASCADE IN OSTEOBLASTS...... 32

FIGURE 1.4 µCT ANALYSIS OF CANNABINOID RECEPTOR DEFICIENT

MICE...... 34

FIGURE 1.5 SCHEMATIC DIAGRAMS OF BONE...... 35

FIGURE 1.6 CB1 RECEPTOR EXPRESSION IN VARIOUS CELL TYPES...... 38

FIGURE 1.7 CB1 RECEPTOR DEFICIENCY MAY IMPAIR OSTEOBLASTS...... 40

FIGURE 1.8 CB1 RECEPTOR DEFICIENCY IMPAIRS RANKL...... 42

FIGURE 1.9 CB1 RECEPTOR EFFECTS ON CELL PROLIFERATION...... 43

FIGURE 1.10 ROLE OF CB1 RECEPTORS IN HEALTHY AND INJURED BONE..45 FIGURE 2.1 COMPETITIVE DISPLACEMENT OF [3H] SR141716A...…...... 62

FIGURE 2.2 GTPγS STIMULATION OF WT AND MUTANT RECEPTORS...... 65 FIGURE 2.3 CONCENTRATION RESPONSE FOR GTPΓS STIMULATION OF WT, S1.39A, AND K3.28A MUTANT RECEPTORS……...……...... …..…………….....66 FIGURE 2.4 EXTRACELLULAR LOOP CONFORMATIONS OF WILD-TYPE (WT) 176 176 AND D2.63 A, K373A, OR D2.63 A-K373A MUTANT CB1 RECEPTORS IN THE ACTIVE (R*) STATE...... 70 FIGURE 2.5 EXTRACELLULAR VIEWPOINT OF EC LOOP CONFORMATIONS 176 OF WT CB1 R* AND THE D2.63 K-K373D SWAP MUTANT...... 71 FIGURE 3.1 TARGETING CANNABINOID RECEPTORS DECREASES PROLIFERATION IN PRIMARY RAT OSTEOBLASTS...... 82

FIGURE 3.2 TRABECULAR BONE VOLUME OF WT AND CB1/2 KO MICE ACROSS 52 WEEKS...... 83

FIGURE 3.3 MC3T3-E1 CELLS TREATED WITH SR141716A, SR144528, AND IN COMBINATION, ASSAYED FOR PERK...... 85

FIGURE 3.4 TARGETING CANNABINOID RECEPTORS MAY CAUSE DIFFERENTIAL IN ERK1 (P42) AND ERK2 (P44) ACTIVITY...... 86

FIGURE 3.5 MC3T3-E1 CELLS TREATED WITH SR141716A, SR144528, AND IN COMBINATION, ASSAYED FOR PSMAD158 ACTIVITY...... 87

FIGURE 3.6 MC3T3-E1 CELLS TREATED WITH SR141716A, SR144528, AND IN COMBINATION, ASSAYED FOR PAKT ACTIVITY...... 88

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LIST OF TABLES

TABLE 1.1 SUMMARY OF CANNABINOID RECEPTOR MUTATIONS IDENTIFIED IN HUMANS…...... 23

TABLE 2.1 RADIOLIGAND BINDING PROPERTIES OF WILD-TYPE AND MUTANT CELL LINES...... 61

TABLE 2.2 THE EFFECTS OF AMINO ACID MUTATIONS OF RECOMBINANT HCB1 RECEPTORS ON THE DISPLACEMENT OF [3H]SR141716A BY CP55,940...... 61

TABLE 2.3 CONCENTRATION-EFFECT DATA FOR AGONIST STIMULATION OF [35S]GTPγS ACTIVITY OF WILD- TYPE AND MUTANT RECEPTORS STABLE EXPRESSED IN HEK293 CELLS...... 64

TABLE 2.4 CONCENTRATION-EFFECT DATA FOR AGONIST STIMULATION OF [35S]GTPγS BINDING OF THE K3.28A AND S1.39A MUTANT RECEPTORS STABLY EXPRESSED IN HEK293 CELSS...... 67

TABLE 2.5 TOTAL INTERACTION ENERGY OF CP55,940 AT THE WILD-TYPE

AND MUTANT CB1 R* MODELS ...... 72

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CHAPTER 1

LITERATURE REVIEW

A Brief History of Cannabinoid Research

As early as 5,000 years ago Cannabis was noted for its effects on the central nervous system1. This often manifested in the form of pain relief, appetite stimulation, and sedation (Iverson, 2000). Medicinal Cannabis preparations were widely used in western medicine during the 19th century. At the time it was recognized that preparations of Cannabis distributed through pharmacies were variable. As the active ingredient was not known, quality control was virtually impossible, and this is in part why the plant fell out of use.

During the Victorian era, many alkaloids were extracted from plants, for their unique properties. These plant chemists were successful because the alkaloids they were targeting are water soluble organic bases that form crystalline solids when combined with acids. Among the medicinal compounds isolated in the 19th century were quinine, morphine, and cocaine. These were major advances in plant chemistry. The molecules on the cannabis plant, however, are almost completely insoluble in water. The chemical nature of cannabinoids prevented early Victorian scientists from making efficient extracts

1 Evidence for the medicinal use of Cannabis goes back to the emperor Chen Nung (the father of Chinese agriculture), a discoverer of medicinal plants, and also taught his people how to cultivate grains. Chen Nung is believed to be the author of the oldest known Chinese pharmacopoeia, in which, he writes about the medical use of Cannabis for rheumatism, menstrual fatigue, malaria, constipation, and absentmindedness.

1 of these polar compounds. The active ingredient, delta9-Tetrahydrocannabinol (Δ9-

THC), was not isolated and identified until 1964(Mechoulam and Gaoni, 1965).

In the 1990s, researchers made discoveries essential for the establishment of the cannabinoid research field. By the end of the decade scientists discovered two distinct cannabinoid receptors (i.e., CB1 and CB2), isolated endogenous cannabinoids

(e.g.,Anandamide and 2-Arachidonylglycerol), synthesized a cadre of ligands, and generated cannabinoid receptor knockout mice (i.e., CB1 KO) (Gerard et al., 1990;

Matsuda et al., 1990; Zimmer et al., 1999). Efforts to identify and clone the CB1 receptor demonstrate that it is one of the most abundant proteins in the brain. Thus, cannabinoid receptors became an attractive target for drug development. The availability of synthetic THC and novel analogs has allowed researchers to begin characterizing the role of this neuronal G-protein coupled receptor (GPCR). The sum of all knowledge on how cannabinoid receptors and their ligands work together in mammals is referred to as the endocannabinoid system (ECS).

Introduction to Ligand Binding Principles and Experimental Considerations

Radioligand and guanosine [gamma-thio] triphosphate ([35S]GTPγS) binding assays are tools which can allow the characterization of agonists, antagonists, and inverse agonists at GPCRs. The main goals of cannabinoid receptor radioligand binding and signal transduction studies are to obtain reliable affinities of ligands for the receptor of interest and to analyze the mechanism of action that is required for binding and/or stimulation. The study of ligand-receptor interactions requires standardization of the

2 assay, if any meaningful comparisons are to be made between different laboratories. It is important to consider experimental conditions for these assays as slight changes in materials can lead to alterations in binding and stimulation values. There are conflicting reports as to what extent particular compounds are binding at putative cannabinoid receptors (e.g., at GPR55) and this may be due to labs using a preferred buffer recipe, out of custom or efficiency (reviewed in (Pertwee et al., 2010; Sharir and Abood, 2010)). To aid in the determination of reliable values from binding data, the theoretical and practical aspects of basic pharmacology principles need to be addressed. These principles, protocols, and strategies are discussed below.

The various stages involved in the development and practicalities of setting up of a binding assay have been covered by numerous publications (Hulme EC, 1992; Hulme and Trevethick, 2010; Lazareno, 1998; Yamamura, 1990). For the purposes of this section we will consider radioligand assays which include removal of excess ligand via washing of filters to which the radioligand-receptor complexes are attached. Principles of, and constants generated from ligand binding assays will be followed by a brief discussion of the [35S]GTPγS receptor stimulation assay. The three basic receptor binding assays are kinetic, Scatchard assay/saturation, and competition binding experiments:

• Kinetic experiments measure the binding of a radioligand over time to

generate association (K+1) and dissociation (K-1) rate constants. Since the

KD is equal to K-1/K+1, kinetic experiments provide an independent

approximation of the dissociation constant and may help validate or

monitor the consistency of the receptor-radioligand system (Yamamura,

1990).

• Scatchard Assay/Saturation experiments involve measuring the binding of

increasing concentrations of radioligand with receptors at equilibrium. A

binding constant is generated (i.e., dissociation constant, KD). The

concentration of specific binding sites for the radioligand, Bmax, is also

generated.

• Competition Binding studies measure one or more concentrations of a

radioligand in the presence of increasing concentrations of non-labeled

compound to determine binding constants. The inhibition constant referred

to as Ki is generated from competition binding experiments using the

Cheng-Prusoff calculation (Ki= IC50/1+F/KD).

Radioligand binding assays take advantage of ligand-receptor reactions at equilibrium or in a steady state. The steady state represents a binding equilibrium between receptor [R] and ligand [L], where the rate of association is equal to the rate of disassociation.

Radioligand-receptor complexes form when a receptor preparation is incubated with a radioligand. This process can be represented as follows:

L + R ↔ RL

The amount of receptor-ligand complex formed during a saturation binding experiment is used to obtain values for KD (the ‘affinity’ expressed as the dissociation constant) and the number of binding sites, expressed as Bmax. When the saturation curve reaches a point where the free radioligand concentration is equal to the KD, at this point the amount of bound ligand is equal to one-half the Bmax. Hence, KD is the concentration

4 of radioligand required to occupy 50% of the binding sites or to reach half-maximal specific binding. Binding assays can identify compounds that have affinity for a particular target. Another step in characterizing a potentially useful ligand is measuring the ligand’s effect on receptor activity close to the signaling cascade.

The [35S]GTPγS assay is used to characterize activity at the receptor. Generally, three parameters are obtained to help determine the activity of various compounds:

• Emax is the maximal response observed at high concentrations of the drug (i.e. 1-

10µM). Emax values can be used to determine the efficacy of agonists when

compared to a full agonist. The amount of GDP used in the assay can influence

the Emax value, but it will also alter the signal to basal ratio (Strange, 2010).

• EC50 is the amount of ligand required to reach a half maximal response. As with

Emax values, EC50 values are also dependent on assay conditions (i.e. GDP).

• Hill coefficient (nH), although not often reported in published studies, signifies the

shape of the response curve. For example, if a drug binds to a single population

of receptor sites the nH is close to 1. When nH values differ from 1 it may suggest

another level of complexity, such as signaling through different G proteins or the

presence multiple binding sites.

Practical Speculations for Increasing the Reliability of Binding Values

The recovery of receptor-ligand complexes from a binding assay is a straightforward concept. Ideally, receptor-ligand complexes will not dissociate during filtration and repeated washing. The use of ice cold wash buffers is recommended as

5 temperature can affect the KD. The KD can appear to shift depending on the temperature of the wash buffer, lower temperatures often greatly reduce the rate of dissociation

(Hulme and Trevethick, 2010). Choosing the appropriate filters and pretreatment is also important. Soaking filters with polyethyleneimine (i.e., 0.1% PEI solution) grants a positive surface charge, which reduces non-specific binding of cationic but not anionic

(i.e, GTPγS) fragments.

Recently a new class of compounds for cannabinoid receptors, allosteric modulators, have been identified (Iliff et al., 2011). Synthetic and endogenous ligands generally bind to the orthosteric site. Since the orthosteric and allosteric sites are structurally distinct, the proper identification and characterization of allosteric modulators is important for drug development (Conn et al., 2009). Allosteric modulators could have a therapeutic potential and be a valuable research tool used to help obtain more reliable results from binding assays. In theory, it could be possible to use a positive allosteric modulator in wash buffer to stabilize the ligand-receptor interaction during filtering

(Hulme and Trevethick, 2010). An allosteric modulator could reduce the dissociation rate during the washing steps thereby increasing reproducibility of binding parameters.

Another speculation for increasing the reliability of binding data is regarding quality control of the radioligand. In general, the assumption is that the radioligand that arrives in the lab is chemically pure based on a data sheet from the manufacturer or label on the vial. Unfortunately, the data sheet or label may not always be accurate. Improper handling, aliquoting and storage conditions are some factors which contribute to alterations in specific activity (and thus affect the KD). Contamination with binding and non-binding impurities can lead to over- and under-estimations of binding parameters,

6 which may cause inaccurate interpretations due to ambiguous data (Sum et al., 2001).

These binding and non-binding contaminants contribute to non-specific binding (Hulme and Trevethick, 2010). A simple check for analyzing the quality of a radioligand is to compare Bmax and KD values with a second radioligand in saturation assays. If the radioligands have the same specific activity then the values will not be significantly different.

Evidence exists that the cell membrane contributes to the functionality of GPCRs

(Khelashvili et al., 2010; Liu et al., 2009; Mahaut-Smith et al., 2008). In this regard, β- arrestin trafficking assays performed in cultured cells, in situ, are a promising development to study receptor properties (Kapur et al., 2009). Another promising area in the study of GPCRs, is the development of isotope labeling of GPCRs and their ligands to potentially obtain structural information based on NMR spectra (Tapaneeyakorn et al.,

2011).

Introduction to the Study of Cannabinoid Receptors

Scientists face a big challenge when attempting to obtain accurate information on the structure of GPCRs and the efficacy of ligands. Revealing the transmembrane helical clusters that surround the binding pocket is crucial to understanding how any protein carries out its functions. Crystallization techniques are often used to reveal important structural information of proteins; researchers have been unable to crystallize the cannabinoid receptors. Since the 1990s transfected cell lines expressing the CB1 receptor have served as a reliable tool for studying the structure of the CB1R and pharmacology of cannabinoids (Matsuda et al., 1990). The molecular structure of the cannabinoid

7 receptors is based on experiments combining site directed mutagenesis with molecular modeling techniques. Cannabinoid receptors harvested from cell cultures can be used to study GPCR activity through techniques including GTPγS for receptor activity and utilizing tritiated (3H) cannabinoids for determining binding affinities.

The investigation of novel compounds acting through the CB1 and CB2 receptors revealed classes of ligands with selective binding properties (Hurst et al., 2002; Song and

Bonner, 1996). There are at least five structurally distinct classes of cannabinoids. There are tricyclic cannabinoids (Δ9-THC, HU-210), bicyclic cannabinoids (CP55,940), indoles

(WIN55,212, JWH-018), fatty acid derivatives or eicosanoids (anandamide, 2- arachidonylgylcerol), and antagonist/inverse agonists (SR141716A, SR144528). See

Figure 1 for cannabinoid agonist classifications and Ki values. Some of these compounds have demonstrated selective binding properties. For instance, CP55-940, Δ9-THC, 11-

OH THC, and anandamide activate both cannabinoid receptors with similar efficacies.

SR144528 and WIN55,212 show a preference for the CB2 receptor. Further structure activity relationship studies of ligands such as SR141716A, has aided in the design of high affinity and selective ligands (Hanus, 2009).

GPCR Background: CB1 Receptor Structure and Function

GPCRs are a super family of cell surface receptors with the principal role of transmitting information regarding the exterior environment to the inside of the cell. This transmission of information is relayed by the heterotrimeric guanine nucleotide-binding regulatory proteins (G proteins) to other proteins (i.e. kinases). Cannabinoid receptors

FIGURE 1.1. CLASSIFICATION AND STRUCTURE OF CANNABINOID LIGANDS WITH KI VALUES. The structures of prototypical cannabinoid compounds from different structural classes with average Ki values for the displacement of a tritiated compound from rat, human, or mouse CB1 and CB2 receptors. The tritiated compound used is often [3H]CP55940, but values are also derived from displacement of [3H]SR141716A, [3H]R-(+)-WIN55212, or [3H]HU- 210. For full references see Pertwee et al., 2010.

belong the class A family of GPCRs and members of this super family share a common

membrane topology (Kristiansen, 2004). The class A receptors are characterized by

having an extracellular N-terminus, intracellular C-terminus, and 7 transmembrane

helices (TMHs) connected by loops (Ballesteros JA 1995). Within the seven TMHs of

9 the CB1 receptor are regions crucial for binding, activation, and signal transduction, see

Figure 1.2 for a diagram of the receptor (For review see (Abood, 2005)). Functional residues in the CB1 receptor can be divided into at least four groups; there are residues that affect ligand binding, receptor conformation, receptor activation, and G-protein association. It should be noted that changes in binding and conformation are always associated with changes in stimulation.

The mutation of residues that affect receptor confirmation may cause a failure of expression due to protein misfolding, and/or an abolishment or severe reduction in binding affinities and receptor activation. On the extracellular portion of TMHs 3-4-5-6 there is an aromatic cluster consisting of tryptophan, tyrosine, and phenyalanine residues.

The residues F3.25, F3.36, W4.64, Y5.39, W5.43, and W6.48 constitute a microdomain of aromatic clusters that face the binding pocket. The study of this receptor revealed that, a tyrosine, Y5.39, is conserved between both CB1 and CB2 receptors. A mutation of

Y5.39 to another aromatic residue phenylalanine (Y5.39F) resulted in only minor differences in affinity and transduction compared to the Wild Type (WT) CB1 receptor.

However, in an isoleucine (Y5.39I) mutation there is a loss of ligand binding along with pronounced topological changes in TMHs 3-4-5 (McAllister et al., 2002). A systematic analysis of the aromatic microdomain demonstrated that the cannabinoids SR141716A and WIN55,212 require aromatic stacking interactions of TMHs 3-4-5-6 to activate the

CB1 receptor (McAllister et al., 2003). This study revealed a selective binding region for aminoalkyindoles and diaryl pyrazole cannabinoids, but not for endogenous

(anandamide) and bicyclic (CP55,940) cannabinoids. The aromatic residues F3.36 and

W6.48 form a toggle switch and the mutational analysis revealed that these residues are

10 important for both binding and activation (McAllister et al., 2004). A mutation of F3.36 to alanine resulted in an increase of constitutive activity that was confirmed by using the inverse agonist SR141716A to reduce basal levels of GTPγS binding. Mutation of

W6.48 did not cause a rise in basal levels but an increase in ligand affinities. Together, the F3.36 and W6.48 form an interaction that exists in the inactive state of the CB1 receptor. As a ligand is recognized by the receptor these ‘bridges’ are broken and the protein conformation changes, operating as a toggle switch mechanism.

Other residues may have more dramatic effects on protein folding or conformation. For example, tryptophan 4.64 (W4.64) is conserved between CB1 and

CB2 receptors and mutational analysis suggests this aromatic residue is important for ligand binding and signaling (Rhee et al 2002, McAllister 2003). Substituting W4.64 to non-aromatic residues leucine (W4.64L) and alanine (W4.64A) resulted in drastic reductions. Both W4.64L and W4.64A mutants displayed a loss of ligand binding and signal transduction. However, the W4.64A mutant did not localize to the cell surface and may be the result of protein misfolding. In many GPCRs, W4.64 is known for its role in proper protein folding (Wess et al., 1993). As another example, mutations in the N terminus of the 2nd extracellular loop (EC2) resulted in retention of the CB1 receptor in the endoplasmic reticulum (Ahn et al., 2009a).

FIGURE 1.2. AMINO ACID SEQUENCE OF CB1 RECECPTOR

Isoleucine 2.62 (I2.62) and aspartate 2.63 (D2.63) are located in a nonbinding region and may be an important structural requirement (Kapur et al., 2008). A mutation of I2.62 to threonine (I2.62T) and substituting D2.63 for, the likewise, similarly charged residue glutamate (D2.63E) did not significantly alter binding or activation compared to

WT. However, substituting the neutral charged asparagine (D2.63N) reduced the potency of CP55,940, WIN55,212, HU-210, and AM4056. The double mutation (I2.62T-D2.63N) resulted in a synergistic increase of the EC50 required for activation. D2.63A is hypothesized to form a ‘salt bridge’ with a lysine (K) residue in the third extracellular

12 loop (K373). Salt bridges between charged residues are the result of proximity and favorable electrostatic attractions (Bosshard et al., 2004). They contribute to protein structure and the specificity of interaction of proteins with various biomolecules. Studies on GPCRs suggest these interactions are between charged residues from spatially distinct domains, i.e., a salt bridge between TMH2 and 7 modulates receptor function. Salt bridges are generally composed of negative charges from Asp, Glu, Tyr, Cys, and the C-

Terminal carboxylate group, and of positive charges from His, Lys, Arg, and the N- terminal amino group (Kumar and Nussinov, 2002). This ‘salt-bridge’ interaction may be important for maintaining the structure of the CB1 receptor. Our preliminary data on alanine substitutions of these residues (i.e., D2.63A-K373A, see chapter 2) produced dramatic reductions in receptor activation.

Mapping Selective Binding Regions

The section that follows describes current knowledge on the structural requirements for selective ligand binding at the CB1 receptor by techniques such as site directed mutagenesis, computer modeling, and radioligand binding. Exploring the residues responsible for activation by typical and atypical cannabinoids can provide insights into requirements for selective binding regions. The structural requirements of ligand activity of CP55,940, anandamide, WIN55,212, and SR141716A are discussed, followed by a section focusing on the K3.28 residue.

CP55,940

Residues important for CP55,940 or bicyclic cannabinoids have been identified in the CB1 receptor. For instance, the Y5.39I mutation but not the Y5.39F mutation

13 resulted in the loss of CP55,940 binding (McAllister et al., 2002). This suggests a role for aromatic residues in CP55,940 binding. Additionally, some residues that are critical for

CP55,940 binding may also lie in nonbinding regions.

It has been suggested that Cysteine 6.47 (C6.47) is a binding residue for

CP55,940 (McAllister et al., 2004; Picone et al., 2005; Shi et al., 2002; Tiburu et al.,

2009). The evidence is based upon a selection of studies on affinity labeling, site- directed mutagenesis, and ligand docking studies. CP55,940 binding was decreased in the

C6.47L mutation but no changes in WIN55,212 binding was observed in mutations of

C6.47. This suggests that C6.47 is part of a conserved motif responsible for recognizing cannabinoids such as CP55,940.

Serine 7.39 (S7.39) has also been reported to be important for CP55,940 binding

(Kapur et al., 2007). The S 7.39A mutation may have introduced a kink in TMH7, altering the structure of the extracellular binding domain required for CP55,940 binding.

A rigorous analysis of alanine mutations of the CB1 EC2 revealed residues important for

CP55,940 binding including the amino acids in EC2 numbered W255, N256, P269,

H270, and I271 (Ahn et al., 2009a). Mutations in the C-terminus of EC2 exhibited decreases in binding for many agonists but not SR141716A.

A mutation of F3.25 with alanine can have differential effects on CP55,940 binding in human and mouse cannabinoid receptors. The effect of a slight CB1 sequence difference was shown by two groups revealing that F3.25A will result in a drastic reduction in human CB1 CP55,940 binding, but not in mouse CB1 receptors (McAllister et al., 2004; Murphy and Kendall, 2003). Moreover, the mouse CB1 F3.25A mutation

14 did not affect CP55.940, WIN55,212 or SR147116A binding; instead it resulted in a substantial decrease in anandamide binding. A K3.28A 2 mutation reduced CP55,940 activity while the stimulation by WIN55,212 was relatively unaffected.

Anandamide

The residue F3.25 may impart specificity for the endogenous cannabinoid, anandamide. Computer modeling on the docking of anandamide at CB1 supports ligand interaction, suggesting aromatic stacking with F3.25 is required for anandamide binding

(McAllister et al., 2003). However, the role of Y5.39 in anandamide recognition is unclear. McAllister (2002) reported that the Y5.39F mutation was reported to significantly decrease anandamide’s binding affinity, and the Y5.39I mutation also abolished binding and signaling at the CB1 receptor. One report suggested that Y5.39S and Y5.39A mutations cause a failure of receptor expression (Shire et al., 1996).

McAllister (2002) suggests that this residue may not lie in a direct binding region, and mutating the Y5.39 residue could result in global changes affecting the shape of the binding pocket.

SR141716A

Alanine substitutions of W5.43 and W6.48 resulted in significant reductions in

SR141716A binding (McAllister et al., 2003). It has also been shown that particular residues within EC2, C257 and C264 are important for maintaining SR141716A affinity

(Fay et al., 2005). This result may be due to a breaking of disulfide bonds, modifying the binding pocket. Furthermore, Fay (2005) introduced a bulky substitution at C7.42 which

2 K3.28A is discussed in greater detail on page 12

15 inhibited SR141716A binding. This may suggest that SR141716A directly interacts with this residue.

Receptor modeling studies suggest that SR141716A has a higher affinity for the inactive state (R) of the CB1 receptor (McAllister et al., 2003). SR141716A stabilizes

TMH6 in the R state through aromatic stacking interactions with F3.36 and W6.48.

Only in the R state is a hydrogen bond available from K3.28; it is unavailable in the active state (R*). This hydrogen bond can interact with the C3 substituent of

SR141716A (Hurst et al., 2002).

WIN55,212

WIN55,212 is a prototypic indole derivative with unique binding requirements.

WIN55,212 binding is reduced by mutations F3.25A, F3.36A, Y5.39A, W5.43A, and

W6.48A (McAllister et al., 2003; Tao and Abood, 1998). Taken together, this data suggests that there is an aromatic domain important for WIN55,212 binding within

TMHs 3-4-5-6. F3.36A and W5.43A mutations demonstrate additional evidence for selective binding regions. WIN55,212 was significantly decreased in the F3.36A and

W5.43A mutants while the binding of CP55,940 was relatively unaffected.

A G3.31S mutation resulted in an enhanced binding of WIN55,212 due to interactions of a carboxyl oxygen on the ligand, which is absent from other indoles that display up ten-fold decreases in binding affinity (Chin et al., 1999; Reggio et al., 1998).

A V5.46F mutation also enhanced WIN55,212 binding, but did not alter binding for the endocannabinoid anandamide (McAllister et al., 2003).

Summarizing Important Regions for Ligand Binding

Cannabinoids have important interactions with both binding and non-binding residues in the CB1 protein. For instance, the current understanding of CP55,940 and

CB1 receptor interactions demonstrates that this ligand requires residues on TMHs 3-5-6-

7, as well as residues within the EC1 and EC2. The limited findings on anandamide binding suggest residues within TMHs 3-5-6 are important for binding but no EC residues are implicated as of yet.

WIN55,212 requires residues within TMHs 2-3-5-6 for proper binding.

SR141716A appears to need residues within TMHs 3-5-6-7 and EC2. There is overlap between binding regions for different classes of ligands. The overlapping binding regions may impede more than one ligand from binding the receptor at a time, despite specific binding residues for different classes of ligands.

K3.28 is Important for Ligand Binding and Binding Pocket Stability

Perhaps more than any other residue, the current understanding of CB1 receptor binding is dependent upon the role of K3.28. This residue may directly interact with

CP55,940 and SR141716A but not with WIN55,212 (Chin et al., 1999; Reggio et al.,

1998; Song and Bonner, 1996). Site-directed mutagenesis studies showed that an alanine substitution (K3.28A) resulted in loss of binding and receptor activity for HU-210,

CP55,940 and anandamide, but WIN55,212 retained binding and activation properties similar to WT. Several computational analysis studies use K3.28 as a primary interaction site of H binding, from the phenolic OH of cannabinoid ligands (Abood, 2005; Shim,

2010).

The effect of the K3.28A mutation could be extended to most ligands, as anandamide, CP55,940, and SR141716A exhibited 17 fold or higher decreases in binding, WIN55,212 can exhibit a low (two-fold) decrease in binding (Hurst et al., 2006;

Hurst et al., 2002; Semus and Martin, 1990; Song and Bonner, 1996). This has lent itself to a hypothesis in a recently published review, that a K3.28A mutation indirectly modifies the binding pocket(Shim, 2010). Further evidence is cited from a study on a bulky arginine substitution, K3.28R (Chin 1998). No difference in CP55,940 binding efficiency was observed between mutant and WT CB1. Since a bulkier substitution doesn’t significantly alter binding affinity then K3.28 may not bind with CP55,940.

However, K3.28 is important for SR141716A binding (Hurst et al., 2002). K3.28 offers a hydrogen bond to SR14716A in the R state. Modeling studies suggest this hydrogen bond forms a salt bridge with D6.58 in the R state. This strongly suggests that K3.28 is involved with ligand recognition in the R state and represents a very important binding residue for some classes of cannabinoids but not the aminoalkyindoles such as

WIN55,212.

Introduction to the Endocannabinoid System

The ECS has been observed in nearly all brain regions and organ systems (Fride,

2002; 2004; Fride et al., 2006). Current findings support a new role for the ECS in regulating bone metabolism and differentiation. An overview of the role of the ECS in development is discussed, followed by a focus on the CB1 receptor in regards to osteoblasts.

Cannabinoids in Development

Successful prenatal development is dependent on a number of factors. The cumulative research on the ECS identifies this system as key modulator of growth and development. The cannabinoid receptors, associated ligands, enzymes and other related molecules are detectable, if not abundantly available in nearly all components of the reproductive system, stages of fertilization and development (Buckley et al., 1998; Fride et al., 2009; Tam et al., 2006). For instance, cannabinoid receptors and anandamide have been detected in sperm of many different species, from sea urchins to humans (Schuel and Burkman, 2005). Anandamide levels can influence implantation and modulate regular gestation (Fride et al., 2005). Endocannabinoids, notably 2-AG, are also found in human breast milk. The ECS can influence pre-implantation events, and it remains an active system in prenatal development and throughout adulthood.

The cannabinoid receptors are expressed during development in the mammalian brain. While there is limited research on the localization of the CB1 receptors in the developing human brain, at week 19 of gestation there are significant populations of cannabinoid receptors functionally coupled to signal transduction mechanisms in the same region of the adult brain (Buckley et al., 1998; Mailleux et al., 1992; Mailleux and

Vanderhaeghen, 1992a; b; Ramos et al., 2005a; Ramos et al., 2005b). The receptors appear to progressively increase in density from prenatal stages into adulthood (Buckley et al., 1998; Mato et al., 2003). Additionally, animal models have shown that high densities of cannabinoid receptors have been detected in fiber-rich areas of the brain that become devoid of cannabinoid receptors in adulthood. This transient distribution and expression of cannabinoid receptors has been interpreted as an indication that the CB1 receptor is involved in several developmental events, such as metabolic support, cell

19 proliferation and migration, axonal elongation, synaptogenesis, and myelogenesis

(Gomez et al., 2008).

Outside the brain the CB1 receptor is found on nerves throughout the human body. CB1 receptors are located on sympathetic nerve terminals which traverse bone

(Ishac et al., 1996). Bone has very rich supply of nerves, and proper neuronal development is linked to proper bone growth and maintenance. Under the proper conditions, such as during traumatic brain injury (TBI), CB1 receptors on these sympathetic nerve terminals can spur bone formation (Tam et al., 2006). Ablation of the

CB1 receptor in mice results in severe age related osteoporosis and poor neurological development, such as deficits in hypoglossal nerve synapses (Fride et al., 2005; Fride et al., 2009).

Neurological conditions have been associated poor bone maintenance (Patel and

Elefteriou, 2007; Takeda, 2009; Takeda and Karsenty, 2008). For instance, cerebral palsy is characterized by neurological abnormalities and paralysis (Rosenbaum et al.,

2007). The impairment of posture and movement control in cerebral palsy leads to secondary bone malformations (Morrell et al., 2002). Furthermore, children with cerebral palsy exhibit low bone mineral content and underdeveloped bone structures

(Modlesky et al., 2009; Modlesky et al., 2008). While CB1 KO mice have neural development problems, effectively describing a bone phenotype via cellular mechanisms has been a challenge to researchers looking for an ECS-related mechanism in bone (Fride et al., 2009; Idris, 2008).

The CB1 receptor is considered a neuronal receptor, so it may seem counter- intuitive for this protein to have a role in bone metabolism. Yet, the first evidence of neuronal control of bone may have emerged as early as 150 years ago (Gros, 1846).

Notably, the trabecular bone is densely populated with sympathetic nerves (Mach et al.,

2002; Serre et al., 1999). There have been recent advances in the understanding of neuronal control of bone mass, cannabinoids also appear to regulate bone formation via sympathetic neurons which traverse bone (Takeda et al., 2002; Tam et al., 2006).

Endocannabinoids act via CB1 receptors located at prejunctional axon terminals, upon activation neurotransmitter release is inhibited. In bone the CB1 receptor activation results in a reduction in norepinephrine release, leading to alteration in cellular activity and an increase in bone mass (Tam et al., 2008). The role of CB1 receptors in bone may be two-fold. The ECS is directing bone growth via nerves which traverse bone, and modulating bone cell activity and differentiation.

ECS Polymorphisms in Health and Disease

The roles of specific amino acids within cannabinoid receptors have been studied in detail and researchers have identified many requirements essential for a compound to bind and/or activate these receptors. There is mounting evidence that different types of cannabinoids may require different amino acids for binding and activation (reviewed in

(Abood, 2005)). There are a number of published examples described below demonstrating a potentially vast amount of CB1, CB2, and FAAH gene divergence in human populations, which can arise from splice variations, polymorphisms, and somatic mutations (See Table 1.1, for review of CNR1 mutations see (Hillard et al., 2012)).

Genomic studies suggest that potential therapies could be developed which target the ECS. For example, the CB1 receptor has been shown to regulate drug addiction and related disorders; in CB1 KO mice there is a reduction in the reinforcing properties and withdrawal severity of morphine (Ledent et al., 1999). Different research teams have shown that the CB1 receptor is involved in the reinforcing effects of morphine by regulating mesolimbic dopamine levels (Chen et al., 1990; Mascia et al., 1999; Tanda et al., 1997). Genetic variations in different strains of rats have been associated with the severity of responses to Δ9-THC-related brain stimulation reward (Lepore et al., 1996).

For instance, the brain-reward-stimulation of Fischer 344 rats remained unaffected, while

Lewis rats show a pronounced effect, and Sprague-Dawley rats show a response about half that of Lewis rats. Investigations of several polymorphisms drug-abusing in humans from European, African and Japanese ethnicities and found associations with a 5’ “TAG” haplotype that was highly associated with substance abuse in all three populations

(Zhang et al., 2004). This demonstrates that genetic variations may underlie differential responses to cannabinoids, and further supports a role for the ECS in drug addiction.

Analysis of a German population revealed that a common cannabinoid receptor polymorphism existed (Gadzicki et al., 1999). This was a silent mutation in T453 (G to

A) in the C-terminal of the cannabinoid receptors. A full-length sequence was unearthed which contained mutations that resulted in amino acid changes, these amino acid changes were F200L, I216V, and V246A (Kathmann M, 2000). It’s fascinating to note that these were somatic mutations isolated from epileptic brain tissue, while DNA obtained from blood samples did not have this mutation. Somatic mutations are generally associated with disease process in cancers, e.g., mutant p53 expression in mutant tissues (Baker et

22 al., 1989, Lamlum et al.,2000). Polymorphisms in the CNR1 gene are associated with drug dependence, obesity, mental health, anxiety, memory performance, and Parkinson’s disease (Barrero et al., 2005; Comings et al., 1997; Ho et al., 2011; Hopfer et al., 2006;

Juhasz et al., 2009; Lazary et al., 2009; Marcos et al., 2012; Mutombo et al., 2012;

Okahisa et al., 2011; Ruiz-Contreras et al., 2013; Ujike et al., 2002; Zuo et al., 2009)

A growing body of scientific research suggests the ECS may have a therapeutic role in major depression and/or bipolar disorder (Monteleone et al., 2009; Monteleone et al.). Research has demonstrated that certain variations or mutations associated with the

ECS may make humans more susceptible to major depression or bipolar disorder. The current study found that specific mutations in both the CB1 receptor and FAAH enzyme were found in human subjects suffering from major depression and bipolar disorder. The

CB1 receptor mutation was significantly associated with major depression, while associations for both CB1 receptor and FAAH mutations were found in patients suffering from bipolar disorders. A previous study has also linked variations in FAAH and CB1 receptors to anorexia nervosa and bulimia nervosa (Monteleone et al., 2009).

TABLE 1.1. SUMMARY OF CANNABINOID RECEPTOR MUTATIONS IDENTIFIED IN HUMANS. For review see Hillard et al., 2012.

In addition to the CB1 receptor, polymorphisms in the CB2 receptor are also

correlated to disease. For instance, polymorphisms in the gene for the CB2 receptor have

been linked to osteoporosis, low bone mineral density (BMD) and hand bone strength in

case-controlled studies consisting of over 3,000 adults (Huang et al., 2009; Karsak et al.,

2005a; Karsak et al., 2009; Yamada et al., 2007). The first study conducted in France

examined CB1 and CB2 receptor DNA in a sample of post-menopausal patients and

female controls (Karsak et al., 2005a). The authors report that certain changes in CB2

receptor, but not the CB1 receptor, were strongly associated with osteoporosis. This is

24 the first study that has found a link between the CB2 receptor and a disease in human patients. A study published out of Japan had similar findings in 2007, in a group of pre and post-menopausal women (Yamada et al., 2007).

The third study on CB2 genes in humans, examined the role of CB2 DNA or genes on hand bone strength (Karsak et al., 2009). The author took radiographic images and DNA samples from a Chevashian population, an ethnically homogeneous population of people of Bulgaric ancestry that live along the Volga River. The authors found several recurring polymorphisms that were significantly associated with a weak hand bone phenotype. These studies have shown that CB2 receptor gene variations were observed in three different genetic/ethnic backgrounds, supporting a link between the CB2 receptors and bone health.

Furthermore, it has been speculated that CB2 receptor activation can inhibit atherosclerotic plaques (Steffens et al., 2005). Atherosclerosis is a late onset disorder that is inversely correlated to bone mineral density. If bone density or strength starts to decrease, then atherosclerosis may be progressing. CB2 receptor polymorphisms may be able to partly explain the association between the low bone density and atherosclerosis.

Δ9-THC has already been shown to reduce atherosclerosis in mice primarily by activating the CB2 receptor (Mach and Steffens, 2008; Steffens et al., 2005).

Mutations in cannabinoid receptors and associated enzymes may underlie many diseases; in fact a “clinical endocannabinoid deficiency” has been proposed to explain some chronic diseases such as: “migraines, fibromyalgia, irritable bowel syndrome, and other functional conditions alleviated by clinical cannabis” (Russo, 2004). A

25 further exploration of both CB1 and CB2 polymorphisms and somatic mutations is warranted. The ECS is an important regulatory system for mammals and the components of the ECS are expressed in nearly all parts of the human body throughout every stage of life. Recently, a complex role for the ECS in bone metabolism has emerged. A majority of research on bone has focused on the CB2 receptor, leaving a gap of knowledge regarding CB1 receptors and bone.

Overview of Cannabinoid Signaling and Proposed Mechanisms of Transduction in Osteoblasts

Cannabinoid receptors are members of the rhodopsin subfamily of G-protein coupled receptors. Cannabinoid receptor signal transduction mechanisms are affected by

G protein coupling and involve: regulation of adenylyl cyclase, alterations of mitogen- activated protein (MAP) kinases, modulation of ion channels, and modulation of intracellular Ca2+. Cannabinoid signaling cascades are linked to cell proliferation, cell differentiation, cell movement, and cell death. Understanding the molecular pathways involved with cannabinoid receptor signaling are key to elucidating their mechanisms in bone.

The CB1 and CB2 receptors are coupled to Gi/o proteins, upon receptor stimulation there is generally an inhibition of adenylyl cyclase and effects on MAP kinase activity (Howlett, 2005; Howlett et al., 2002; Howlett and Fleming, 1984; Pertwee et al.). The CB1 receptor when coupled to Gi/o can also modulate A-type and inwardly rectifying potassium currents and cause an inhibition of N- and P/Q-type calcium

26 currents. Cannabinoid receptor signaling events are usually pertusiss toxin sensitive, implicating the involvement of Gi/o coupled proteins (Howlett et al., 1986). Additional evidence from experiments which sequester Gi/o proteins from being used by cannabinoid receptors has shown that the CB1 can associate with Gs (Jarrahian et al., 2004). CB2 receptors are not known to associate with Gs (Calandra et al., 1999; Glass and Felder,

1997). In contrast, experiments have revealed CB1 receptor coupling with Gq proteins in

HEK cells (Lauckner et al., 2005). Both CB1 and CB2 receptor stimulation can induce

2+ Gq mediated Ca release in insulinoma cells (De Petrocellis et al., 2007). The Gi/o and Gs

2+ protein can modulate cAMP and Ca currents while Gq is mainly involved with

2+ intracellular Ca release. CB1 and CB2 receptors are known to associate with Gi/o and

Gq, only the CB1receptor is known to associate with Gs proteins.

The CB1 receptor mediated inhibition of adenylyl cyclase was the first cannabinoid receptor mechanism to be characterized (Howlett and Fleming, 1984). CB2 receptors can also inhibit adenylyl cyclase activity (Bayewitch et al., 1995). The ability of cannabinoid receptors to interact with Gi/o is exploited in the adenyly cyclase assay

(and the [35S]GTPγS receptor stimulation assay). The functional inhibition of adenylyl cyclase and thus cAMP, has been demonstrated in many other experiments (Demuth and

Molleman, 2006; Pertwee et al.). This cannabinoid mediated effect is sensitive to pertussis toxin and CB1 antagonists such as SR141716A, and leads to an attenuation of cAMP accumulation. Alterations in cAMP concentrations can regulate PKA phosphorylation resulting in significant changes in cellular activity (Childers and

Deadwyler, 1996; Mu et al., 2000). For example PKA activity can affect gene expression and regulate potassium channel activity (Hampson et al., 1995).

MAP kinase pathways are often activated by GPCRs and MAP kinase cascades can lead to the activation of ERK1/2, c-Jun N-terminal kinase (JNK), p38 MAP kinase and/or ERK5 proteins. Stimulation of CB1 and CB2 receptors in vivo and in vitro generally leads to the activation of ERK1/2, PI3K, and PKC through mechanisms that involve the activation of Gi/o proteins and inhibition of adenylyl cyclase and alterations in the activity of protein kinases (Davis et al., 2003). CB1 receptor signaling can lead to alterations in the levels of p38 MAP kinase and JNK. The stimulation of various signaling molecules can also be dependent on the cell type or tissue.

Ion channels can be modulated by CB1 and CB2 receptor stimulation (Atwood et al., 2012; McAllister et al., 1999). CB1 receptors can stimulate G-protein coupled inwardly-rectifying potassium channels which are activated through Gi/o proteins, and this may be induced by a variety of CB1 agonists (Turu and Hunyady, 2010).

Experiments using Xenopus oocytes transfected with CB2 and G-protein coupled inwardly-rectifying potassium channels did not demonstrate CB2 modulation of ion channel function (McAllister et al., 1999). However, CB₂ cannabinoid receptors inhibit synaptic transmission when expressed in cultured autaptic neurons (Atwood BK, et al,

2012). CB1 receptors can also affect the function of L-type, N-Type, and P/Q type calcium channels (Caulfield and Brown, 1992; Endoh, 2006; Felder et al., 1995;

Gebremedhin et al., 1999; Hampson et al., 1998; Mackie et al., 1993; Mackie and Hille,

1992; Mackie et al., 1995).

Cannabinoids can modulate levels of intracellular Ca2+. 2-AG and WIN55212-2 were able to increase intracellular Ca2+ in NG108-15 cells, a neuroblastoma-glioma hybrid cell line (Sugiura et al., 1996). These effects were inhibited by pertussis toxin and

SR141716A, suggesting the effect is mediated by Gi/o proteins via the CB1 receptor. A phospholipase C (PLC) inhibitor was also able to block the response implicating the

2+ involvement of IP3 in the release of Ca (Sugiura et al., 1997). Additional evidence exists on cannabinoid modulation of Ca2+ in endothelial, cerebellar granule, canine kidney, and smooth muscle cells (Demuth and Molleman, 2006). Anandamide was also demonstrated to modulate intracellular Ca2+ in endothelial cells by activation of PLC, the effect was blocked by the CB2 antagonist SR144528 but not the CB1 antagonist

SR141716A (Zoratti et al., 2003). Collectively, the data supports CB1 and CB2 receptor

2+ mediated release of intracellular Ca , through Gi/o proteins and increases in PLC activity.

The signaling mechanisms and predominately associated G-proteins of CB1 receptors in osteoblasts is unclear but existing studies on G-proteins in bone cells may provide a clue to plausible mechanisms. The CB1 receptor coupled G-proteins are also associated with other GPCRs and these G-proteins have been demonstrated to affect important signaling molecules in osteoblasts. Gi/o proteins may regulate osteoblast proliferation by interacting with MAPK cascade and affecting downstream ERK activation (Wu et al.). Anti-apoptotic signals can result from AKT activation which can induce a caspase cascade under the regulation of Gi proteins. The effect on such downstream mediators has been explored in osteoclasts (Ross, 2005). Potential cannabinoid signaling pathways in osteoclasts have already been proposed. Notably, the proposed mechanism in Figure 1.3, adapted from Ross (2005), suggests CB1 or CB2 downstream targets in osteoblasts could be ERK, SMADs and AKT.

Gq may regulate osteoblast proliferation and differentiation. In vitro assays have revealed that Gq signaling promotes osteoblast proliferation (Wu et al.). In an apparent

29 contradiction, transgenic mice with a constitutively activated Gq in osteoblasts appear to have reduced numbers of osteoblasts and lower bone marrow density (Ogata et al., 2007).

Cultures from these Gq-transgenic mice show impaired osteoblast differentiation confirmed by a decrease in activity of the differentiation marker alkaline phosphatase

(ALP). This study was conducted with FVB/N mice and MC3T3 cells; it would be interesting to see if future studies find a consistent Gq-associated inhibition of osteoblast differentiation across different mice backgrounds such as in C57/Bl6 or CD1 mice strains.

Gs proteins have a demonstrated role in bone remodeling as well. Transgenic animals with a Gs deficiency exhibit skeletal malformations which support a role for Gs proteins in endochondral bone development (Castrop et al., 2007). A Gs deficiency in chondrocytes is lethal in mice, the animals display severe growth plate defects (Sakamoto et al., 2005a). Mice with an osteoblast-specific Gs deficiency have reduced bone turnover, thickened cortical bone, and a narrow bone marrow cavity (Sakamoto et al.,

2005b). Gs promotes bone formation in vivo, and osteoblast differentiation and proliferation are promoted in vitro.

The CB1 receptor can be associated with Gi/o, Gq and Gs proteins which are implicated in bone remodeling, osteoblast differentiation, and proliferation. Taken together, the scientific data on CB1 signaling in osteoclasts and the role CB1associated

G-proteins in osteoblasts lends support to a hypothesis which suggests that CB1 signaling may affect the levels of pAkt and pERK, thus influencing expression of Runx2 and

Osterix, leading to changes in cell proliferation and osteoblast differentiation.

Cannabinoid receptor signaling may also affect pSMAD158 activity via pERK. Bone

30 morphogenic proteins act through the SMAD158 complex to commit MSCs to the osteoblasts lineage and may also redirect MSC differentiation into the osteoblast lineage

(Iacono et al., 2007; ten Dijke, 2006). SMADs efficiently regulate differentiation through interactions with important transcription factors, such as Runx2. There is a fairly established role for the SMAD158 complex in skeletal health and regeneration (Rath et al., 2011; Song et al., 2009). However, much more work remains to determine the full extent at which SMADs can regulate MSC differentiation. Researchers also do not know many of the ligands and receptors that are important for SMAD activation during tissue differentiation and repair. Perhaps cannabinoid receptors may be another source of

SMAD regulation, but there is no available published data regarding cannabinoid regulation of the SMAD158 complex in osteoblasts, or any other cell type. There is one cannabinoid-SMAD study published, which investigated WIN55,212 mediated activation of SMAD2/3 in epidermal tissue (Balistreri et al., 2011). Cannabinoid receptor activation of ERK and the SMAD158 complex would be a novel finding. Figure 1.3 is a hypothetical diagram of cannabinoid signaling in osteoblasts.

Towards a Model of the ECS in the Bone Microenvironment

New evidence demonstrates that the ECS is found on both the immature and mature cells that regulate bone metabolism (George et al., 2008; Idris et al., 2009; Jiang et al.; Ofek et al., 2006a; Tam et al., 2006; Tam et al., 2008). The cells which reside within calcified bone express both the CB1 and CB2 cannabinoid receptors and associated endocannabinoids (Hutchins et al.). For example, osteoblasts contain the machinery for synthesizing the endocannabinoids anandamide and 2-AG.

Endocannabinoids and synthetic agonists are capable of modulating RANKL and

FIGURE 1.3. HYPOTHETICAL PATHWAY OF CANNABINOID SIGNALING CASCADE IN OSTEOBLASTS. Cannabinoid receptors may influence the activity of MAP kinases, p-SMAD158 complex, and AKT in mesenchymal stem cells (i.e., immature osteoblasts, MC3T3-E1 cell line).

protegerin production in osteoblasts. RANKL and protegerin are important regulators of osteoclasts (Idris et al., 2008; Tam et al., 2006)

Collectively, the base knowledge of the ECS in bone supports the speculation that cannabinoids can regulate important events such as osteoblast development, proliferation, and coupling.” The ECS may be an important regulator bone metabolism , however most of the published studies are focused on “osteoblast-osteoclasts”, the CB2

32 receptor and osteoclasts. Increasing our knowledge of the CB1 receptor’s role in bone is critical to shaping our understanding of the functions of the ECS in basic bone biology, and how the ECS contributes to the health and disease of this tissue. The role of CB2 receptor in osteoclasts is the focus of many research publications, demonstrating that the

CB2 receptor is important for proper bone development and is associated with osteoporosis in human populations (Karsak et al., 2005b; Karsak et al., 2009; Ofek et al.,

2006b). Despite these interesting findings on a component of the ECS, the amount of information of CB1 is lacking leaving a gap of knowledge that prevents an effective description of how the ECS can regulate bone. Both receptors appear to be important, as animal models of CB1 or CB2 KO mice reveal a phenotype with alterations bone metabolism (See Figure 1.4).

Microcomputed Topograhpical (µCT) analysis of bones of CD1 CB1 KO mice revealed effects on bone volume. The histomorphetric analysis performed by Idris et al (2005) effects on bone volume. The histomorphetric analysis performed by Idris et al (2005) showed a decrease in osteoclast number and bone resorption, while no effect on osteoblast numbers was observed. These results suggest that while osteoclasts demonstrate a drastic response to cannabinoid receptor deficiencies, the effects on osteoblasts may be more subtle. While Idris et al (2005) found that ablation of CB1 receptors resulted in high peak bone mass in young CD1 mice, practically opposite results were obtained from C57/Bl6 CB1 KO mice, which were found to display low bone mass (Tam et al., 2006). Interestingly, the C57/Bl6 mice are hypersensitive to leptin (Takeda and Karsenty, 2008). It should be noted that both CD1 and C57/Bl6 CB1

KO strains exhibit severe age-related osteoporosis.

The components of the ECS are present in the cellsvariety comprising of mechanisms the bone marrow stem cell niches. A stem cell niche is a specific anatomic location where there is an established population of stem cells. The ECS may be active in these niches which help regulate tissue regeneration, maintenance, and repair through a

FIGURE 1.4 µCT ANALYSIS OF CANNABINOID RECEPTOR DEFICIENT MICE. µCT images of distal femurs representing the bone mass phenotypes in CB1 and CB2 KO mice. A) Male and female CB1 KO mice with a C57/Bl6 background display a decrease in percent bone volume. Male and female mice with a CD1 background display an increase in percent bone volume. B) Distal femoral analysis of CB2 KO in mice with C57/Bl6 background, demonstrates a low bone mass phenotype.

FIGURE 1.5 SCHEMATIC DIAGRAMS OF BONE. A) generic long bone, B) illustrated stem cell niche, C) illustrated OB-HSC interactions, and D) a bone H&E of human bone marrow section. The bone trabeculae is lined by osteoblasts that are closely associated with neighboring HSCs and Maturing HCS precursors (MBCs), which together form the endosteal niche that is adjacent and intermingled to fenestrated sinusoidal capillaries (C). All cellular elements reside in a stromal scaffold that is formed by a groups of stromal cells (composed reticular cells, reticular fibers, and) MSCs. Different types of stromal cells, may regulate stem cell activation, proliferation, mobilization, and differentiation by secreting different microenvironmental signals.

CB1 are also observed in the developing human brain. Another important aspect of bone development and maintenance is the regulation of stem cell niches and osteoblast coupling to other cells. Figures 1.7 and 1.8 provide evidence of the CB1 receptor’s involvement in osteoblast and osteoclast coupling. It was recently reported that the ECS is a regulator of hematopoietic stem and progenitor cell (HSC) interactions with theirbone marrow niches (Jiang et al., 2010). Jiang et al (2010) isolated the HSC from C57/Bl6

WT, CB1 KO, CB2 KO, and FAAH KO mice with the same background. The authors found that cannabinoid receptors are expressed and endocannabinoids are secreted by bone marrow stem cell niches. The term niche is often used by the scientific community to describe the in vitro and in vivo microenvironment in which stem cells are found, a microenvironment that is also involved in regulating differentiation or cell fate. A niche constitutes a basic unit of physiology that integrates the signals which mediate the activity of stem cells (Scadden, 2006). These niches are essentially formed from hematopoietic stem cells located in proximity to stromal cells and osteoblasts (Levesque et al., 2010). The bone structure and adjacent cells are important for cellular events such as the control of cell cycle and proliferation. The close proximity of the hematopoietic stem cells suggests that there is molecular cross talk between the different cell types forming these niches which may be mediated by the ECS during osteoblast-osteoclast coupling and osteoblast- hematopoietic stem cell (HSC) interactions

The bone marrow HSC niche is probably the best characterized stem cell population, although much more work is needed to clearly define the function of the cells and the intricate molecular mechanism within the niche. The HSC niche is categorized as

36 being adjacent to bone trabeculae and capillaries, as HSCs are preferentially found localized in the endosteal region (Mendez-Ferrer 2010). Figure 1.5 provides an example of a HSC niche within bone marrow and an example of OB-HSC interactions.

Mesenchymal stem cells, or stromal cells, are located in bone marrow stem cell niches, muscle, and fat (Levesque et al., 2010). These cells can potentially differentiate into cartilage, muscle, fat, and bone cells such as osteoblasts. Osteoblasts are the bone cells that make the bone matrix and direct its mineralization into mature bone.

Osteoblasts differentiate from stromal cells, and the differentiation process can be divided into different stages: proliferation, matrix deposition, and mineralization. Mature osteoblasts re-differentiate to form osteocytes and bone lining cells; cells which play a major role in calcium regulation and bone remodeling. Osteoblast differentiation is often studied by measuring the expression of distinct differentiation markers. These markers include ALP, type 1 collagen, bone sialoprotein, osteopontin, and osteocalcin. ALP is considered an early marker of osteoblast differentiation while osteocalcin is a late marker. Methods to characterize osteoblast cultures include combining techniques such as measuring cell proliferation, ALP activity, and signal transduction mechanisms, such as the MAP kinase cascade. CB1 receptors or CB1 mRNA appears to be present in stromal cells, osteoblasts, osteoclasts, macrophages, fat cells, and bone marrow stromal cell cultures and other cells which constitute a niche (Idris et al., 2009; Idris et al., 2005;

Tam et al., 2006). Figure 1.6 demonstrates that the CB1 receptor is expressed in various cells of the bone microenvironment and that CB1 receptor levels may increase over time in bone marrow cells. The CB2 receptor is also present on osteoblasts and the levels of expression increases in bone marrow niches when exposed to osteogenic factors

FIGURE 1.6. CB1 RECEPTOR EXPRESSION IN VARIOUS CELL TYPES. A) Expression of CB1 mRNA assessed by quantitative PCR and expressed as the number of molecules per nanogram of total mRNA in various cells and tissues. B) Expression of CB1 mRNA freshly isolated from bone marrow cells. Data demonstrates that CB1R is expressed by MSCs and osteoblasts and CB1R levels may increase with age.

(Ofek et al., 2006a). The presence of the ECS in cells, which comprise stem cell niches within bone, suggests a role for the ECS in bone maintenance.

Evidence has been offered which suggests that the expression of CB1 receptors is dependent on proper differentiation factors (Tam et al., 2006). There is also evidence that bone stem cells increase CB1 mRNA during differentiation (Bab, 2007; Ofek et al.,

2006a; Tam et al., 2006). Taken together, stromal cells may increase or decrease levels of CB1 and/or CB2 receptors when exposed to the proper osteogenic factors. Figure 1.6 provides indirect evidence that the levels of cannabinoid receptors may become elevated

38 in mature bone cells compared to stromal cells, suggesting the involvement of the CB1 receptor in cell differentiation or proliferation. These transient levels of CB1 receptors imply a role for this protein in developmental events, as transient expression levels of

75.6 pg/10^7 cells and 75.2-98.8 ng/107 cells, respectively. CB1 KO and CB2 KO HSCs demonstrated a decrease in cell population. Cultures from FAAH KO micedemonstrate increased colony formation, perhaps due to elevated levels of anandamide. Cannabinoid receptors bone cells appear to be targets of endocannabinoids and other lipids. Given the many classes of lipids, future studies could find new and important roles in bone biology for lipids, especially endocannabinoids (Ross, 2005). Future studies could provide pharmacological interventions for HSCs-based treatment of bone diseases, which could target the ECS.

FIGURE 1.7. CB1 RECEPTOR DEFICIENCY MAY IMPAIR OSTEOBLASTS. Cell co-cultures were prepared, comprised of Osteoblast-bone marrow and bone marrow macrophage cultures. The culture were treated with factors to induce osteoclast formation. The factors are RANKL and M-CSF. Osteoclast formation was significantly reduced in co-cultures prepared from CB1 KO vs WT. This effect was rescued by the addition of WT OB. The effect of CB1-/- on osteoclast numbers is rescued by the addition of WT OB. This implies that the CB1 deficiency may impair the ability of osteoblasts to support osteoclast function. Effects of CB1 KO on osteoclasts are mediated by osteoblasts, possibly due to a decrease in the coupling the usually occurs between these cells.

Jiang et al. (2010) also found that the cannabinoids Δ9-THC, anandamide , and

CP55,940 could increase the number of colony forming units formed and migration of human and murine cells. The effect of Cannabidiol, Cannabinol, and

Tetrahydrocannabivarin were assayed on cultures of primary stromal cells (Scutt and

Williamson, 2007). Figures 1.9 and 1.10 demonstrate CB1 effects on cell proliferation and migration. Cannabidiol is a bicyclic cannabinoid that does not bind to a known

40 cannabinoid receptor but can affect activity of other cannabinoids such as Δ9-THC in vivo and in vitro. Cannabidiol was able to stimulate CFU formation. Cannabinol, the degradation product of Δ9-THC, was able to stimulate CFU formation 2 to 3 times above control cells. Terahydrocannabivarin occurs in <1% of plant material, originally identified as an antagonist, this cannabinoid was able to stimulate CFU formation but it’s affects were blocked by a CB2 antagonist (Scutt and Williamson, 2007; Thomas et al.,

2005). In the case of Tetrahydrocannabivarin co-applied with AM630, the authors may have been comparing the effects of dual blockade of CB1 and CB2 on stromal cell proliferation. Activating the CB1 receptor, or perhaps both receptors, is able to stimulate bone cell proliferation. In summary, Scutt 2007 demonstrated that non- -specific cannabinoids agonists can increase CFUs of stromal cells, concluding that it must be mediated through the CB2 receptor, yet the authors did not examine the effects of a single potent, selective CB1 agonist, only antagonists. Unfortunately, previous studies have not examined the effects of CB1 agonists or CB1 ablation in primary stromal cells.

FIGURE 1.8. CB1 RECEPTOR DEFICIENCY IMPAIRS RANKL. Osteoclast formation is critically dependent on RANKL expressed by osteoblasts. RANKL was analyzed using a quantitative PCR technique to measure RANKL mRNA. RANKL does not fully explain the effect of CB1 KO but this provides a mechanism for a decrease in coupling between these cells.

Cannabinoids may direct stromal cell differentiation, for example into osteoblasts versus adipocytes (Idris et al., 2009). Bone marrow stromal cells from CB1 KO mice

FIGURE 1.9. CB1 RECEPTOR EFFECTS ON CELL PROLIFERATION. Nonspecific agonists can increase colony forming units of bone marrow cultures isolated from Wistar rats. Implying cannabinoids can, perhaps, stimulate the proliferation of bone cells. Treatment of CFU-f cultures with a variety of naturally occurring cannabinoids, including cannabidivarin (CBDV), cannabigerol (CBG), cannabinol (CBN), cannabidiol (CBD), THC, and tetrahydrocannabivarin (THCV), all at 10 uM, produced a stimulation of colony formation in all cases. This increase in colony number was also reflected by a parallel increase in the number of colonies that were positive for both ALP expression and collagen synthesis or differentiating osteoblasts through markers of differentiation such as ALP activity (Jiang et al.; Scutt and Williamson, 2007).

have enhanced adipocyte differentiation. This observed increase in adipogenesis can be reproduced using CB1 selective antagonists, such as AM251, in WT stromal cell cultures (Idris et al., 2009). If cannabinoids are modulating the differentiation of stromal

43 cells, then some of the observed affects on bone in CB1/2 KO mice may be related to fewer stromal cells differentiating into osteoblasts.

Tam et al (2006) also looked at the effect of CB1 ablation on new bone formation using a model of traumatic brain injury (TBI) to stimulate bone growth. Importantly, the

ECS mediated effect on bone growth after a TBI was observed in both CD1 and C57/Bl6 mice. The authors report that upon TBI stimulation, the levels of 2-AG increase, suppressing the release of norepinephrine through CB1 receptors on bone sympathetic nerve terminals, leading to the activation of osteoblasts. Figure 1.10 displays data from

Tam’s 2008 findings on Bone and CB1. The data is the result of a bone injury model.

Tam el al also suggests a model of CB1 regulation of bone formation by modulating

FIGURE 1.10 ROLE OF CB1 RECEPTORS IN HEALTHY AND INJURED BONE. A) The rate of bone formation and mineral apposition in WT and CB1 KO mince. B) The effects of traumatic brain injury on bone formation and mineral apposition in WT and CB1 KO mice. C) Model of CB1 bone regulation thru modulating adrenergic signaling. Activation of CB1 receptors in bone sympathetic nerve terminals, restrains NE release. Thus, alleviating the tonic suppression of bone formation by the sympathetic nervous system.

45 adrenergic signaling. The activation of CB1 receptor in bone sympathetic nerve terminals, restrains norepinephrine release. Thus CB1 activation alleviates the tonic suppression of bone formation by the sympathetic nervous system. It is important to note that beta adrenergic neurons are considered to be present and active in stem cell niches.

Without a CB1 receptor the mesenchymal stem cells may be inhibited from migrating to sites of injury and poorly differentiate into osteoblasts upon arrival. It is unclear if this

CB1 KO decrease in bone formation and mineral apposition is unique to head injuries, or is a CB1 mediated effect in bone injuries in general.

Summary of Cannabinoid and Bone Research

There is supportive evidence for a role of the ECS on bone cells, specifically osteoblasts. However, the current knowledge base is lacking important information on cannabinoid receptor mechanisms at work in osteoblasts. Future experiments on cannabinoids and osteoblasts should provide signaling mechanisms to explain the bone phenotype observed, incorporate measurements of osteoblast proliferation, and osteoblast differentiation markers such as ALP.

Cannabinoids can affect the proliferation and perhaps the differentiation of cells within the bone stem cell niche. This implies that the ECS may be important for proper bone development and maintenance. However, much remains to be done in order to characterize these cells that are influenced by cannabinoids. Additionally, the CB1/2 KO model represents a unique opportunity to study the importance of the ECS. While bearing in mind that the data on CB1 receptor in bone is lacking, we can focus some experiments to help clarify the importance of this receptor in relation to other members of

46 the ECS, such as the CB2 receptor. Another important aspect of this effort will be attempting to uncover the mechanism behind cannabinoid receptor effects of bone such as looking at the activity of MAP kinases, pAKT, and pSMAD158 complex activity.

Western blot analysis of mesenchymal stem cells assayed with a diverse selection of cannabinoid receptor agonists is a logical first step to gain insight into the molecular mechanisms underpinned by the ECS.

Specific Aims

There are two specific aims for this thesis. The following sections introduce the specific aims and the goals of those aims. In chapter 2 and 3 the data generated to investigate the specific aims will be discussed in detail.

Specific Aim 1: Novel Insights into CB1 Cannabinoid Receptor Signaling: A Crucial

Interaction Identified between EC3-Loop and TMH2 (Publication in process)

Site-directed mutagenesis techniques will be employed to investigate the role of amino acids resides of the CB1 receptor. We will substitute alanine for each of our mutations: K3.28A, D2.63A, K3.28A, D2.63A-K373A, and S1.39A. Receptor function will be measured by GTPγS stimulation and binding analysis with tritiated CB1 ligands.

The results of mutational analysis will be analyzed by molecular modeling techniques.

In chapter 2 the results of this study will be discussed in detail, while considering how this project will add to the mutagenesis knowledge base for the CB1 receptor, and will assist in molecular modeling as well as the understanding of ligand-receptor interactions. In chapter 4, we will revisit the discussion on mutagenesis and molecular

47 modeling but with the intention of examining a translational potential for this type of data in pharmaco-genomic medicine.

Specific Aim 2: The Anabolic role of Cannabinoid Receptors in Bone: Targeting

Cannabinoid Receptors in Osteoblasts.

We hypothesize that the endocannabinoid system plays a role in bone health. The ablation of cannabinoid receptors has been shown to disrupt normal bone development.

Previous research suggests the presence of cannabinoid receptors in mesenchymal stem cells, osteoclasts, and osteoblasts. The activation/antagonism of these receptors may also affect levels of pERK and other important signaling molecules in these cells. Our preliminary data demonstrates differences in staining of the early differentiation marker

ALP, and cell proliferation between the Wild-Type (WT) and CB1/2 KO primary osteoblasts isolated from calvaria of neonatal mice.

Experiments in this aim will test the effects of CB1 and CB2 antagonists on cell proliferation and signaling pathways. The results of this aim will indicate whether the cannabinoid receptors play a significant role in osteoblastogenesis and will provide insight on the cellular mechanisms of cannabinoid receptors in bone maintenance. In

Chapter 3 we will discuss the data generated to address this aim.

CHAPTER 2 NOVEL INSIGHTS INTO CB1 CANNABINOID RECEPTOR SIGNALING: A CRUCIAL INTERACTION IDENTIFIED BETWEEN EC3-LOOP AND TMH2

Introduction

The cannabinoid CB1 receptor (CB1), a member of the class A rhodopsin-like family of G protein-coupled receptors (GPCRs) (see Fig.1.1), is found primarily in the central nervous system (CNS) and is important in the regulation of neuronal activity. In addition, there is evidence that the CB1 receptor is expressed in peripheral tissues (albeit to a lesser extent), including the adrenal gland, bone marrow, heart, lung, and prostate

(Howlett et al., 2002). The CB1 receptor, a Gi/o coupled GPCR, binds five structurally diverse classes of ligands; these include the endocannabinoids (typified by anandamide and 2-arachidonoylglycerol), the classical and nonclassical cannabinoids (typified by

HU-210 and CP55,940, respectively), the aminoalkylindoles (typified by WIN55,212-2), and the diarylpyrazole antagonists/inverse agonists (typified by SR141716A) (Picone et al., 2002).

Considering its fundamental role in the CNS, it is not surprising that the CB1 receptor has been reported to mitigate numerous pathologies, including Alzheimer’s disease, cancer, obesity, and pain (Pertwee, 2009). Unfortunately, many attempts at harnessing the therapeutic potential of the CB1 receptor have failed due to unacceptable

CNS-related side effects, such as euphoria, depression, and suicidal fixation

(Christopoulou and Kiortsis, 2011). Clearly, a better understanding of the CB1 receptor’s signal transduction mechanism(s), at a molecular level, would be useful in realizing this receptor’s therapeutic potential.

Traditionally, the high degree of sequence homology of amino acid residues from transmembrane helices (TMHs) of different GPCRs has led to the identification of conserved residues, which have been shown to be crucial for receptor function using biochemical studies (Tao and Abood 1992, Roche et al 1992). In the third TMH of the

CB1 and CB2 receptors is a conserved lysine reside Lys 192 (K3.28), which plays an important role in selective ligand binding (song and bonner). We began our investigation by corroborating this study with the establishment of a K3.28A mutant cell line that demonstrates selective ligand recognition between different structural classes of cannabinoids such as WIN55,212, CP55,940, and AM4056.

In addition, charged interactions between amino acid residues from different

TMH domains have been shown to be essential for either ligand binding or receptor function (Sealfon et al., 1995; Xu et al., 1999; Zhou et al., 1994). Residues from the extra-cellular (EC) loops demonstrate low sequence homology (Peeters et al., 2011b) and were initially thought to connect the TMH domains rather than have a direct role in receptor functioning.

However, recent studies have demonstrated the critical role of the extracellular loops to ligand binding and receptor signaling. Mutation studies have demonstrated that the first extracellular loop (EC-1 loop) is important to activation of the adenosine A2B receptor (Peeters et al., 2011a). The second extracellular loop (EC-2 loop) has been shown to be important in ligand binding and activation at the V1a vasopressin receptor

(Conner et al., 2007), helix movement in rhodopsin (Ahuja et al., 2009), and is involved in the binding of allosteric modulators at the M2 acetylcholine receptor (Avlani et al.,

2007). Less is known about the third extracellular loop (EC-3 loop); however, a key salt

50 bridge between the EC-3 and EC-2 loops has been observed to influence ligand binding and receptor activation at the β2 adrenergic receptor (Bokoch et al., 2010).

The EC-1 and EC-2 loops of the CB1 receptor (Ahn et al., 2009a; Bertalovitz et al., 2010; Murphy and Kendall, 2003) have been better characterized than its EC-3 loop.

EC-3 loop modeling studies reported here suggest that the EC-3 loop residue K373 may form a functionally-important ionic interaction with a transmembrane residue, D2.63176.

Our previous D2.63176 mutation studies have demonstrated that the negative charge of

D2.63176 is critical for agonist efficacy, but not ligand binding at the CB1 receptor (Kapur et al., 2008). We hypothesized that this functional requirement (of a negatively-charged residue at 2.63176) may be due to this residue’s participation in an ionic interaction with

K373 that is necessary for signal transduction. To test this hypothesis, three mutations that would disrupt this putative interaction, D2.63176A, K373A, D2.63176A-K373A and a charge reversal mutation D2.63176K-K373D that would restore the interaction were evaluated for their impact on ligand binding and agonist efficacy. The S1.39A mutant was also created to provide preliminary data for future investigations into the role of this residue in maintaining protein structure, but molecular modeling experiments are ongoing to determine a conclusive role. The binding affinities for CP55,940 and SR141716A were not significantly affected by any of the mutations. However, the efficacy of

CP55,940 and WIN55,212-2 was markedly reduced by the alanine-substitution mutations, while the charge reversal mutation led to partial rescue of WT levels of efficacy. Computational results indicate that the D2.63176-K373 ionic interaction strongly influences the conformation(s) of the EC-3 loop, providing a structure-based rationale for the importance of the EC-3 loop to signal transduction in CB1. Specifically, the putative

51 ionic interaction results in the EC-3 loop pulling over the top (extracellular side) of the receptor; this EC-3 loop conformation may serve protective and mechanistic roles.

Our results have for the first time identified an interaction between the residues from TMH2-ECL3, suggesting the proximity of these 2 domains and their role in modulating CB1 signal transduction.

Materials and Methods

Materials

[3H]CP55,940 (160-180 Ci/mmol) and [35S]GTPγS (1250 Ci/mmol) were purchased from PerkinElmer (Boston, MA). WIN55,212-2, CP55,940, and SR141716A were obtained from Tocris (Ellisville, MI). Pfu Turbo DNA polymerase for mutagenesis experiments was from Stratagene (La Jolla, CA). All other reagents were obtained from

Sigma or other standard sources. CB1 antibody was kindly provided by Ken Mackie

(Indiana University).

Amino Acid Numbering

The numbering scheme suggested by Ballesteros and Weinstein was employed here (Ballesteros and Weinstein, 1995). In this system, the most highly conserved residue in each TMH is assigned a locant of 0.50. This number is preceded by the TMH number and followed by the absolute sequence number in superscript. All other residues in a TMH are numbered relative to this residue. Sequence numbers used are human CB1 sequence numbers unless otherwise noted (Bramblett et al., 1995).

Mutagenesis and Cell Culture

The K3.28A, S1.39A, D2.63176A, K373A, D2.63176A-K373A, and D2.63176K-

K373D mutants of the human CB1 in the vector pcDNA3 were constructed using the

QuikChange site-directed mutagenesis kit (Stratagene, La Jolla, CA). The mutagenic oligonucleotides used were between 27-33 base pairs long. Restriction endonuclease digestion and DNA sequencing subsequently confirmed the presence of the mutation.

Stably transfected HEK-293 cell lines were created by transfection with wild-type or mutant CB1-pcDNA3 cDNA by the Lipofectamine reagent (Invitrogen, Carlsbad, CA) and selected in growth medium containing geneticin (1 mg/ml) as previously described

(McAllister et al., 2003).

Radioligand binding and GTPγS Binding Assay

Protein membrane preparations harvested from stably transfected HEK293 cells were prepared and assayed as previously described (Kapur et al., 2007). In brief, binding assays (saturation and competition binding assays) were initiated by the addition of 50 µg membrane protein to glass tubes pretreated with siliconizing fluid (Pierce, Rockford, IL; to reduce nonspecific binding) containing [3H]SR141716A, and an appropriate volume of binding buffer A (50 mM Tris-Base, 1 mM EDTA, 3 mM MgCl2, and 5 mg/ml BSA, pH

7.4) to bring the final volume to 500 µl. Nonspecific binding was determined in presence of excess (1 µM) unlabelled SR141716A. Reactants were allowed to reach equilibrium

(~1hr). Subsequently, free and bound radioligand were separated by vacuum filtration through Whatman GF-C filters, and the radioactivity retained on the filters was quantified by a liquid scintillation counter.

The Kd (equilibrium dissociation constant) and Bmax (maximal binding) values were determined by analyzing the saturation binding data by nonlinear regression and fitted to one-site binding model using GraphPad Prism 4.0 software (GraphPad, San Diego, CA).

The displacement log IC50 values were determined by nonlinear regression and fitting the data to one-site competition and then converted to Ki (inhibitory constant) values using the Cheng and Prusoff method (Cheng and Prusoff, 1973) with the use of GraphPad

Prism.

The GTPγS assay was initiated by the addition of 20 µg of membrane protein into silanized glass tubes containing 0.1 nM [35S]GTPγS, 10 µM GDP in GTPγS binding buffer (50 mM Tris-HCl, 100 mM NaCl, 3 mM MgCl2, 0.2 mM EGTA, 0.1% BSA, pH7.4). Nonspecific binding was assessed in the presence of 20 µM unlabeled GTPγS.

Free and bound radioligand were separated and bound radioactivity was quantified as described above. Nonlinear regression of log concentration values versus percent effect, fitted to sigmoidal dose-response was used to obtain estimates of agonist concentrations that elicit half the maximal response (EC50) and maximal response (Emax).

Statistical Analyses

Data are reported as mean value of the replicates along with their 95% confidence limits. The Ki and log EC50 values in the mutant and wild-type CB1 receptors were compared using one way ANOVA with Bonferroni multiple comparison post tests. P values of <0.05 were deemed to be statistically significant

Molecular Modeling

Receptor model construction protocol for loop calcuations

Wild-type (WT) CB1 Activated (R*) Receptor Model Construction—Using interactive computer graphics, extracellular (EC-1 F180–S185, EC-2 G254–E273, and EC-3 G369–

K376) and intracellular loops (IC-1 R145–R150, IC-2 P221–T229, and IC-3 S303–

M336) were manually added to our previously constructed transmembrane helix (TMH) bundle model of the CB1 R* (active state) receptor, with CP55,940 docked in its global minimum energy conformation (Kapur et al., 2007). The program Modeller was then used to refine loop structures (Fiser et al., 2000; Sali and Blundell, 1993). Because of their close spatial proximity, the conformations of all three extracellular loops were calculated together followed by calculation of the three intracellular loop conformations.

Chosen loop conformations were those that produced a low value of the Modeler objective function. The loops were minimized in three stages (Stages 1-3 described below). Next, portions of the N and C termini were added and conformations of each refined in Modeller. The termini were minimized using stages 4-5 of the minimization protocol.

N terminus- The first 89 residues of the N-terminus were truncated, based on results from the Chin lab (Andersson et al., 2003) which showed that CP55950 has wild-type (WT) binding affinity and efficacy at the N-terminal truncated CB1, while the receptor has better cell surface expression than WT. X-ray crystal structures of Class A GPCRs with lipid-derived endogenous ligands show that the N-terminus occludes the binding pocket.

In the crystal structure of rhodopsin (Li et al., 2004), the N terminus is positioned centrally, occluding the extracellular side of the bundle (i.e. the retinal plug). This general placement of the N terminus is also observed in the crystal structure of the

55 sphingosine 1-phosphate receptor (Hanson et al., 2012). Since CB1 also has a lipid- derived endogenous ligand, a truncated N terminus conformation (positioned centrally over the extracellular side of the receptor) was chosen.

EC-2 loop—One of the significant sequence divergences between rhodopsin and CB1 is in the second extracellular (EC-2) loop region. This loop in CB1 is shorter than in rhodopsin and is missing the conserved disulfide bridge between the cysteine in the EC-2 loop and C3.25 in TMH3 of rhodopsin. Instead, there is a Cys at the extracellular end of

TMH4 in CB1 and a Cys near the middle of the EC-2 loop that experiments suggest may form a disulfide bridge (Fay et al., 2005). Consequently, the position of the EC-2 loop with respect to the binding site crevice in CB1 around TMHs 3, 4, and 5 is likely to be quite different from that in rhodopsin. Therefore, this loop was modeled with an internal

C257–C264 disulfide bridge based upon mutation results from the Farrens lab (Fay et al.,

2005), which show that these two cysteines are required for high-level expression and receptor function. To guide selection of an appropriate EC-2 loop conformation, we used mutation results from the Kendall lab (Ahn et al., 2009a; Bertalovitz et al., 2010) which demonstrate that mutation of EC-2 loop residue F268 to a tryptophan severely damages the binding affinity and efficacy of CP55,940, but has no significant effect on the binding affinity of SR141716A. Thus, an EC-2 loop conformation was chosen that placed F268 in close proximity to CP55,940. A F268W mutant bundle was constructed to verify that this mutation resulted in significant steric overlaps with CP55,940 in our model but not with SR141716A (see Supp. Fig 1).

EC-3 loop—The extracellular loops were refined using Modeller, in two stages; in the first stage, no harmonic distance constraints were used. This calculation was performed

56 to examine the general conformational space of the EC-3 loop. The EC-3 loop conformation with the lowest objective function placed the EC-3 loop over the top of the receptor; in addition, the putative ionic interaction between D2.63176 and K373 had formed. In the second stage, a 3.0 kcal/mol harmonic distance constraint was placed between the EC-3 loop residue K373 and D2.63176. Specifically, the distance between the

OD1 atom of D2.63176 and the NZ atom of K373 was constrained to 3.0 ± 2.0 Å. This second calculation was performed to obtain a focused conformational sampling of the

EC-3 loop conformation with the lowest objective function (obtained in the first stage of the calculation).

IC-3 loop—The CB1 IC-3 loop is much longer than the corresponding sequence in

Rhodopsin. NMR experiments have been performed on a peptide fragment composed of the CB1 sequence span from the intracellular end of TMH5 to the intracellular end of

TMH6, in micelles (Ulfers et al., 2002). This study suggested that part of the IC-3 loop is

α helical. This region occurs after the intracellular end of TMH5 [K5.64300] and consists of a short α-helical segment from A301 to R307, followed by an elbow region (R307–

I309) and an α-helical segment (Q310–S316) up to an III sequence (I317–I319) in IC-3.

Based on these results, we replaced the initial Modeller-built IC-3 loop with this α-helix- elbow-α-helix region and then the rest of IC-3 loop (I317–P332) was rebuilt and optimized using Modeller.

C terminus—A C terminal fragment S414–G417, which contains a putative palmitoylation site at Cys415 (Fay et al., 2005), was added to the model and C415 was palmitoylated. C-terminus truncation experiments from the Mackie lab (Jin et al., 1999) have shown that CB1 (with truncation at C417) signals normally in the presence of

57 agonists. With the exception of Helix 8, the C terminus is largely unstructured, though recent work on an isolated C terminus peptide suggests the existence of an additional C terminal helix, Helix 9 (Ahn et al., 2009b). However, recent results from the Mackie lab

(Straiker et al., 2012) reinforce that the functional significance of the C terminus pertains to desensitization and receptor internalization—not necessarily receptor signaling by heterotrimeric G proteins. Therefore, we modeled the truncated C terminus as unstructured.

Receptor Model Energy Minimization Protocol—The energy of the ligand/CB1 R* complex, including loop regions and N and C termini, was minimized using the OPLS

2005 force field in Macromodel 9.9 (Schrödinger Inc., OR). An 8.0-Å extended nonbonded cutoff (updated every 10 steps), a 20.0-Å electrostatic cutoff, and a 4.0-Å hydrogen bond cutoff were used in each stage of the calculation. The minimization was performed in five stages. In the first stage of the calculation, the ligand and TMH bundle were frozen, but the loops were allowed to relax. The generalized born/surface area continuum solvation model for water as implemented in Macromodel was used. This stage of the calculation consisted a of Polak–Ribier conjugate gradient minimization in

1000-step increments until the bundle reached the 0.05 kJ/mol gradient. Since mutation results from the Kendall lab (Ahn et al., 2009a; Bertalovitz et al., 2010) demonstrate that mutation of EC-2 loop residue F268 to a tryptophan severely damages the binding affinity and efficacy of CP55,940, the terminal side-chain hydrogen of F268 (atom name:

HZ) was frozen in place. Freezing this hydrogen allowed F268 the most conformational freedom, allowing the side-chain to pivot about HZ, while requiring F268 to stay in close proximity to CP55,940. The second stage of the calculation was performed exactly as the

58 first stage, except that HZ of F268 was unfrozen. In the third stage, the loops were frozen but the ligand and the side-chains of the TMHs were allowed to optimize. The minimization consisted of a conjugate gradient minimization using a distance-dependent dielectric, performed in 1000-step increments until the bundle reached the 0.05 kJ/mol gradient. Because a previously minimized TMH bundle was used as the starting structure in constructing this model (Kapur et al., 2007), the backbone atoms of the transmembrane helices were frozen to prevent the bundle from over packing. In the fourth stage, the N and C-termini were minimized using the same protocol used in second stage. In this stage, only the termini were minimized. In the fifth stage, the TMH bundle was minimized again, exactly as described in the third stage.

Mutant CB1 Activated (R*) Receptor Models Construction and Minimization—four mutant bundles were constructed: K373A, D2.63176A, D2.63176A-K373A, and

D2.63176K-K373D. These mutant models were constructed using the final WT CB1 R* model(Kapur et al., 2007) as the starting structure, using interactive computer graphics to perform the appropriate mutations. The N terminus was temporarily removed to prevent it from biasing mutant loop refinement. Modeller was used (as before) to refine the EC-1 and EC-3 mutant loop structures. No harmonic distance constraint was used for the alanine-substitution mutants (however, the same distance constraint used for WT was also used for D2.63176K-K373D). The WT conformations of the EC-2 loop, the intracellular loops and the termini were preserved. As with the WT CB1 R*, chosen loop configurations for the mutant bundles were those that produced a low value of the modeler objective function; the loops were minimized using stages 1-3 of the minimization protocol (see above). Next, the N terminus was reattached to the mutant

59 bundles. The termini were minimized using stages 4-5 of the minimization protocol (see above).

Assessment of pairwise interaction and total energies

Interaction energies between CP55940 and the WT, K373A, D2.63176A, D2.63176A-

K373A, or D2.63176K-K373D receptors were calculated using Macromodel

(Schrodinger). After defining the atoms of CP55,940 as one group (group 1) and the atoms corresponding to a residue that lines the binding site in the final ligand/CB1 R* complex as another group (group 2), Macromodel was used to output the pair-wise interaction energy (coulombic and van der Waals) for a given pair of atoms. The pairs corresponding to group 1 (ligand) and group 2 (residue of interest) were then summed to yield the interaction energy between the ligand and the receptor.

Results

The binding of [3H]SR141716A to WT and mutant receptors stably expressed in

HEK 293 cells was measured to generate an estimate of the Kd and Bmax values. Similar cell surface expression of WT and mutant cell lines was verified by immunofluorescence staining (data not shown).

Radioligand Binding Assays. Saturation binding analysis of [3H]SR141716A at the

176 176 176 D2.63 A, K373A, D2.63 A-K373A, and D2.63 K-K373D mutations displayed Kd

(CI) values of 4.2 (0.1-9.8) nM, 1.7 (0.2-3.5) nM, 4.4 (0.1-9.1) nM, and 3.5 (0.1-24) nM, respectively (see Table 2.1). The S1.39A mutation demonstrated a Kd of 4.93(0.38- 9.5) nM. The Kd for the WT hCB1 receptor was 2.2 (0.4-3.9) nM. The Kd values for the mutants vs. WT are not statistically different.

Similarly, the Bmax values for each cell line demonstrated that expression levels of these receptors between the different cell lines were comparable. The cell lines

176 176 176 D2.63 A, K373A, D2.63 A-373A, and D2.63 K-K373D respective Bmax (CI) values were 2.3 (1.0-3.5) pmol/mg, 1.8 (0.1-3.7) pmol/mg, 2.7 (1.7-3.7) pmol/mg, and 0.7 (0.1-

2.4) pmol/mg. The S1.39A cell line generated a Bmax 4.4nM (0.7-27). The WT CB1 cell line displayed a Bmax of 2.4 (1.9-2.9) pmol/mg.

Competitive Binding Assays. We investigated the binding affinity of the bicyclic cannabinoid agonist CP55,940 to displace [3H]SR141716A bound to the WT and mutant hCB1 receptors. The Ki values between WT and mutant receptors overlap and were not

176 significantly different (see Table 2.2, Fig. 2.2). The Ki (CI) values for WT, D2.63 A,

K373A, D2.63176A-K373A, and D2.63176K-K373D were 17 (5.3-53) nM, 4.9 (0.6-43) nM, 17 (3.3-85) nM, 5.1 (0.63-41.5) nM, and 15 (3.0-69) nM, respectively. Analysis of

S1,39A revealed a Ki (CI) value of 4.4nM (0.7-27).

Agonist Stimulated GTPγS Binding. [35S]GTPγS binding was used to measure the stimulation of WT and mutant cannabinoid receptors upon stimulation with different classes of cannabinoid ligands (See Tables 2.3, 2.4, and Fig. 2.2, 2.3). EC50 and Emax values were generated for WT and mutant receptor activation in the presence of CP55-

940 and WIN55,212-2. The EC50 values of CP55-940 and WIN55,212-2 at WT CB1 were 12.6 nM and 36.7 nM, respectively. The D2.63176A mutation significantly increased EC50 values for CP55-940 and WIN55-212-2 to 67 nM (5.3 fold) and 231 nM (

TABLE 2.1. RADIOLIGAND BINDING PROPERTIES OF WILD-TYPE AND MUTANT CELL LINES. The Kd and Bmax values were determined from saturation binding experiments using [3H]SR141716A on HEK 293 cell membrane preparations stably transfected with the wild-type or mutant hCB1 receptor. Data represent the mean and corresponding standard error of the mean (SEM) of at least three independent experiments performed in triplicate. No significant difference was observed between the wild-type and mutant binding properties as determined by a two-tailed Student's t test.

TABLE 2.2. THE EFFECTS OF AMINO ACID MUTATIONS OF RECOMBINANT HCB1 RECEPTORS ON THE DISPLACEMENT OF [3H]SR141716A BY CP55,940. Data represent the mean and corresponding 95% confidence limits of at least three independent experiments performed in triplicate. The Ki value of CP55,940 at the mutant receptors was not significantly different from wild-type CB1 receptors using a two-tailed Student's t test.

6.3 fold), respectively, and maximum agonist responsiveness was lower. The K373A mutation resulted in similar effects on the EC50 and Emax values. The K373A mutant generated a significant increase in EC50 values from WT for CP55-940 and WIN55-212-2 to 70nM (5.6 fold) and 274nM (7.5 fold), respectively. However, when the ionic interaction between D2.63176 and K373 was disrupted by double alanine substitutions, receptor activity was severely reduced. The D2.63176A-K373A mutant resulted in

FIGURE 2.1. COMPETITIVE DISPLACEMENT OF [3H]SR141716A. CP55,940 was used as the displacing compound. [3H]SR141716A binding in membranes prepared from HEK293 cells stably transfected with wild-type, D2.63176A, K373A, 176 176 D2.63 A-K373A , D2.63 K-K373D, or S1.39A mutant CB1 receptors. Each data point represents mean ± S.E.M. of at least three independent experiments performed in triplicate.

TABLE 2.3. CONCENTRATION-EFFECT DATA FOR AGONIST STIMULATION OF [35S]GTPγS BINDING OF WILD-TYPE AND MUTANT RECEPTORS STABLY EXPRESSED IN HEK 293 CELLS. Data represent the mean of at least three independent experiments performed in triplicate. The values in parentheses are the 95% CIs. Statistical analysis was performed using a two-tailed Student's t test to determine the level of significance.*=P< 0.05.

FIGURE 2.2. GTP γS STIMULATION WT AND MUTANT RECEPTORS. CONCENTRATION-EFFECT CURVES OBTAINED FROM [35S]GTPγS BINDING IN HEK293 MEMBRANE PREPARATIONS EXPRESSING WILD- TYPE OR D2.63176A, K373A, OR D2.63176A-K373A, D2.63176K-K373D MUTANT CB1 RECEPTORS. A) is the concentration-effect curve for WIN55,212. B) is the concentration-effect curve for CP 55,940. C) is the concentration-effect curve for JWH-018. D) is the concentration-effect curve for AM4056. Each data point represents mean ± S.E.M. of at least three independent experiments performed in triplicate.

FIGURE 2.3. CONCENTRATION RESPONSE FOR GTPΓS STIMULATION OF WT, S1.39A, AND K3.28A MUTANT RECEPTORS. Concentration-effect curves obtained from [35S]GTPγS binding in HEK293 membrane preparations expressing A) S1.39A or B) K3.28A mutant or C) WT CB1 receptors. Each data point represents mean ± S.E.M. of at least three independent experiments performed in triplicate.

TABLE 2.4. CONCENTRATION-EFFECT DATA FOR AGONIST STIMULATION OF [35S]GTPγS BINDING OF THE K3.28A AND S1.39A MUTANT RECEPTORS STABLY EXPRESSED IN HEK 293 CELLS. Data represent the mean of at least three independent experiments performed in triplicate. The values in parentheses are the 95% CIs. Statistical analysis was performed using a two-tailed Student's t test to determine the level of significance.*=P< 0.05.

68 dramatic shifts of either or both the EC50 and Emax values and for CP55-940 and WIN55-

212-2 to 39.8 nM (Emax 29%) and 561 nM (Emax 59%), respectively. The largest shift observed was from WIN55,212-2, 15.3 fold above WT value. In contrast, the charge

176 reversal mutant, D2.63 K-K373D, displayed an EC50 and Emax for WIN55-212-2 of 126

176 nM and 79%, respectively. Likewise, the D2.63 K-K373D mutant EC50 and Emax values for CP55-940 were 38 nM and 82%, respectively.

Modeling Studies

Modeller Results: Extracellular Loop Conformations in the WT CB1 R* and the

D2.63176A, K373A, D2.63176A-K373A, and D2.63176K-K373D Mutants. As described in Methods, low energy WT and mutant loop conformations were added to our previous

CB1 R* bundle (Kapur et al., 2007). Consistent with the experimental results, the WT model includes an ionic interaction between D2.63176 and EC-3 loop residue K373 (see

Fig.2.5). This ionic interaction causes the EC-3 loop to pull across the top (extracellular side) of the receptor. Clearly, this specific ionic interaction cannot form in the

D2.63176A, K373A, or the D2.63176A-K373A mutant. By not forming this ionic interaction, the EC-3 loops of the mutant receptors experience greater conformational freedom. As illustrated in Figure 2.5, the modeled loop conformations of D2.63176A,

K373A, and D2.63176A-K373A position the EC-3 loop away from the center and are more directly above TMHs 6 and 7. It is noteworthy that these three mutants have very similar EC-3 loop conformations and that these conformations are fundamentally different from the WT EC-3 loop conformation.

Unlike the D2.63176A, K373A, or the D2.63176A-K373A mutant, the D2.63176K-

K373D swap mutant can form the putative ionic interaction. In agreement with the experimental results, the model of this mutant includes an ionic interaction between

D2.63176K and K373D (see Fig. 2.5). This ionic interaction causes the EC-3 loop to pull across the top (extracellular side) of the receptor. As observed in Fig. 2.5, the WT and the

D2.63176K-K373D EC loops have a remarkable degree of conformational similarity in their EC loops. The formation of the putative ionic interaction (despite having switched the residues at 2.63176 and 373) explains how the D2.63176K-K373D swap mutant is capable of promoting an EC-3 loop conformation that is very similar to the WT EC-3 loop conformation. In addition, the negatively charged K373D may be able to form ionic interactions with K370 and K7.32376 (see Fig. 1.2). These interactions may reduce the frequency of the D2.63176K-K373D ionic interaction. Energetically favorable interactions with K370 and K7.32376 is highly unlikely for K373 (in WT), as its positive charge would be repelled by the positive charge on K370 and K7.32376.

CP55,940/Receptor Pairwise and Total Interaction Energies. The results of the saturation and competitive binding assays demonstrate that all mutations do not significantly affect the binding affinity of the ligands studied. Therefore, to test if our models agreed with these results, pairwise and total interaction energies were calculated for the WT and mutant models (the total interaction energies are listed in Table 2.5).

Quantitatively, Table 2.5 shows that none of the mutations resulted in significant change in the total interaction energy between CP55,940 and the receptor. These results indicate that our computational models are consistent with the results of the binding assays.

FIGURE 2.4. EXTRACELLULAR LOOP CONFORMATIONS OF WILD-TYPE (WT) 176 176 AND D2.63 A, K373A, OR D2.63 A-K373A MUTANT CB1 RECEPTORS IN THE ACTIVE (R*) STATE. CP55,940 is shown in green; D2.63176 and K373 are shown in orange; WT EC loops are shown in blue; D2.63176A, K373A, and D2.63176A-K373A mutant EC loops are shown in red, yellow, and purple, respectively. In the WT model, the putative ionic interaction between D2.63176 and K373 has formed; this promotes an EC-3 loop conformation that is pulled over the top of the receptor. In the alanine-substitution models, the putative interaction does not form and the EC-3 loops are away from the bundle core. A) Viewpoint is from extracellular with intracellular portions of TMHs, IC loops, and the N and C termini omitted to simplify view. B) Viewpoint is from lipid looking between TMH1 and 7. The intracellular portions of TMHs, IC loops, EC-1, EC-2, part of TMH1 and 7, and the N and C termini have been omitted here to simplify the view.

FIGURE 2.5. EXTRACELLULAR VIEWPOINT OF EC LOOP CONFORMATIONS 176 OF WT CB1 R* AND THE D2.63 K-K373D SWAP MUTANT. CP55,940 is shown in green; D2.63176 and K373 are shown in orange; WT EC loops are shown in blue; the D2.63176K-K373D swap mutant EC-3 loop is shown in red. (see Figure 4a legend for further details). A) In the WT model, the putative ionic interaction between D2.63176 and K373 has formed; this promotes an EC-3 loop conformation that is pulled over the top of the receptor. B) In the D2.63176K-K373D mutant model, the putative ionic interaction has been formed, promoting an EC-3 loop conformation that is very similar to WT.

TABLE 2.5. TOTAL INTERACTION ENERGY OF CP55,940 AT THE WILD- TYPE AND MUTANT CB1 R* MODELS.

Discussion

In the present study, we have reproduced one of the most important findings in the CB1 binding literature (Song and Bonner, 1996) mutated an important residue in the

1st transmembrane domain (S1.39A), and identified novel interacting residues with molecular modeling.

Selective Ligand Recognition and K3.28A

In chapter 1 we discussed K3.28 and its role in receptor activation and recognition of agonists. We confirmed earlier reports that this lysine residue is important for recognizing bicyclic, tricylic, but not the aminoalkyindole class of cannabinoids (Fig

2.3).

S1.39A: A Mutation for the Future

S1.39A may turn out to be another important point of interaction for selective ligand recognition and signal transduction; however it awaits characterization with molecular modeling techniques. Previous work has shown that another serine residue (S292) has an important role in the signal transduction of cannabinoid agonists, HU-210 and CP55940, but not in that of aminoalkylindoles derivatives WIN55,212-2 (Rhee, 2002).

Understanding the role of unique residues in the cannabinoid receptors may lead to treatments of diseases associated with mutations or polymorphisms of the ECS (See chapter 4 for discussion).

Novel Interacting Residues and Molecular Modeling

We have used computational methods together with model-guided mutagenesis to evaluate the functional importance of a putative intramolecular ionic interaction within the CB1 receptor. Our previous mutation studies demonstrated the importance of a negative charge at residue 2.63176, possibly indicating its involvement in an essential ionic interaction (Kapur et al., 2008). Our previous modeling studies indicated that the

EC-3 loop residue K373 might be the ionic partner to D2.63176. To test this hypothesis,

176 four alanine-substitution mutants CB1 receptors were constructed: D2.63 A, K373A,

D2.63176A-K373A, and D2.63176K-K373D to evaluate the effect of removing the putative ionic interaction. The charge reversal mutant was designed to determine if switching the positions of the ionic partners could rescue WT levels of function. Finally, computational methods were also used to explore how the putative ionic interaction influences receptor structure.

Ligand binding affinity was not significantly affected by any of the mutations performed here. These results are consistent with our prior characterization of D2.63176 which was shown to be crucial for signal transduction but did not participate in high affinity agonist binding (Kapur et al., 2008). In addition, the binding affinity data reported here is consistent with the predictions made from our WT and mutant models.

Specifically, CP55,940 was found to have a similar total interaction energy in the WT and mutant receptor models; this is not surprising, as neither D2.63176 nor the EC-3 loop are part of the predicted CP55940 binding pocket. Indeed, reports of extracellular loop mutations that only affect agonist efficacy (and not ligand binding) are well documented in the GPCR literature. Residues in EC-2 loop of the M3 muscarinic receptor could be mutated without affecting ligand binding; however, a significant reduction in agonist efficacy was observed (Scarselli et al., 2007). Similar results have been observed in the

EC-1 loop of the adenosine A2B receptor (Peeters et al., 2011a). Analogously, our results suggest that the ionic interaction between D2.63176 and K373 is not important for

SR141716A (Table 2.1) or CP55940 binding at the CB1 receptor. Additionally, none of

3 the mutations significantly affected the Bmax for [ H]SR141716A. These results suggest that the mutations reported here did not cause the receptor to fold incorrectly or fail to express at the cell surface.

In contrast to the binding affinity results, the D2.63176A, K373A, D2.63176A-

176 K373A or D2.63 K-K373D mutations caused a significant change in CP55940’s EC50

176 176 compared to WT. However, the EC50s of the D2.63 A, K373A, or the D2.63 K-

K373D mutants when compared to the D2.63176A-K373A mutant were not significantly different. This is consistent with our hypothesis that it is the ionic interaction between

75 the charged residues, D2.63176 and K373 (and not the residues independently) that is important to agonist efficacy. If D2.63176 and K373 were independently important to function, then one would expect that the EC50 of the double-alanine mutant would be higher than either of the single-alanine mutants.

A previous report demonstrated the presence of a negatively charged residue at position 2.63176 that is crucial for receptor function (Kapur et al., 2008). In this study, we demonstrate that an ionic interaction between D2.63176 and K373 (not simply the

176 negative charge on D2.63 per se) is required for CB1 WT function. Emax values for either CP,55940 or WIN55,212-2 at the double alanine mutant showed a significant decrease in function. This result suggests that the interaction between D2.63176 and K373 is important for signaling at CB1. This result is also reinforced by results for the charge reversal mutant, D2.63176K-K373D, as both CP55,940 and WIN55,212-2 showed a restoration of function compared to the double alanine mutation. Therefore, the ability to switch the residues at 2.63176 and 373 (dramatically flipping the polarity on both residues) and preserve near-WT levels of efficacy strongly supports the existence of a functionally- required ionic interaction between D2.63176 and K373.

The single alanine mutants showed increased Emax values relative to the double alanine mutant (Emax = 59% at D2.63A and Emax = 29% for CP55940; Emax = 89% at

D2.63A and Emax = 59% for WIN55212-2) that are larger than what might be expected for disruption of the same ionic interaction as seen in the double alanine mutant. Our models suggest that residues near the putative ionic interaction may help rescue function in these single-alanine mutants. There are two additional lysines (K370 and K7.32376, see

Fig. 1.2) that are in close proximity to K373. These lysines may be able to form an ionic

76 interaction with D2.63176, thus partially rescuing function at the K373A mutant.

Likewise, there is a negatively charged aspartate (D184) and two hydrophilic residues

(H181 and D185) on the EC-1 loop that are in close proximity to D2.63176. These residues may be able to form an ionic interaction (or a simple hydrogen bond in the case of H181 and S185) that enables the partial rescue of function at the D2.63176A mutant. In the double mutant, D2.63176A-K373A, no such rescue would be possible because the polar residues at each site (D2.63 or K373) have been replaced with a non-polar residue

(Ala).

Involvement of Extracellular Loops in GPCR Activation. Results reported here suggest that the formation of an ionic interaction/salt bridge between the EC-3 loop and the extracellular end of TMH2 is crucial to CB1 signaling. The hallmark of Class A

GPCR activation by an agonist is the “tripping” of the toggle switch within the binding pocket that allows TMH6 to flex in the CWXP hinge region and straighten. This straightening breaks the “ionic lock” between R3.50 and E/D6.30 at the intracellular end of the receptor. The result is the formation of an intracellular opening of the receptor, exposing residues that can interact with the C-terminus of the Gα subunit of the G protein

(Hamm et al., 1988). There is increasing evidence that movements in the extracellular loops also occur subsequent to agonist binding and are integral to transmission of the activation “message” (or covalent ligand isomerization in the case of rhodopsin). NMR studies of rhodopsin activation by light have indicated that activation triggers a simultaneous displacement of the EC-2 loop and TMH5. Motion of EC-2 may allow the extracellular end of the TMH6-EC-3-TMH7 segment to pivot toward the center of the protein and conversely allow the intracellular end of TMH6 to rotate outward (Ahuja et

77 al., 2009). In some Class A GPCRs, such as CXCR4, a specific interaction between the

EC-3 loop and N-terminus (disulfide bridge) acts as a “microswitch” that is crucial to the

CXCR4 signaling (Rana and Baranski, 2010).

The computational results reported here illustrate how the ionic interaction between D2.63176 and K373 causes the EC-3 loop to pull across the top (extracellular side) of the receptor. Notably, this EC-3 loop conformation is preserved in the charge reversal mutant, D2.63176K-K373D mutant. As described in Results, a strikingly different EC-3 loop conformation is observed in the three alanine-substitution mutants.

These results suggest that the putative ionic interaction strongly influences the conformation of the EC-3 loop. This promoted EC-3 loop conformation could serve two important structural roles. First, this EC-3 loop conformation may contribute to forming a protected, closed extracellular surface as has been reported in the crystal structures of rhodopsin (Li et al., 2004) and the sphingosine 1-phosphate receptor (Hanson et al.,

2012). Second, this ionic interaction creates a noncovalent ‘tether’ between the extracellular ends of TMHs 2, 6 and 7 allowing conformational changes that occur on one side of the receptor to be transmitted to the other side of the receptor. Thus, the alanine- substitution mutants are less capable of transmitting conformational changes throughout the receptor and efficacy is consequently impaired. In conclusion, we have identified the

EC-3 loop conformation that is mechanistically important in the signaling cascade in

CB1.

CHAPTER 3 THE ANABOLIC ROLE OF CANNABINOID RECEPTORS IN BONE: TARGETING CANNABINOID RECEPTORS IN OSTEOBLASTS.

Introduction

We hypothesize that the endocannabinoid system (ECS) plays a role in bone health. The ablation of cannabinoid receptors has been shown to disrupt normal bone development (See chapter 1, Fig 1.4). Previous research suggests the presence of cannabinoid receptors in mesenchymal stem cells, osteoclasts, and osteoblasts. The activation/antagonism of these receptors may also affect levels of pERK, and other signaling molecules in these cells. Our preliminary data demonstrates differences in cell proliferation between mice the Wild-Type (WT) and CB1/2 KO primary osteoblasts isolated from calvaria of neonatal mice and in primary cells isolated from rats. Further analysis of WT and CB1/2 KO bones by µCT provide novel data on the distal femur for phenotype characterization.

In MC3T3-E1 osteoblastic cells, the CB1 antagonist, AM251, has been reported to induce increases in Runx2 mRNA, mineralized bone nodule formation, and activation of signaling molecules such as ERK and AKT (Wu et al. Bone 49 (2011) 1255-63).

Studies from our lab characterizing mice in which both CB1 and CB2 receptors were inactivated by homologous recombination have demonstrated increased bone mass coupled with enhanced osteoblast differentiation of bone marrow stromal cells in culture

(manuscript in preparation). We explored the effect of antagonizing CB1 and CB2 cannabinoid receptors in osteoblastic cells to gain insights into molecular pathways that may help to explain the effects of the ECS in bone development. Experiments in this

79 chapter will test the effects of CB1 and CB2 antagonists on the pre-osteoblast cell line

MC3T3-E1, with a strong focus on the potential signaling pathways underlying the observed phenotype in the CB1/CB2 KO mouse model.

Materials and Methods

Osteoblast Isolation and Culture

Primary immature osteoblasts were isolated from the calvaria (parietal bones) of 3-5 day old animals by sequential collagenase digestions as previously described (Arnott et al.,

2007). Prior to experiments, the cells were cultured in a 75cm2 flasks in standard α-

MEM media. The cells were left to adhere and proliferate until the flask was nearly confluent before using in experiments.

Proliferation Assays with Primary Osteoblasts

Primary cells from rats isolated from the parietal bones of neonates were plated at 2,000 cells/well in MEM with 10% FBS. After 24 hours the cells were washed with plain media, and the media was replaced with MEM with 1%FBS and cells were treated with

1,3,5,7 and 10 µM of SR141716A, SR144528, or a combination of the two compounds.

Cells culture was stopped at 48 hours post treatment. Cell proliferation was measured using a WST-1 proliferation kit from Caymen (Cat# 10008883).

Primary cells isolated from parietal bones of WT and CB1/CB2 KO mice were plated at

2,000 cells/well in 96 well plates. After 2 weeks cells numbers were measured using a

CyQuant kit from Invitrogen (Cat#C35006). A calibration curve was also generated with

WT and CB1/2 KO primary cells to determine cells numbers.

Western Analysis for Determination of Protein Activity

MC3T3-E1 cells were grown to confluence in 100-mm plates with minimal essential medium supplemented with 10% FBS. Drug treatment of the cells consisted of time courses with 1µM of either SR141716A or SR144528, or in combination. Cells were then lysed and centrifuged at 16,000xg for 1 min at 4 °C. Supernatants, corresponding to the cytosolic fraction, were collected, and protein concentrations were determined by the Bradford assay (Bio-Rad). Cytosolic fractions (30 µg) were separated on a 10% gel by SDS-PAGE followed by immunoblotting. Antibodies against phosphorylated ERK1/2 (1:5000), SMAD158 (1:1000), SMAD5(1:1000), and AKT

(1:1000) were detected. A monoclonal anti-body against GAPDH (1:5000) was used to confirm equal protein loading. Odyssey Infrared Imaging System and software (LI-COR,

NE, USA) was utilized to detect and quantify the antibody-specific bands using IRdye

800CW or IRDye 680-conjugated secondary antibodies. The data was normalized to control (T=0 minutes) and reported as fold increases above T=0.

Time course experiments

MC3T3 cells were seeded into 100mm dishes at 200,000 cells/dish in MEM with

10%FBS and grown to confluence. The cells were transferred to 1%FBS at least 24 hours prior to experimentation. Cells were washed with HBSS before receiving 1 µM of a cannabinoid (dissolved in DMSO) in HBSS. Cells were harvested at various times using

81 a protease (Thermo Sci Cat#78425) and phosphatase (Thermo Sci Cat#78420) inhibitor cocktail.

Statistics

Analyses were carried out using Graphpad Prism Software (San Diego, CA). Multiple comparisons in the case of multiple time and/or treatment groups were assessed by using analysis of variance (ANOVA). When significant differences were indicated by

ANOVA, group means were compared using the Bonferoni posthoc method for comparisons.

Results

Primary Osteoblasts Show Decreased Proliferation. Treatment of primary osteoblasts isolated from the calvarias of neonatal rat pups with 10µM SR141716A or a combination of SR141716A and SR144528, resulted in a significant decrease in primary osteoblast proliferation (Fig. 3.1A,C). However, targeting the CB2 receptor with SR144528 did not result in a significant decrease in proliferation at any of the applied doses (Fig. 3.1B). In

Figure 3.1D, primary osteoblasts isolated from WT and CB1/2 KO mice demonstrated a significant decrease in proliferation after 14 days.

High Bone Mass Phenotype for CB1/2 KO Female Mice. In vivo the female CB1/2 KO mice showed an increase in bone mass at 8 weeks, and the osteoblasts isolated from these animals have increased ALP activity in vitro (Data not shown). Taken together, Fig 3.1 and 3.2, suggest that a characteristic of CB1/2 KO osteoblasts is that these cells proliferate at a lower rate, may have increased ALP activity, which could account for the high bone mass phenotype observed.

FIGURE 3.1. TARGETING CANNABINOID RECEPTORS DECREASES PROLIFERATION IN PRIMARY RAT OSTEOBLASTS. A) Primary osteoblasts treated with SR11716A. B) Primary osteoblastas treated SR144528. C) Primary ostesoblasts treated with SR141716 and SR144528. D) Primary osteoblasts from CB1/2 KO and WT mice assayed for proliferation after 14 days. Bars represent means ± SEM of at least 3 separate experiments; *P < 0.05.

FIGURE 3.2. TRABECULAR BONE VOLUME OF WT AND CB1/2 KO MICE ACROSS 52 WEEKS.

MC3T3-E1 cells treated with either SR141716A or SR144528 alone or in

combination, assayed for pERK. Within 15 minutes, treatment with 1 µM SR141716A,

SR144528, or 1 µM of each in combination resulted in several fold increases in pERK

activity (Fig 3.3). SR141716A demonstrated a trend towards increased, sustained pERK

activity, but did not reach significance until 60 minutes (Fig 3.3; ANOVA (7, 18) F=3.25,

P<0.05). Targeting the CB2 receptor with SR144528 resulted in a rapid, significant

increase in pERK activity at 5, 10, and 15 minutes, but the activity quickly dropped off to

84 near basal levels (Fig 3.3B; ANOVA (7, 16) F=10.21, P<0.01). However, targeting both

CB1 and CB2 receptors resulted in the highest amount of pERK activity at 15 minutes, as well as a significant elevation of ERK activity between 10 and 30 minutes (Fig 3.3C;

ANOVA (7, 16) F=25.39, P<0.01 and P<0.05). Targeting cannabinoid receptors may cause differential increases in ERK1 (p42) and ERK2 (p44) activity. There is a trend towards increased p44 activity in each treatment group but it is not significantly different from p42 activity (Fig 3.4).

MC3T3-E1 cells treated with either SR141716A or SR144528 or in combination, assayed for pSMAD158. Targeting a single cannabinoid receptor with either SR141716 or SR144528 leads to alterations in pSMAD158 activity; however these changes are not significant (Fig 3.5A-C). When both cannabinoid receptors are targeted with both

SR141716A and SR144528 in combination, pSMAD158 activity becomes significant at

15 and 30 minutes (Fig 3.5D; ANOVA (7, 16) F=3.03, P<0.05).

MC3T3-E1 cells treated with either SR141716A or SR144528 or in combination, and assayed for pAKT activity. Targeting cannabinoid receptors with either drug alone or in combination did not lead to significant changes in pAKT activity (Fig 3.6). There was a trend towards increased pAKT activity in the SR141716A timecourse experiments but this effect was diminished when SR144528 was co-applied.

FIGURE 3.3. MC3T3-E1 CELLS TREATED WITH SR141716A, SR144528, AND IN COMBINATION, ASSAYED FOR PERK. A) Representative images from western blot analysis. B) Graph of SR141716A induced ERK activity. C) Graph of SR144528 induced ERK activity. D) Graph of SR141716A and SR144528 combination induced ERK activity. Bars represent means ± SEM of 3 separate experiments; *P < 0.05 and **P < 0.01.

FIGURE 3.4. TARGETING CANNABINOID RECEPTORS MAY CAUSE DIFFERENTIAL INCREASES IN ERK1 (P42) AND ERK2 (P44) ACTIVITY. A) Quantification of SR141716A p42 and p44 activity. B) Quantification of SR144528 p42 and p44 activity. C) Quantification of SR141716 and SR144528 p42 and p44 activity. The levels of p42 and p44 were not significantly different from each other at any time point.

FIGURE 3.5. MC3T3-E1 CELLS TREATED WITH SR141716A, SR144528, AND IN COMBINATION, ASSAYED FOR PSMAD158 ACTIVITY. A) Representative images from western blot analysis. B) Graph of SR141716A for induced SMAD158 phosphorylation. C) Graph of SR144528 for induced SMAD158 phosphorylation. D) Graph of SR141716A and SR144528 combination for SMAD158 phosphorylation. Bars represent means ± SEM of at least 3 separate experiments; *P < 0.05.

FIGURE 3.6. MC3T3-E1 CELLS TREATED WITH SR141716A, SR144528, AND IN COMBINATION, ASSAYED FOR PAKT ACTIVITY. A) Representative images from western blot analysis. B) Graph of SR141716A 4528 induced pAKT activity. C) Graph of SR144528 induced pAKT phosphorylation. D) Graph of SR141716A and SR144528 induced pAKT phosphorylation. Bars represent means ± SEM of 3 separate experiments.

Discussion

The trabecular bone volume of female CB1/2 KO mice is increased compared to

WT, yet the osteoblasts of these animals proliferate at a significantly lower rate (Fig 3.1).

Perhaps an increase of ALP activity in CB1/2 KO osteoblasts could help to explain how these cells are resulting in a high bone mass phenotype. The activity of signaling molecules such as pERK, pSMAD158, and pAKT may provide mechanistic insight to characterize the nature of CB1/2 KO osteoblasts

SR141716A stimulated pERK, pSMAD158, and pAKT activity. pERK activity increased steadily after T=0, peaking at 60 minutes (>3 fold increase). pSMAD158 activity increased about 2 fold at 10 minutes, diminishing gradually until 60 minutes, and increasing again at 120 minutes however the values did not reach significance. pAKT appeared to display cyclical activity (Fig 3.6B). SR144528 stimulated pERK, pSMAD158, but not pAKT activity. SR144528 treatment resulted in rapid, significant increases in pERK at 5, 10 and 15 minutes (Fig 3.3C). However, the effects of SR144528 on pSMAD158 and pAKT did not reach significance.

Cannabinoid receptor antagonists can significantly alter the activity of the

SMAD158 complex. This suggests that cannabinoids can influence bone morphogenic signaling pathways, and therefore play a significant role in osteoblast differentiation and function (Chen et al., 2004). Our results suggest dynamic signaling events occur during

CB1 and CB2 receptor antagonism, which can significantly alter the activity of ERK and

SMADs, and potentially affecting Runx2 expression (See Fig 1.3). This potential role for

SMADs and cannabinoids in bone is a novel finding, and future experiments should be

90 conducted to confirm this mechanism. These experiments include using MAPK inhibitors to affect pSMAD158 activity or cell proliferation, and RT-PCR analysis could provide reliable data on the levels of Runx2 in these osteoblasts. These types of experiments would help to corroborate the observed pSMAD158 activity that is associated with a high bone mass phenotype in these animals. The effect of CB1 and

CB2 antagonism in osteoblastic cells may be distinct from that of a neuron or another cell type within the body, due to differences in receptor expression, ligand production, G- protein coupling, and the role of the ECS within a specific environment.

CHAPTER 4

SUMMARY

Specific Aim 1 Epilogue

In chapter 2, specific aim 1 is addressed through the characterization of a novel interaction between D2.63 and K373. This work was completed by analyzing mutant cannabinoid receptors from established cell lines, which were used for binding experiments. Additionally a key residue in the CB1 receptor was explored for its selective ligand binding properties. The Lysine3.28 (K3.28A) alanine mutation showed that CP55,940 and AM4056 cannot maintain proper CB1 stimulation, while WIN55,212 and JWH-018 activity is not significantly different from WT receptor stimulation.

Aminoalklyindoles such as WIN55,212 appear to require different residues for receptor activation than the bicyclic, endogenous fatty acid amides, and classical cannabinoids.

Mutational analysis of the cannabinoid receptor will contribute to the base of knowledge of a molecular model of the CB1 receptor, allowing the design of potentially useful therapeutic drugs. One tantalizing possibility, on the forefront of pharmacogenomics research, is to create compounds that may activate cannabinoid receptors when there is a loss of endogenous ligand activity or recognition due to a mutation in genes encoding the cannabinoid receptors. Hypothetically, a patient could possess a polymorphism or acquire a mutation that hinders efficient interactions at cannabinoid receptors by endocannabinoids. In this scenario, a drug is chosen based on the patient’s genotype. A different class of cannabinoids may be able to replace the endogenous compounds or increase the efficiency of receptor-ligand interactions. This

92 type of personalized approach would require either selecting a compound that has structurally distinct binding requirements from endogenous compounds (i.e., an indole such as WIN55212) or a compound that will enhance endocannabinoid activity at the target. A ‘clinical endocannabinoid deficiency syndrome’ resulting from defects in the

ECS (i.e., receptor mutations, alterations in endocannabinoid production), has already been proposed to underlie certain diseases including treatment resistant conditions, and cannabinoid receptor polymorphisms are associated with several diseases (See Table 1.1)

(Russo, 2008). To date, a mutation is yet to be identified in the human cannabinoid receptor that results in conclusive alteration of ligand-receptor interactions. The efficacy of future cannabis-based clinical trials could be enhanced by developing patient screening methods for polymorphisms or mutations in genes associated with the endocannabinoid system.

Specific Aim 2 Epilogue

Significant advances towards understanding the mechanisms of cannabinoid receptor signaling in bone development and disease have been made, but much remains to be defined. Recent studies on mice in which both cannabinoid receptors (CB1 and

CB2) have been inactivated (CB1/2 KO mice) demonstrate that cannabinoid receptors are important for healthy skeletal development (See Chapter 1 and 3). Endogenous cannabinoids are abundantly expressed in hematopoietic stem cell niches, where stromal and mature bone cells are located. The cannabinoid receptors appear to regulate osteoclast activity and bone resorption. Yet, little was known about how cannabinoid signaling can regulate osteoblasts. In chapter 3, specific aim 2 was addressed by

93 investigating and proposing a molecular mechanism for the bone phenotype of CB1/2 KO mice, which involved significant increases in pSMAD158 and pERK, but not AKT in vitro.

Genetic mutations in cannabinoid receptors and altered endogenous ligand production may underlie osteoporosis. In fact, investigations of cannabinoid receptor polymorphisms in geographically distinct human populations reveal a correlation between CB2 receptor polymorphisms and osteoporosis. However a significant association between the effects of cannabinoid type 1 (CB1) receptor polymorphisms and bone health is unclear. In animal studies, the ablation of the CB1 receptor results in a poor bone phenotype. Despite this finding, definitive molecular underpinnings of CB1 receptor in bone were not uncovered. Future studies on cannabioid receptors and bone need to examine the influence of pSMAD158 and pERK on Runx2 activity. The emerging human data, animal models, and basic research suggest that cannabinoid receptors may represent a reasonable target for maintaining bone health or in the treatment of bone diseases.

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