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Identification and in vivo Characterization of a Potential TAAR1 Antagonist

by

Vincent Ming Yin Lam

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of & Toxicology University of Toronto

© Copyright by Vincent Ming Yin Lam 2017

Identification and in vivo Characterization of a Potential TAAR1 Antagonist

Vincent Ming Yin Lam

Doctor of Philosophy

Department of Pharmacology & Toxicology University of Toronto

2017 Abstract

TAAR1 is a G- coupled expressed in regions in the and represents a potential novel therapeutic target for the treatment of neurological disorders. While success has been made with discovering novel selective for TAAR1, only one TAAR1 antagonist has been described thus far. We used an in silico screen on a TAAR1 model and identified several novel agonists and potential antagonists for TAAR1. One of the identified antagonists (compound 22) was predicted to have favourable physicochemical properties that should allow it to cross the blood brain barrier. In vivo studies were therefore carried out and showed that compound 22 potentiates - and -mediated locomotor activity, consistent with behaviours observed in Taar1-KO animals. In order to assess whether the effects of compound 22 are mediated through antagonism of TAAR1, experiments were carried out on Taar1-KO mice. Our results show that compound is also able to enhance amphetamine- and cocaine-mediated locomotor activity in Taar1-KO mice, suggesting that the in vivo effects of compound 22 are not mediated by TAAR1. In collaboration with Screening Program at UNC-Chapel Hill, we attempted to determine the target for compound 22. PDSP results suggested several potential targets for compound 22. These include, the , and transporters; as well as sigma 1 and 2 receptors. Furthermore, the dopamine D2 receptor was also an initial hit in a functional assay performed by PDSP. Our follow-up studies using heterologous systems showed that neither DAT nor dopamine D2 dopamine receptors are targets of compound 22. Therefore, the of compound 22 mediating its psychoactive effects remain unknown.

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Acknowledgments

First and most importantly, I would like to thank my supervisor Dr. Ali Salahpour for his guidance throughout my graduate career in both my MSc and PhD degrees. His endless optimism, enthusiasm, and patience guided the research that is presented in this thesis. Furthermore, I would like to thank Dr. Amy Ramsey for her intellectual and financial support. I would also like to thank my supervisory committee members Dr. Nobrega, Dr. Matthews, and my co-supervisor Dr. Ross for their insight and support of me and my project. I would like to specifically acknowledge the work Dr. Matthews did as the reader for this thesis on such short notice, where I will forever be eternally grateful for your assistance.

Within the lab I would like to thank our lab manager Wendy Horsfall for her expertise in molecular biology, in vivo experiments, and general scientific knowledge. Without Wendy, I do not believe my project would have progressed as far as it did. In addition, I would like to thank the recently graduated Dr. Pieter Beerepoot and Dr. Catharine Mielnik; dear friends whom I have spent the last 10 years in class and the lab. Specifically, I will miss working with Pieter where his crazy ideas and passion helped me throughout my undergraduate and graduate studies. In addition, I would also like to extend my sincerest thanks to Kasia for being a fantastic friend and an excellent scientist. While our projects rarely overlapped, I could only look up in awe at the organization and rigor that defines her as a scientist. Without her help and guidance, I do not believe I would have finished my thesis in time, one day I hope to repay the favour. In addition, I would like to thank all former and current lab members of the Ramsey Salahpour lab. Specifically, I would to thank the following members for their help and tolerating the organized chaos that has become my work space: Marija Milenkovic, Kristel Bermejo, Shababa Masoud, Laura Vecchio, Sonny Chen, and Rehnuma Islam. I would also like to thank the undergraduate students I had the fortunate opportunity to mentor: Eun Jee Koh, Thomas Zhang, and Negin Sadeghlo.

Lastly, I would like to thank my family and friends for their support throughout the years. Specifically I would like to mention my father, whose battle with cancer over the past decade has been an inspiration to me. Seeing the strength and positivity he has use to tackle the disease is truly remarkable and something I hope to emulate. To my friends outside of the lab, while I cannot list all of your names, your presence in my life has surely kept at least some of the marbles in the jar.

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Table of Contents

Acknowledgments...... iii Table of Contents ...... iv List of Tables ...... vii List of Figures ...... viii List of Appendices ...... x List of Abbreviations ...... xi 1 Introduction ...... 1 1.1 G-Protein Coupled Receptors ...... 1 1.1.1 GPCR Classification ...... 1 1.1.2 GPCR Signalling ...... 2 1.1.3 GPCR Desensitization and Internalization ...... 4 1.1.4 Structure and Function ...... 6 1.1.5 GPCR Oligomerization ...... 7 1.1.6 GPCR Trafficking ...... 7 1.1.7 GPCR ...... 10 1.2 Trace Associated Receptor 1...... 12 1.2.1 Trace ...... 12 1.2.2 Synthesis and of Trace Amines ...... 14 1.2.3 Dietary Effects of Trace Amines ...... 17 1.2.4 Properties of Trace Amines within the ...... 17 1.2.5 Clinical Effects of Trace Amines ...... 18 1.2.6 Associated Receptor (TAAR) Family ...... 19 1.2.7 Anatomical Expression of TAAR1 ...... 19 1.2.8 TAAR1 Ligands ...... 21 1.2.9 Cellular Localization of TAAR1 ...... 26 1.2.10 Cellular Signalling ...... 28 1.2.11 TAAR1 Mutant Mice ...... 30 1.2.12 TAAR1 and Disease ...... 35 1.3 Drug Discovery ...... 38 1.3.1 Computational Screens of GPCRs ...... 39 1.3.2 Generation and Optimization of a GPCR Model ...... 40 1.3.3 Hypothesis...... 42 1.3.4 Rationale for Hypothesis...... 43 2 Methods ...... 45 2.1 Generation of the TAAR1 Homology Model and Molecular Docking ...... 45 2.1.1 2D Molecular Similarity Calculations ...... 46 2.2 Reagents, Cells, and Drugs ...... 46 2.3 Plasmids ...... 47 2.3.1 β2TAAR1 ...... 47 2.3.2 BRET EPAC cAMP Biosensor ...... 47 2.3.3 Human HA-DAT ...... 47 2.4 Cell Culture and Transfections ...... 47 2.4.1 Cell Transfections ...... 47 2.5 BRET Assays ...... 48

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2.5.1 TAAR1 Signalling Assay ...... 48 2.5.2 Dopamine D2-β- Recruitment Assay ...... 48 2.5.3 BRET Assay Protocol ...... 48 2.6 Fluorescent Dopamine Uptake Assay ...... 49 2.7 Animal Studies ...... 49 2.7.1 Housing ...... 49 2.7.2 Generation of Experimental Mice ...... 50 2.7.3 Behavioural Experiments ...... 50 2.8 Statistical Analysis ...... 51 3 Results ...... 52 3.1 TAAR1 Homology Model and in silico Screen ...... 52 3.2 In vitro Evaluation of predicted ligands ...... 52 3.2.1 Characterization of Hits ...... 53 3.2.2 Characterization of Antagonist Hits...... 69 3.3 In vivo Characterization of Compound 22 ...... 73 3.3.1 Chemical Properties of Compound 9, 16, 22, and 24 ...... 73 3.4 In vivo Effects of Compound 22 ...... 73 3.4.1 Compound 22 Potentiates the Locomotor Stimulating Activities of Amphetamine and Cocaine in Wildtype C57BL/6J Mice ...... 76 3.5 Effects of Compound 22 in Taar1-KO mice ...... 81 3.5.1 Effects of Compound 22 on Amphetamine-Induced Locomotion in Taar1-KO mice ...... 81 3.5.2 Effect of Compound 22 on Cocaine-Induced Locomotion in Taar1-KO mice .....83 3.5.3 Effect of Compound 22 on Basal Locomotion in Taar1-KO mice ...... 85 3.5.4 Compound 22 Screens in Collaboration with PDSP...... 85 3.5.5 Compound 22 Interaction with the (DAT) ...... 87 4 Discussion ...... 90 4.1 Evaluation of the TAAR1 Homology Model...... 90 4.1.1 Molecular Docking of the TAAR1 Homology Model ...... 91 4.2 In vitro Evaluation of Predicted Ligands Yielded Novel Agonists and Potentially Low Potency Antagonists...... 92 4.3 Characterization of Agonist Hits ...... 92 4.3.1 Three Partial Agonists for TAAR1 were Discovered ...... 92 4.3.2 Characterization of Agonist Analogs ...... 94 4.3.3 The Discovery of Low Potency Antagonists for TAAR1 ...... 94 4.3.4 Chemical Properties of Compound 22 Allow for Access Across the Blood Brain Barrier ...... 95 4.4 Compound 22 Potentiates Amphetamine and Cocaine-Induced Locomotor Activity ...... 96 4.4.1 Compound 22 Potentiates Amphetamine Induced Locomotor Activity ...... 96 4.4.2 Compound 22 Potentiates Cocaine-Induced Locomotor Activity ...... 97 4.4.3 Compound 22 Alone Does Not Stimulate Locomotor Activity...... 97 4.5 Effects of Compound 22 in Taar1-KO mice ...... 98 4.5.1 Compound 22 Potentiates Amphetamine Locomotor Activity in Taar1-KO Mice ...... 98 4.5.2 Compound 22 Potentiates Cocaine Locomotor Activity in Taar1-KO mice ...... 99 4.5.3 Compound 22 Alone does not Stimulate Locomotor Activity in WT and Taar1-KO mice ...... 101 4.5.4 Conclusion of the in vivo Studies with Compound 22 ...... 101 v

4.6 PDSP Screen showed that Compound 22 Binds to Monoamine Transporters and Sigma Receptors ...... 102 4.6.1 PDSP Binding Studies and Results ...... 102 4.6.2 Functional GPCR Assay Showed Compound 22 does not Activate GPCRs...... 102 4.6.3 Compound 22 Does Not Effect Dopamine Uptake...... 105 4.6.4 PDSP Positive Hits and Their Ability to Effect Dopamine Signalling ...... 105 4.7 Negative PDSP Targets...... 112 4.7.1 Receptors ...... 112 4.7.2 Receptors ...... 113 4.8 Targets Not Tested by PDSP ...... 114 4.8.1 Receptors ...... 114 4.8.2 Glutamate Receptors ...... 115 4.9 Limitations and Future Directions ...... 117 4.9.1 Limitations ...... 118 4.9.2 Potential targets of Compound 22...... 118 4.9.3 Future Experiments ...... 119 4.10 Conclusion ...... 121 References ...... 122 Appendix ...... 161 Licenses and Copyright...... 177

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List of Tables

Results

Table 3.1 Chemical structures of the purchased compounds 1-42 55

Functional data for agonists discovered by the docking screen against the Table 3.2 59 TAAR1 homology model

Functional data for weak agonists discovered by the docking screen against Table 3.3 61 the TAAR1 homology model (EC50 > 100 μM).

Table 3.4 Functional data for five analogues of compound 8. 64

Table 3.5 Functional data for five analogues of compound 16 67

Potential antagonists discovered by the docking screen against the TAAR1 Table 3.6 71 homology model

Comparison of predicted physical properties of antagonist hits from the Table 3.7 74 PubChem database

Comparison of predicted physical properties of compound 22 against Table 3.8 75 known drugs that cross the blood brain barrier

Discussion

Table 4.1 PDSP Targets that were not tested 104

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List of Figures

Introduction

Figure 1.1 Metabolic pathway of trace amines and 15

Figure 1.2 Pathway for Trace Amine and Production 16

Figure 1.3 Known ligands for human TAAR1 24

Figure 1.4 The circuitry of the 34

Results

Figure 3.1 Binding poses of TAAR1 ligands in the orthosteric binding site 54

Identification of TAAR1 agonists and antagonists using a BRET Figure 3.2 57 EPAC cAMP biosensor

Dose response curves for the three most potent of the discovered Figure 3.3 58 agonists

Figure 3.4 Dose response curves for discovered agonists 60

Figure 3.5 Effect of discovered agonist on cells not expressing TAAR1 62

Figure 3.6 Dose response curves for analogues of compound 8 63

Dose response curves for analogues of compound 8 on cells not Figure 3.7 65 expressing TAAR1

Figure 3.8 Dose responses curves for analogues of compound 16 66

Dose response curves for analogues of compound 16 on cells not Figure 3.9 68 expressing TAAR1

Figure 3.10 Dose response curves for potential TAAR antagonists 70

Dose response curves for analogues of compound 16 on inhibiting Figure 3.11 72 TAAR1 signalling

Figure 3.12 in vivo studies with compound 22 co-injected with amphetamine 77

Figure 3.13 in vivo studies with compound 22 co-injected with cocaine 79

Figure 3.14 in vivo studies with compound 22 on basal locomotor activity 80

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in vivo studies with Taar1-KO mice co-injected with compound 22 and Figure 3.15 82 amphetamine

in vivo studies with Taar1-KO mice co-injected with compound 22 and Figure 3.16 84 cocaine

in vivo studies with Taar1-KO mice and compound 22 on basal Figure 3.17 86 locomotor activity

Dose response curves for β-arrestin recruitment to the dopamine D2 Figure 3.18 88 receptor using and compound 22

Dose response curves for cocaine and compound 22 effects on Figure 3.19 89 dopamine transporter uptake activity

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List of Appendices

Appendix A: Results

Supplemental Tables

Supplemental Compound 22 binding studies from PDSP: primary screen for compound 160 Table 1 22 and subsequent hits

Supplemental Compound 22 binding studies from PDSP: secondary screen for 161 Table 2 compound 22 and subsequent Ki values

Supplemental Figures

Supplemental Tango assay screen for compound 22 by PDSP 162 Figure 1

Supplemental Secondary screens compound 22 activation of the dopamine D2 163 Figure 2 receptor by PDSP

Appendix B: Discussion Dopamine Receptors ...... 165 Dopamine D1 and D2 ...... 165 Dopamine D3 ...... 166 Dopamine D4 ...... 166 Dopamine D5 ...... 167 Conclusion ...... 167 Serotonin Receptors ...... 168 5-HT1A ...... 168 5-HT1B ...... 168 Serotonin Receptor Conclusion ...... 169 Receptors ...... 169 α1A ...... 169 α2A and α2C ...... 170 β1 ...... 170 Conclusion ...... 171 Cholinergic Receptors ...... 171 M2, M3, and M5 Muscarinic Receptors ...... 171 Receptors ...... 172 Opioid Receptors ...... 173 Glutamate Receptors ...... 173 CB1 and CB2 Receptors ...... 174 x

List of Abbreviations

6-OHDA 6-OH-dopamine AADC aromatic L- decarboxylase ADHD deficit hyperactivity disorder β2AR β2 adrenergic receptor bPEA β-phenylethylamine CREB cAMP response element-binding protein CRLR receptor like receptor DAG diacylglycerol DAT dopamine transporter DAT-CI dopamine transporter knock-in DBH dopamine-β-hydroxylase DMEM Dulbecco’s Modified Eagle Serum DRN dorsal raphe nucleus DTG 1,3-di(o-tolyl)guanidine ERK extracellular signal-regulated kinases GABA γ-aminobutyric acid GAP GTP activating protein GIRK G-protein-activated inwardly rectifying potassium channels GPCR G-Protein coupled receptors GRK G-protein coupled receptor kinases IP3 inositol 1,4,5-triphosphate LC coeruleus LHR luteinizing receptors MAO monoamine oxidases MDMA 3,4-methylenedioxymethamphetamine mGluR metabotropic glutamate NAc NET norepinephrine transporter OCT organic channel PDSP Psychoactive Drug Screening program PKA cAMP-dependent PKC protein kinase C PLC C PNMT N-methyltransferase RAMP receptor activity modifying REEP receptor expression enhancing protein RGS regulator of G-protein signalling RTP receptor transporting proteins SERT xi

SN SNc substantia nigra pars compacta SNr substantia nigra pars reticula SSRI selective serotonin inhibitor TBPB 1-(1’-2-methylbenzyl)-1,4’-bipiperidin-4-yl)-1H benzo[d]imidazol-2(3H)- one T1AM 3-iodothyronamine Tc Tanimoto similarity coefficient TAAR1 trace amine associated receptor 1 tPSA topological polar surface area VMAT2 vesicular 2 VTA

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1 Introduction 1.1 G-Protein Coupled Receptors

With over 800 known members, G-Protein Coupled Receptors (GPCR) are the largest family of receptors in the human (Foord, 2002; Audet and Bouvier, 2012). These receptors are currently the target of approximately 40% of the prescribed drugs on the market (Wise et al., 2002). GPCRs play pivotal roles in a wide range of biological functions, that include but are not limited to: olfaction, cardiovascular function, and (Ferguson et al., 1998).

1.1.1 GPCR Classification

Although GPCRs share similar signalling mechanisms and receptor topology, there is very little shared among receptor types. Therefore, GPCRs have been divided into five or six (depending on classification criteria) major families of receptors based primarily on sequence similarity (Foord et al., 2005). The vast majority of GPCRs are classified into the three following classes: Class A (-like), B (-like), or C (metabotropic glutamate-like) (Foord et al., 2005).

Class A GPCRs (rhodopsin-like) comprise the largest family of GPCRs with roughly 700 found in the (Fredriksson et al., 2003). It is important to note that olfactory receptors make up the bulk of the class A family, consisting of over 65% of the receptors within this class. In general, class A GPCRs have their binding pocket located within the transmembrane domains (Venkatakrishnan et al., 2013). Some notable examples of class A

GPCR’s include: Rhodopsin, β2 adrenergic receptor (β2AR), and Trace Amine Associated Receptor 1 (TAAR1).

Class B GPCRs (secretin-like) are characterized by their large (~100 amino acid) cysteine rich N- terminal domain, responsible for ligand binding (Wheatley et al., 2012; Venkatakrishnan et al., 2013). In contrast to class A receptors, class B receptors bind as their endogenous ligands (Harmar, 2001). Notable examples of class B GPCR’s include: and parathyroid .

Class C receptors (metabotropic-glutamate like) are characterized by their large 500-600 amino acid N-terminal domains. The large N-terminal domain binds the ligand and consists of a two

1 2 lobed structures, termed the ‘venus fly trap’ domain (Bräuner-Osborne et al., 2007). However, the mechanism by which the binding of a ligand to the venus fly trap domain translates into GPCR signalling remains elusive (El Moustaine et al., 2012). In addition, a unique distinction for class C receptors is that all these receptors function as obligatory dimers (Bräuner-Osborne et al., 2007; El Moustaine et al., 2012). Notable family members of the Class C GPCRs include: metabotropic glutamate (mGluR) and metabotropic γ-aminobutyric acid (GABA) B receptors.

1.1.2 GPCR Signalling

Canonical signalling for GPCRs results from the receptor acting as a guanine nucleotide exchange factor for the intracellular heterotrimeric G-protein complex. When an extracellular ligand binds to the receptor, the receptor subsequently undergoes a conformational change that results in the activation of the heterotrimeric G-protein complex (Manning and Gilman, 1983). Although GPCR signalling through G-proteins has been well established as the canonical signalling pathway, over the last decade, extensive studies have shown that GPCRs can also signal in non-canonical pathways that are G-protein independent (see section 1.1.3.1.1).

1.1.2.1 G-Proteins

The heterotrimeric G-protein complex is composed of three subunits: the Gα GTPase, and the Gβγ dimer. The complex is associated as a heterotrimer when the Gα subunit is in its inactive GDP bound form. GPCR activation induces the exchange of GDP to GTP in the Gα subunit, causing the heterotrimer to dissociate into the Gα and Gβγ subunit components. Once disassociated, the Gα and Gβγ subunits interact with downstream effector proteins to generate, or release, further secondary messengers. The specific effector protein that is activated downstream depends on the family of G-protein subunits that are coupled to the receptor. There are 16 genes encoding for Gα subunits, yielding a total of 20 expressed Gα subunits. The Gα subunits can be separated into four families based upon sequence homology: Gαs, Gαi, Gαq, and Gα12. The Gαs family (Gαs and Gαolf) of G-proteins are stimulatory toward , causing an increase in intracellular cyclic (cAMP). Conversely, the Gαi family (Gαi1-3), Gαt (two isoforms, also known as transducin), Gαo, Gαz, and Gαgust are inhibitory to adenylyl cyclase, causing a decrease in intracellular cAMP. The Gαq family (Gαq, Gα11, Gα14, and Gα15) activates membrane bound (PLC), forming inositol 1,4,5-triphosphate (IP3) and diacylglycerol (DAG) from

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phosphatidylinositol. Lastly, the Gα12 family (Gα12 and Gα13) activates Rho-specific guanine nucleotide exchange factors (Tanabe et al., 2004; Luttrell, 2006).

In addition to the Gα subunits, the Gβγ heterodimer also has important functions in GPCR signalling. Currently, there are 5 known Gβ subunits, and 12 known Gγ subunits. Although there are almost 1000 possible combinations of Gβγ heterodimers, it is currently unknown whether all these combinations exist in vivo (see review by [Hildebrandt, 1997]). Nevertheless, there are common combinations of the Gβγ heterodimer expressed in specific tissues. For example, the Gβ1γ1 is the predominant heterodimer found associated with the Gαt in the retina (Ford et al., 1998).

Although it was not initially recognized, it is now generally accepted that Gβγ subunits can mediate as many functions as Gα subunits (Milligan and Kostenis, 2006) and activate effectors on their own, such as the PLC-β isoforms, ion channels, and G-protein coupled receptor kinases (GRK) (Ford et al., 1998).

1.1.2.2 Effector Proteins

Once the heterotrimeric G-protein complex has been disassociated into Gα and Gβγ subunits, downstream effector proteins, discussed below, are activated by the binding of G-protein subunits (Clapham and Neer, 1993).

1.1.2.2.1 Adenylyl Cyclase

Adenylyl cyclases are the downstream effectors for the Gαs and Gαi family of G-proteins. The family of adenylyl cyclases contains 10 members, all of which are 12 transmembrane proteins that convert intracellular ATP to the secondary messenger cAMP (Sunahara et al., 1996). In addition to Gα subunits, it has been shown that Gβγ subunits can also interact and activate adenylyl cyclase (Rebois et al., 2006; Wang and Burns, 2006; Boran et al., 2011). Once the adenylyl cyclase has been activated, the secondary messenger cAMP is produced from ATP hydrolysis, which in turn activates further downstream signalling cascades. Some important proteins that are directly activated by cAMP include, but not limited to, the cAMP-dependent protein kinases (PKA) and cAMP-regulated guanine nucleotide exchange factors (Zwartkruis and Bos, 1999).

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1.1.2.2.2 Phospholipase C β

The second major class of effector proteins is the family of membrane bound PLCβ (isoforms 1-

3). These proteins are activated by the Gαq family, as well as Gβγ subunits (Park et al., 1993). These lipases hydrolyze membrane bound phosphatidylinositol to yield the intracellular second 2+ messenger IP3, and the membrane bound DAG. The cytosolic IP3 regulates cytosolic Ca by binding to ligand gated calcium channels located in the endoplasmic reticulum. Meanwhile, DAG is the primary activator of several isoforms of the membrane bound protein kinase C (PKC) (Morris and Scarlata, 1997).

1.1.2.2.3 Ion Channels

Lastly, ion channels can be inhibited, or activated, by G-protein subunits. The main ion channels that are activated in are the family of G-protein-activated inwardly rectifying potassium Channels (GIRK), also known as the Kir3 channels (Kubo et al., 2005; Rebois et al., 2006). GIRK channels are comprised of a heterotetrametic assembly of different GIRK subunits (GIRK 1-4).

These channels are activated by the binding of Gβγ subunits originating from heterotrimeric Gαi complexes (Logothetis et al., 1987; Wickman et al., 1994). GIRK channels are important for mediating the slow inhibitory postsynaptic potential in neurons, and in general, are the main effectors of several pre- and post-synaptic GPCRs in the brain (see discussion Section 4.6-4.8). Other ion channels activated by G-protein subunits include, the ‘N-type’ calcium channels (inhibited by Gαo), and the ‘L-type’ calcium channels (activated by Gαs) (Wickman and Clapham, 1995).

1.1.3 GPCR Desensitization and Internalization

Regulation of GPCR signalling can occur at all stages of the signalling cascade (receptor, G- protein, or effector). Receptors can be phosphorylated and potentially internalized, G-proteins can bind to a regulator of G-protein signalling (RGS) or GTP activating protein (GAP) to modulate the rate of GTP hydrolysis, and/or the recycling or enzymatic degradation of secondary messengers. These will each be discussed in more detail in the sections below.

1.1.3.1 Receptor and Internalization

Activated GPCRs that have had the heterotrimeric G-protein complex dissociated undergo phosphorylation on specific and threonine residues in the third intracellular loop, and the C-

5 terminal domain of the receptor (Premont et al., 1995; Ferguson et al., 1996). This phosphorylation is mediated by the GRK. The mammalian family of GRKs consists of seven members. GRK2, 3, 5, and 6 are ubiquitously expressed, GRK1 and 7 are expressed selectively in the visual system, and GRK 4 is expressed in specific tissues such as, the proximal tubule cells of kidneys, testis, and brain (Premont et al., 1996; Sallese et al., 2000; Villar et al., 2009). Although phosphorylation is the first step of desensitization, it is not sufficient to completely uncouple the receptor from the G- protein. This was first reported with the discovery of GRK1, where it was observed that phosphorylated rhodopsin could still bind and signal through transducin (GαT) (McDowell and Kühn, 1977). In accordance, other non-visual GPCRs, such as the β2AR, also show impairment of G-protein signalling upon receptor phosphorylation (Benovic et al., 1985). Removal of the phosphorylation sites delays the desensitization of the receptor (Bouvier et al., 1988). Therefore, the role of GRKs is necessary to initiate desensitization and internalization of GPCRs, but it is not sufficient in mediating complete desensitization.

1.1.3.1.1 in GPCR Desensitization and Signalling

While phosphorylation triggers the process of desensitization, other proteins are necessary to complete the process. Phosphorylation of the receptor allows for the binding of arrestin proteins that mediate the complete desensitization of the receptor by blocking the association of the receptor with the heterotrimeric G-protein complex (Bennett and Sitaramayya, 1988; Lohse et al., 1990, 1992; Attramadal et al., 1992). Once bound, arrestins mediate GPCR endocytosis through a clathrin dependent pathway (Ferguson et al., 1996; Goodman et al., 1996).

Visual arrestin (i.e. arrestin 1) was the first arrestin discovered, and was found to mediate the complete decoupling of rhodopsin from transducin (GαT) (Bennett and Sitaramayya, 1988). Arrestin 2 and 3 were discovered based on their sequence homology with arrestin 1; these arrestins were discovered to bind and desensitize the agonist stimulated β2AR (Lohse et al., 1990). Arrestin 2 and 3 were originally named β-arrestin1 and β-arrestin2 respectively, and this nomenclature will be used in this thesis (Goodman et al., 1996). In total, four arrestin isoforms are expressed in (arrestin 1 -4), with arrestin 1 and 4 often named visual arrestins, because they are expressed in the visual system (Wilden et al., 1986; Craft et al., 1994). The key difference between the visual arrestins and β-arrestins lies in the C-terminal tail of the protein and therefore their interaction with clathrin. β-arrestins contain two motifs that link the GPCR to the clathrin

6 dependent endocytic machinery. β-arrestins bind with high affinity to clathrin in vitro through their C-terminal tail, while visual arrestins do not (Goodman et al., 1996).

In addition to arrestin’s role in desensitization and mediating endocytosis of GPCRs, it is now well established that internalized GPCRs can still signal through arrestin-mediated pathways in a G- protein independent manner. The receptor–arrestin signalling pathway has now been shown to activate a wide variety of proteins including kinases, small GTPases, guanine nucleotide exchange factors, E3 ubiqutin ligases, phosphodiesterases, and transcription factors (Reiter and Lefkowitz, 2006; Gesty-Palmer and Luttrell, 2008; Luttrell, 2008; Rajagopal et al., 2010). Furthermore, arrestin-mediated signalling has been shown to not mediate specific physiological effects such as the rewarding response of (Bohn et al., 1999, 2002, 2003). In accordance with these observations, it has been found that ligands can selectively signal through the G-protein dependent pathway or the arrestin pathway. This type of signalling is termed ‘’ or ‘biased signalling’ (Gesty-Palmer and Luttrell, 2008; Luttrell and Kenakin, 2011).

1.1.4 Structure and Function

GPCRs are seven-transmembrane integral proteins localized predominately at the plasma membrane. All GPCRs share the same general topography: plasma membrane spanning seven- transmembrane hydrophobic core, three intracellular loops, three extracellular loops, an extracellular N-terminal domain, and an intracellular C-terminal domain (Duvernay et al., 2005). Indeed this topography for GPCRs was confirmed with the crystallization of bovine rhodopsin (Palczewski et al., 2000). Inside the cell, the intracellular portion of the receptor binds to the heterotrimeric G-protein subunits, where these G-proteins mediate the canonical signalling for GPCRs (see section 1.1.2). Recent methodological breakthroughs in crystallization techniques have allowed for the detailed study of the tertiary structure of GPCRs, starting with rhodopsin and β2AR (Rasmussen et al., 2007). With the co-crystallization of the β2AR and Gαs, it was found that the structure existed in either an active or inactive state (Rasmussen et al., 2011a; Rasmussen et al., 2011b). In the activated state (agonist bound GPCR), the outward movement of the TM VI domain causes a 130° rotation of the Gα subunit. It was proposed that this rotation in the Gα subunit allows for the exchange of GDP to GTP, leading to G-protein mediated signalling Rasmussen et al., 2011b). While the traditional view of GPCRs involves one receptor coupled with

7 one set of G-proteins, many studies have also found these receptors can exist in an oligomeric state.

1.1.5 GPCR Oligomerization

While it is well established that many membrane bound non-GPCR receptors, like receptor kinases, exist and function as dimers (Heldin, 1995; Bain et al., 2007), GPCRs were often thought to exist in a monomeric state, with evidence showing that a GPCR monomer was often a functional receptor (Chabre and le Maire, 2005; Whorton et al., 2007, 2008). However, many biochemical and biophysical studies have shown GPCRs to also exist in a oligomeric state (Angers et al., 2000; Lavoie et al., 2002; Milligan, 2009; Ferre et al., 2014; Tena-Campos et al., 2014). It is now well accepted that class C GPCRs form constitutive homo- and hetero-dimers (Pin et al., 2004).

There are several important functions for oligomerization. The first role of dimerization is the regulation or requirement for the export of GPCRs from the endoplasmic reticulum. For example, the heterodimerization of two metabotropic GABAB receptors (GABAB R1 and GABAB R2) is necessary for proper trafficking and function of the receptor (Margeta-Mitrovic et al., 2000; Galvez et al., 2001). The second function of oligomerization is the alteration of pharmacological properties of receptors. One such example is the loss of selective ligand binding for either the δ- or κ- monomers once the two receptors form a δκ-opioid heterodimer (Gomes et al., 2000). In addition, dimerization has also been shown to alter G-protein coupling to the receptor. An example being the dimerization of the dopamine D1 and D2 receptors, leading to coupling of the heterodimer to Gαq, whereas, individually, the dopamine D1 and D2 receptors couple to Gαs and Gαi respectively (Lee et al., 2004; Rashid et al., 2007).

Although the study of GPCR oligomerization has been primarily done in vitro, recent literature has highlighted functional oligomers in vivo (Rivero-Muller et al., 2010).

1.1.6 GPCR Trafficking

Receptor trafficking is a dynamic process that contributes to the regulation and proper function of GPCRs. The general mechanism for endoplasmic reticulum export of GPCRs first involves translation and proper folding of the receptor in the endoplasmic reticulum, followed by the subsequent packaging of the GPCR into transport vesicles, where it is then targeted to the

8 endoplasmic reticulum-golgi intermediate complex. Incomplete or misfolded receptors in the endoplasmic reticulum are degraded by ubiquitination via the proteosome/lysosomal pathway (Meusser et al., 2005). During receptor maturation, various post translational modifications (see section 1.1.6.2) occur while the receptor is being transported from the endoplasmic reticulum to the endoplasmic reticulum-golgi intermediate complex, and then to the trans-Golgi network, before finally being delivered to the plasma membrane (see review [Duvernay et al., 2005]). For GPCRs, trafficking and transport of the receptor from the endoplasmic reticulum to the plasma membrane is considered the rate limiting step in their biogenesis (Petaja-Repo et al., 2000). There are several mechanisms within the cell to aid in the trafficking of a GPCR to the plasma membrane. This sections below will describe and elaborate on these mechanisms.

1.1.6.1 Signal Sequences

The first determinant in cell surface targeting is found in the primary amino acid sequence, in the form of distinct and conserved motifs. It is well established that specific motifs aid in the export of membrane proteins from the endoplasmic reticulum. However, unlike other membrane proteins, GPCRs do not have consensus motifs that are conserved in the different classes of receptors. In fact, not all GPCRs require export motifs for proper targeting to the plasma membrane. For GPCR’s that contain export motifs, these motifs are located on the C-terminus of several of the following receptors: 1B, 2, 3, dopamine D1, II type 1, and α2 adrenergic receptors (Schülein et al., 1996; Bermak et al., 2001; Duvernay et al., 2004; Robert et al., 2005). Although much less prevalent, export motifs also exist in the intracellular loops and N-termini of some GPCRs, such as the human B receptor (Köchl et al., 2002; Duvernay et al., 2009; Angelotti et al., 2010). Mechanistically, it is hypothesized that these export motifs aid receptor trafficking in one of three ways; 1) they allow for the interaction between the receptor and the coat protein 2 export machinery (Miller et al., 2003; Dong et al., 2012), 2) they enable for the interaction between GPCR and specific molecular chaperones (Bermak et al., 2001), or 3) they facilitate oligomerization with other GPCRs (Zhou et al., 2006). In contrast to expressing export motifs, several GPCRs also express endoplasmic reticulum retention motifs on the C-terminus of

GPCRs. To date, only the metabotropic GABAB and mGluR1B receptors have been shown to contain such retention motifs (Margeta-Mitrovic et al., 2000; Chan et al., 2001).

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1.1.6.2 Post Translational Modifications

GPCRs can undergo several post translational modifications while being trafficking from the endoplasmic reticulum to the plasma membrane. The most common of these post translational modifications is N-linked, (Renthal et al., 1973) and O-linked glycosylation (Sadeghi and Birnbaumer, 1999; Petaja-Repo et al., 2000; Nakagawa et al., 2001). The role of glycosylation is dependent on the receptor. For instance, the removal of N-linked sites in the angiotensin 1 and follicle-stimulating hormone receptors leads to endoplasmic reticulum retention (Davis et al., 1995; Deslauriers et al., 1999), but removal from muscarinic M2 and histamine H2 receptors does not affect surface expression (van Koppen and Nathanson, 1990; Fukushima et al., 1995). In addition to glycosylation, GPCRs also commonly undergo palmitoylation at cysteine residues (Qanbar and Bouvier, 2003). Palmitoylation serves to target GPCRs to the plasma membrane (Karnik et al., 1993; Zhu et al., 1995; Schülein et al., 1996; Fukushima et al., 2001; Percherancier et al., 2001), as well as orienting the C-terminal tail to enhance arrestin affinity for the receptor (Charest and Bouvier, 2003).

1.1.6.3 Molecular Chaperones

Lastly, some GPCRs require the binding of specific molecular chaperones for proper trafficking to the plasma membrane. Molecular chaperones can be separated into two different categories. The first category is non-specific protein chaperones that aid in general folding and post translational modifications. These proteins, in general, reside in the endoplasmic reticulum and include heat shock proteins, calnexin, and calreticulin (Siffroi-Fernandez et al., 2002; Mizrachi and Segaloff, 2004). The second category of molecular chaperones are GPCR specific chaperones, proteins that only bind to certain families of GPCRs, and directly influence the trafficking of the receptor to the plasma membrane. Examples of these molecular chaperones include the single transmembrane proteins, such as the family receptor activity modifying proteins (RAMP) 1-3. RAMPs bind and mediate the trafficking of the calcitonin receptor like receptor (CRLR) to the plasma membrane (McLatchie et al., 1998), as well as act as general modulators of GPCR signalling (Hay et al., 2006). Furthermore, the family of receptor transporting proteins (RTP) 1-4 and receptor expression enhancing protein 1 (REEP) also act as molecular chaperones for the olfactory family of GPCRs, via the trafficking of olfactory receptors to the plasma membrane (Saito et al., 2004).

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In addition to single transmembrane proteins acting as molecular chaperones, GPCRs themselves can also act as molecular chaperones, either through homo- or hetero-dimerization. Examples of these are the metabotropic GABAB receptor 2 heterodimerizing with the GABAB receptor 1 for the proper expression and function of the receptor (White et al., 1998). The homodimerization of the β2AR is also important for cell surface targeting (Salahpour et al., 2004). In conclusion, GPCR trafficking to the plasma membrane is a dynamic process that is mediated by different biochemical modifications (i.e. post translational modifications) or biochemical interactions (i.e. molecular chaperones).

1.1.7 GPCR Ligands

There is a large variety of ligands for GPCRs, ranging from a photon of light, to , to small molecules, peptides, or even proteins (Ji et al., 1998). Ligands can bind in two distinct sites on GPCRs, the orthosteric or allosteric binding sites. In general, the orthosteric binding site is defined as the ligand binding site for the endogenous ligand (Wootten et al., 2013). While, the allosteric site is topographically distinct from the orthosteric site (Conn et al., 2009).

1.1.7.1 Orthosteric Ligands

The location of the orthosteric binding site is dependent on the class of GPCR. Class A (rhodopsin like family) have their orthosteric binding site within the transmembrane domains. Class B (secretin like family), and class C (glutamate family) have their orthosteric binding sites in large extracellular domains. Traditional ligands for GPCRs (agonist, antagonist, and ) all bind to the orthosteric binding site. Agonists are ligands that activate a receptor to induce signalling (i.e. efficacy). Biochemically, agonists stabilize the active state of the receptor, promoting the activation of the heterotrimeric G-protein complex (Ji et al., 1998). Inverse agonists act to stabilize the receptor in an in-active conformation; often times the action of inverse agonists is to reduce the constitutive activity of a receptor that is independent of ligand activation (Khilnani and Khilnani, 2011). Antagonists are defined as ligands that bind to the orthosteric binding site but do not have efficacy (Hopkins and Groom, 2002).

1.1.7.2 Allosteric Ligands

It has been well established that allosteric ligands do exist for other proteins, such as hemoglobin and ion channels (Monod et al., 1965). A classic example of an are

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benzodiazepines, which are positive allosteric modulators for the GABAA ion channels (Sieghart, 2015). Allosteric modulators were only discovered to be specific for GPCRs when several compounds were found to block agonist induced signalling of the α2- and β2 adrenergic receptor, without acting as antagonists themselves (Huang et al., 1990). Mechanistically, allosteric ligands bind to a distinct site from the orthosteric binding site, and either inhibit (negative allosteric modulators) or potentiate (positive allosteric modulators) the activation of the receptor by its natural ligand (Conn et al., 2009).

While allosteric modulators have not been a traditional target for drug discovery, there are some important properties of allosteric binding sites that can be exploited. In general, allosteric modulators have four advantages over orthosteric ligands. First, the allosteric site does not bind endogenous ligands, therefore the allosteric ligand is not in competition with other ligands, and the allosteric site is therefore saturable. A saturable site is important, since this allows for a ‘ceiling’ effect to be reached, in contrast to orthosteric targets that have the potential for over stimulation of the target (Christopoulos and Kenakin, 2002). Secondly, allosteric ligands only modulate (positively or negatively) the signalling of the receptor in tissues that express both the endogenous ligand and the receptor. This is important, since allosteric ligands only exert their effects when the receptor is bound by an (Birdsall et al., 1996). Third, some ligands that bind to the orthosteric binding site have physiochemical and pharmacokinetic properties that are challenging for small molecule drug discovery (i.e. receptors). Since allosteric binding sites are separate from the orthosteric binding site, small molecule drug discovery is not constrained by these ligand properties (Conn et al., 2009). Lastly, allosteric sites are ligand binding sites that are topographically distinct from the orthosteric binding site, allowing for a greater diversity of binding sites, even within the same family of receptors, allowing for greater receptor subtype selectivity (Ellis, 1997; Gregory et al., 2007).

Subtype selective orthosteric ligands are often difficult to discover, due to the high degree of homology in subtype orthosteric binding sites (Christopoulos, 2002; Conn et al., 2009; Jones et al., 2012). For example, muscarinic receptors have long been thought to be potential targets for the treatment of neurological disorders, such as Alzheimer’s disease or (Gillespie et al., 1996; Bodick et al., 1997a; Bodick et al., 1997b; Shannon et al., 2000; Mirza et al., 2003). However, subtype selective ligands do not exist, resulting in a limited use of muscarinic ligands for the treatment of these diseases. For example, (M1/M4 preferring agonist) showed

12 preliminary promise in the reduction of behavioural disturbances seen in Alzheimer patients, as well as reducing the positive and negative symptoms of schizophrenia patients. However, xanomeline treatment is associated with high levels of adverse events due to off target activation of M2/M3 receptors (Bymaster et al., 1998; Jakubik et al., 2006).

Due to the potential benefits of targeting the M1 receptor, continued research in the discovery of allosteric modulators led to the generation of subtype selective positive allosteric modulators. 1- (1’-2-methylbenzyl)-1,4’-bipiperidin-4-yl)-1H benzo[d]imidazol-2(3H)-one (TBPB) was the first selective positive allosteric modulator for the M1 receptor that was characterized in vivo (Jones et al., 2008). Similar to the results with xanomeline, TBPB was shown to be efficacious in reducing the positive symptoms in animal models of schizophrenia, through the potentiation of NMDA receptor mediated currents. However, these early positive allosteric modulators were discovered to be bi-topic ligands, binding to both the allosteric and orthosteric binding site (Jones et al., 2008). Further research has yielded the next generation of positive allosteric modulators (i.e. VU0357017 and benzylquinolone carboxylic acid), which bind to a novel allosteric site that does not overlap with the orthosteric binding site (Ma et al., 2009; Lebois et al., 2010). Indeed, this next generation of M1 positive allosteric modulators has been shown to be effective at reversing prefrontal cortex deficits in animal models of schizophrenia and is proposed to be a potential treatment for schizophrenia (Ghoshal et al., 2016; Grannan et al., 2016).

In summary, allosteric binding sites are potential targets for the discovery of sub-type selective ligands. While there are, comparatively, few clinically relevant allosteric modulators when compared to orthosteric ligands, animal studies with positive allosteric modulators of the muscarinic receptor provide in vivo validation for the potential clinical use of allosteric modulators.

1.2 Trace Amine Associated Receptor 1

The focus of this thesis is on TAAR1. The following section will summarize the current literature for TAAR1.

1.2.1 Trace Amines

The compounds that are now classified as trace amines were initially discovered over 100 years ago, and are found in several organisms (Dale and Dixon, 1909; Barger and Dale, 1910). These

13 compounds were initially classified as non-catecholic that have potent sympathomimetic actions. Trace amines are related to classic monoamine (dopamine, norepinephrine, epinephrine, and serotonin) in terms of structure, biosynthesis, cellular localization, anatomic distribution, degradation, and elimination (Figure 1.1 and 1.2) (Boulton and Quan, 1970; Boulton and Wu, 1972, 1973; Wu and Boulton, 1973; Boulton and Baker, 1975). In invertebrates, and serve as major neurotransmitters, functionally replacing the role of epinephrine and norepinephrine normally found in vertebrates (Robertson and Juorio, 1976; Roeder, 1999). However, in vertebrates, particularly in mammals, the precise physiological role of trace amines is less clear. While trace amines are present in many tissues at low levels, including the brain, they have long been considered side products of the synthesis and metabolism of classical monoamines, and were thought to be inactive at physiological levels in (Berry, 2004). High levels of trace amines were most commonly described to act as indirect sympathomimetic ligands that resulted in amphetamine like responses within the brain (Fuxe et al., 1967; Raiteri et al., 1977; Reynolds et al., 1979; Baud et al., 1985; Parker and Cubeddu, 1988; Paterson, 1993; Barroso and Rodriguez, 1996). Indeed, there is substantial evidence that several trace amines can act as “false neurotransmitters” at high concentrations by interacting with monoamine transporters located at the vesicular and plasma membrane, such as the dopamine transporter (DAT) and vesicular monoamine transporter 2 (VMAT2) in an amphetamine-like manner (Kopin et al., 1964; Kopin, 1968). For example, β-phenylethylamine (bPEA) only differs in structure to amphetamine by one methyl group (Figure 1.3). Given at high enough concentrations, systemically administered bPEA can increase extracellular dopamine concentrations, resulting in increased locomotor activity (Dourish, 1982; Hirano et al., 1989; Lapin, 1996; Janssen et al., 1999). The sympathomimetic effects occurring at high trace amine concentrations are not thought to be relevant at physiological concentrations. Although trace amines have long been recognized as substrates for DAT, the serotonin transporter (SERT), and the norepinephrine transporter (NET), their potency for these transporters are at least three orders of magnitude higher than the maximum synaptic concentration of endogenous trace amines (Raiteri et al., 1977; Danek Burgess and Justice, 1999; Liang et al., 2009). Therefore, it is unlikely that trace amines exert their function as monoamine transporter substrates at physiological concentrations. While the exact role of trace amines in mammals has remained elusive for many years, in clinical settings, several studies have reported that dysregulated levels of trace amines are

14 associated with several human diseases such as schizophrenia, bipolar disorders, attention deficit hyperactivity disorder (ADHD), Parkinson’s disease, phenylketonuria and many others.

1.2.2 Synthesis and Metabolism of Trace Amines

The synthesis of trace amines follows a similar pathway to the synthesis of the classic monoamine neurotransmitters dopamine, norepinephrine, and epinephrine (see Figure 1.2) (Berry, 2004). bPEA and p-tyramine are the primary trace amines, from which all other trace amines are derived. bPEA and p-tyramine are derived from the of and tyrosine by aromatic L-amino acid decarboxylase (AADC) respectively. Further modifcation of bPEA and p- tyramine by dopamine-β-hydroxylase (DBH) or phenylethanolamine N-methyltransferase (PNMT) results in the formation of other trace amines. β-hydroxylation of p-tyramine by DBH produces p-octopamine, and methylation of the primary amine of tyramine or octopamine by PNMT produces N-methyltryamine and respectively. Methylation of the primary amine of bPEA by PNMT produces N-methylphenethylamine. Similar to the metabolism of dopamine, norepinephrine, and epinephrine, the first step in the metabolism of trace amines is completed by monoamine oxidases (MAO)-A and -B (Philips and Boulton, 1979; Durden and Philips, 1980; Yu et al., 2003), with only bPEA being an MAO-B selective substrate (Yang and Neff, 1973).

Even though the levels of trace amines in the brain are low, trace amines are synthesized at rates that are equivilent to that of the monoamine neurotransmitters (dopamine, epinephrine and serotonin) (Durden and Philips, 1980; Paterson et al., 1990). Therefore, the differences in the levels of trace amines, compared with monoamine neurotransmitters, are most likely due to their rapid metabolism (Durden and Philips, 1980).

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Acid Metabolite Acid Metabolite Parent Compound Aldehyde Metabolite (Primary Metabolite (Primary Metabolite for TA) for Catecholamines)

β-

p-Tyramine A/B

p-Octopamine Oxidase

Synephrine Aldehydedehydrogenase

Dopamine Monoamine

Methyltransferase -

Norepinephrine O

- Catechol Epinephrine

Figure 1.1. Metabolic pathway of trace amines and catecholamines. The primary pathway for the metabolism for both trace amines and catecholamines involves the formation of acid derivatives from these compounds. The first step to the metabolism of these compounds involves the conversion of the primary or secondary amine to a short-lived aldehyde intermediary through A or B. Further metabolism of these aldehyde intermediaries by aldehyde dehydrogenase produces the acid form of the metabolites, where these acid forms are the primary metabolites for both trace amines and catecholamines. Secondary metabolites are also formed by the reduction of the aldehyde intermediary to an through aldehyde reductase. Lastly the acid metabolites of dopamine, norepinephrine and epinephrine are further metabolized by catechol-O-methyltransferase as their primary metabolite that is excreted through the urine. Figure adapted from (Lam et al., 2017).

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Trace Amines

L-Phenylalanine β-phenethylamine N-Methylphenethylamine

Phenylalanine Hydroxylase

N-Methyltyramine

methyltransferase (PNMT) methyltransferase

-

N Amino Acid Decarboxylase (AADC) Amino Acid Decarboxylase L-Tyrosine - p-Tyramine p-Octopamine Synephrine

Tyrosine Hydroxylase (TH)

Aromatic L Aromatic Phenylethanolamine

L-Dopa Dopamine (DBH) hydroxylase Dopamine beta Norepinephrine Epinephrine

Figure 1.2. Pathway for Trace Amine and Catecholamine Production. The synthesis of the endogenous neurotransmitters dopamine, norepinephrine, and epinephrine follow the enzymatic modification of phenylalanine. First phenylalanine is P-hydroxylated to tyrosine by phenylalanine hydroxylase. Next L-DOPA is produced by the O-hydroxylation of tyrosine by tyrosine hydroxylase. Decarboxylation of L-DOPA by Aromatic L-Amino Acid Decarboxylase (AADC) produces dopamine where further β- hydroxylation of dopamine by Dopamine Beta Hydroxylase (DBH) produces norepinephrine and methylation of the primary amine by Phenylethanolamine N- methyltransferase (PNMT) produces epinephrine. The primary trace amines bPEA and p-tyramine are formed from decarboxylation of phenylalanine and tyrosine by AADC respectively. Further β- hydroxylation of p-tyramine by DBH produces octopamine and methylation of the primary amine of tyramine or octopamine produces N-Methyltryamine and synephrine respectively. Methylation of the primary amine of bPEA by PNMT produces N-methylphenethylamine. Figure adapted from (Lam et al., 2017).

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1.2.3 Dietary Effects of Trace Amines

High levels of trace amines were first discovered in extracts of ergot or putrefied meat. Since this discovery, it has been shown that both prokaryotes and eukaryotes produce trace amines. Importantly, high levels of trace amines can be found in edible produce, with highest naturally occurring levels of trace amines being found in certain plants (ie. cacao beans), and fermented foods such as cheese, beer, and wine. In addition, the bacteria found in the gut of mammals can also produce trace amines, by the action of bacterial AADC (Jansen et al., 2003). However, in general, the high levels of trace amines from diet have no effect on human physiology, due to the fast peripheral metabolism of trace amines by MAO found in the gut (McCabe and Tsuang, 1982; McCabe, 1986). However, it is recommended that patients using MAO inhibitors avoid fermented foods due to the potential accumulation of trace amines, specifically tyramine, which can lead to a hypertensive reaction (Anderson et al., 1993; Finberg and Gillman, 2011).

1.2.4 Properties of Trace Amines within the Neuron

As mentioned previously, the primary properties of trace amines are their low concentrations in the brain (~100 ng/g of tissue), lack of vesicular storage, and fast metabolism. Trace amines such as p-tyramine have been found to readily diffuse across an artificial membrane with a T1/2 = 13s (Berry et al., 2013). At a physiological pH, p-tyramine has a positive charge on the primary amine. Interestingly, based on the Nernst equation for the behaviour of a partially charged ion, it is expected that p-tyramine should readily diffuse across the plasma membrane, following the flow of ions upon membrane (Berry et al., 2016). Therefore, it is predicted that p- tyramine, and by extension other trace amines, can be found predominantly in the extracellular space, due to their low T1/2 of diffusion and positive charge. However, quite paradoxically when [3H]tyramine is loaded into synaptosomes, from both the frontal cortex and , depolarizing concentrations of KCl did not lead to an increase in extracellular [3H]tyramine as expected (Berry et al., 2016). It turns out, that p-tyramine is actively taken up into the synaptosome by the organic 2 (OCT). While these experiments were performed with p-tyramine, it is postulated that OCT-2 can also transport other trace amines, such as bPEA, as well. While it has traditionally been thought that trace amine levels are primarily regulated through synthesis and metabolism, these results indicate that another level of regulation for trace amines, within neurons, could be through active uptake by OCT-2.

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1.2.5 Clinical Effects of Trace Amines

Clinical studies have shown that trace amines, and their receptors, are linked to multiple neurological disorders such as schizophrenia, ADHD, bipolar disorder, and . Specifically, in the context of depression, it has been shown that bPEA levels in the brain correlate with the disease. Indeed, decreased levels of bPEA have been detected in the cerebral spinal fluid of depressed patients when compared to controls (Sandler et al., 1979) and bPEA or L- phenylalanine (precursor of bPEA) supplementation in these patients produced relief from depression (Sabelli et al., 1996). Furthermore, MAO inhibitors are effective treatments for atypical depression (Jarrett et al., 1999), where inhibition of MAO is known to increase systemic levels of trace amines (Murphy et al., 1998). In fact, an increase in bPEA levels has been observed in the Maob knockout mouse, indicating that in the absence of MAO-B, there are increases in bPEA that are similar to those seen with MAO inhibitors (Grimsby et al., 1997). While the actions of bPEA is in the central , bPEA can also be detected peripherally (i.e. urine). Peripheral excretion of bPEA has been proposed as a biomarker for several neurological diseases.

In terms of ADHD, it has recently been found that children suffering from the disease show decreased levels of bPEA (Baker et al., 1991; Kusaga, 2002). In addition to this, ADHD patients have decreased urinary levels of bPEA, postulating that bPEA could maybe be used as biomarker for ADHD (Scassellati et al., 2012). In patients suffering from schizophrenia, increased plasma levels of bPEA have been linked to the development of the disease (Shirkande et al., 1995). Moreover, patients suffering from paranoid schizophrenia have increased urinary secretion of bPEA (Potkin et al., 1979). Lastly, high levels of bPEA have also been associated with bipolar affective disorder. Indeed, it was found that women suffering from bipolar effective disorder have high urinary excretion of bPEA, with MAO inhibitors (standard treatment for disease) further increasing bPEA levels, leading to exacerbating of the symptoms of bipolar affective disorder in these patients (Karoum et al., 1982).

While other trace amines are less studied, when compared with bPEA, deficits in tyramine and octopamine have also been reported in cases of depression, where there is a significant decrease in the excretion of the primary tyramine/octopamine metabolite p-hydroxymandelic acid in patients suffering from depression (Sandler et al., 1979).

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In summary, trace amines have been shown to be associated with neurological disorders. It is not known whether the increase in trace amines in the brain is the result or the cause of these diseases. Indeed, many of these studies were published before the discovery of TAAR1, a GPCR that binds trace amines as its endogenous ligands.

1.2.6 Trace Amine Associated Receptor (TAAR) Family

In 2001, a new family of class A rhodopsin-like GPCRs were cloned that specifically bound trace amines as their endogenous ligands: there were named Trace Amine Receptors (TA1 and TA2 respectively) (Borowsky et al., 2001; Bunzow et al., 2001). Within the next several years, other GPCRs were deorphanized and classified as trace amine receptors, based on their sequence similarity to TA1 and TA2 (Lindemann and Hoener, 2005). However, these other receptors did not bind to endogenous trace amines, and it was suggested that the nomenclature of this family be changed to trace amine associated receptors (TAAR). Using this nomenclature, TA1 and TA2 were renamed TAAR1 and TAAR4 respectively. While this nomenclature was officially adopted for the names, it was suggested by the International Union of Pharmacology, that TAAR1 retain the

TA1 nomenclature (Maguire et al., 2009). However, the literature has adapted to the use of TAAR as the primary nomenclature for the receptors. The TAAR family of genes are differentially expressed across mammalian , with 15, 17, 6, and 6 receptors reported in rat, mouse, macaque, and humans respectively (Hashiguchi and Nishida, 2007; Grus and Zhang, 2008; Nei et al., 2008; Horowitz et al., 2014).

1.2.7 Anatomical Expression of TAAR1

TAAR1 tissue expression pattern has been reported for mouse (Borowsky et al., 2001; Lindemann et al., 2008; Di Cara et al., 2011), rat (Bunzow et al., 2001; Grus and Zhang, 2008; Szumska et al., 2015), and rhesus (Miller et al., 2005; Xie et al., 2007; Xie and Miller, 2009). TAAR1 is expressed primarily in the , as well as several peripheral tissues. While human evidence for TAAR1 expression has remained elusive, the creation of an anti-human TAAR1 monoclonal has provided experimental evidence for TAAR1 expression in human tissues (see below) (Revel et al., 2013; Raab et al., 2016).

Initial studies with RT-PCR showed TAAR1 expression in several mouse brain regions including, the , , , dorsal root ganglia and (Borowsky et al.,

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2001). Further studies using in situ hybridization identified TAAR1 mRNA levels in several monoaminergic regions, including, substantia nigra (SN), VTA, (LC), and dorsal raphe nucleus (DRN) (Borowsky et al., 2001). These results were subsequently confirmed by the generation of the Taar1-KO mouse.

One of the Taar1-KO mouse line was generated by replacing the entire coding region of the Taar1 gene with the LacZ reporter gene. Subsequent LacZ staining in the Taar1-KO brains showed LacZ positive staining in similar brain regions to those reported with previous studies using RT-PCR and in situ hybridization (Lindemann et al., 2008). Specifically, these areas were the dopamine and serotonin containing regions of the hypothalamus, SN, VTA, amygdala, and DR (Lindemann et al., 2008). In a separately generated Taar1-KO mouse line, TAAR1 expression was also observed in the SN, VTA, frontal cortex and striatum (Di Cara et al., 2011). In brains of rhesus monkeys, TAAR1 mRNA is expressed in monoaminergic regions, including the SN/VTA, LC, DR, amygdala, , and nucleus accumbens (NAc) (Xie et al., 2007).

In accordance with these early mRNA expression studies, functional evidence for TAAR1 signalling in the mouse brain was also found in the VTA and DRN, using electrophysiological outputs (Revel et al., 2011). However, contrary to expression data, no TAAR1 specific signalling was found in the LC. Together, these studies clearly show that TAAR1 is expressed in monoaminergic regions in the brain and may therefore be implicated in the modulation of dopamine and serotonin neurotransmission.

While there is substantial evidence for TAAR1 expression, and function, in the rodent brain, human expression levels of TAAR1 within the brain have, so far, not been studied extensively. Currently, the only report of TAAR1 expression in the originates from studies utilizing RT-PCR, showing low levels of TAAR1 transcripts in the amygdala, hypothalamus, cerebellum, dorsal root ganglia, and hippocampus (Borowsky et al., 2001). However, even with the recent discovery of a highly specific anti-human TAAR1 monoclonal antibody, no evidence for TAAR1 protein expression in the human brain has been reported.

It is important to note that in addition to the brain, TAAR1 is also expressed in the spinal cord (Gozal et al., 2014), peripheral tissues (Revel et al., 2013), as well as immune cells (Nelson et al., 2007; Panas et al., 2012; Babusyte et al., 2013). In , TAAR1 is necessary for chemotaxic migration of cells towards TAAR1 agonists. Moreover, TAAR1 signalling in B and T

21 cells can trigger immunoglobulin and release, respectively (Babusyte et al., 2013). TAAR1 is also expressed in the islets of Langerhans, and intestines, based on LacZ staining patterns carried out on Taar1-KO LacZ mice (Revel et al., 2013). Furthermore, this expression profile has been confirmed in humans. Using the human TAAR1 antibody, TAAR1 specific staining in peripheral tissues, such as the Beta cells of the pancreas, , and pylorus, has been reported (Raab et al., 2016). Interestingly, TAAR1 signalling appears to regulate secretion in mice, whereby administration of the TAAR1 selective agonist RO5166017 resulted in increased glucose-dependent insulin secretion (Raab et al., 2016). In accordance with this study, the administration of the selective TAAR1 partial agonist, RO5263397, reverses the side effect of weight gain observed with the , indicating that peripheral TAAR1 signalling can regulate metabolic (Revel et al., 2012a). These results led the authors to conclude that TAAR1 could also be a potential novel target for the treatment of metabolic diseases such as type 2 or .

1.2.8 TAAR1 Ligands

In general the TAAR family of receptors can be characterized into two different subsets, based on their ligand recognition profile; primary amine (Taar1-4) and tertiary amine (Taar5-9) detectors (Ferrero et al., 2012). As with other receptors that bind to biogenic amines, the human TAAR receptors contain a highly conserved Asp1033.32 (superscripts represent Ballesteros-Weinstein nomenclature) (Ballesteros and Weinstein, 1995) that is required for salt bridge formation and ligand recognition (Shi and Javitch, 2002). It is interesting to note that in mice and zebra fish, only 13/15 and 27/112 of the TAAR receptors contain this Asp1033.32.

Of all the TAAR receptors, only TAAR1 and TAAR4 (previously TA1 and TA2) have been shown to be activated by trace amines (Borowsky et al., 2001; Bunzow et al., 2001). While both TAAR1 and TAAR4 are expressed in rodents, TAAR4 is a in humans (Liu et al., 1998; Maguire et al., 2009). Importantly, all the TAAR receptors (except TAAR1) have also been shown to function as a subset of olfactory receptors in mice, as they are expressed in the (Liberles and Buck, 2006; Dewan et al., 2013; Zhang et al., 2013; Liberles, 2015). As putative olfactory receptors, all these TAARs induce canonical olfactory signalling via a Golf- mediated pathway. However, recent studies have suggested that TAAR5 may have significant

22 differences in its signalling, compared with other TAARs, with TAAR5 displaying basal signalling activity via the Gq/11 pathway (Dinter et al., 2015).

Of all the TAAR receptors, TAAR1 has attracted the greatest interest from the research community. The human TAAR1 receptor is a G-protein-coupled 7-transmembrane domain receptor with short N- and C-termini. The gene for the human TAAR1 is located on 6q23.2 and encodes for a 332 amino acid GPCR that is generated from a single (Zucchi et al., 2006). The human, rat, and mouse TAAR1 receptors couple to Gαs heterotrimeric G-protein to stimulate the production of cAMP (Borowsky et al., 2001; Bunzow et al., 2001; Barak et al., 2008).

As mentioned previously, TAAR1 has a high affinity for endogenous trace amines, such as p- tyramine and bPEA, but a low affinity for classic monoamine neurotransmitters such as dopamine, serotonin and norepinephrine (Borowsky et al., 2001; Bunzow et al., 2001). In addition to endogenous trace amines, TAAR1 also has high affinity for other classes of compounds, such as adrenergic drugs, , , dopamine metabolites (i.e. 3-methoxytyramine), derivatives (i.e. 3-iodothyronamine [T1AM]), and psychoactive drugs (i.e. amphetamine and 3,4-methylenedioxymethamphetamine [MDMA]) (Figure 1.3) (Bunzow et al., 2001; Scanlan et al., 2004; Sotnikova et al., 2010; Liu et al., 2014; Sukhanov et al., 2014). Interestingly, it has been proposed that one of the mechanisms by which amphetamine, MDMA, and benzofurans exert part of their biological effects is through their direct action on TAAR1 (Bunzow et al., 2001; Xie and Miller, 2009; Di Cara et al., 2011; Rickli et al., 2015). In fact, recent reports demonstrated that selective TAAR1 agonists could be useful for attenuating the rewarding properties of cocaine and in animal studies (Pei et al., 2014; Thorn, Jing, et al., 2014; Thorn, Zhang, et al., 2014; Cotter et al., 2015; Harkness et al., 2015).

1.2.8.1 Selective TAAR1 Ligands

Beginning in 2009, scientists from Hoffmann-La Roche published multiple studies of novel, selective, high affinity ligands for TAAR1, outlining both their in vitro and in vivo characterization. The selective TAAR1 antagonist RO5212773 (EPPTB) was the first to be described (Bradaia et al., 2009). Electrophysiological studies in mouse brain slices, treated with EPPTB, showed an increase in the firing rate of neurons in the ventral tegmental area (VTA) similar to the Taar1-KO mice (tested in parallel). Mechanistically, it was found that

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TAAR1 modulates the firing rate of dopaminergic neurons through the activation of the kir3 channels. Furthermore, a functional link between TAAR1 and the dopamine D2 receptor was discovered, where antagonism of TAAR1 via EPPTB resulted in an increased dopamine D2 receptor agonist potency (Bradaia et al., 2009). This functional link with the dopamine D2 receptor was the first functional link observed between TAAR1 and the dopamine D2 receptor in intact neurons. EPPTB remains the only known TAAR1 antagonist; however, the pharmacokinetic properties of EPPTB preclude its use for in vivo studies.

Next, a series of high affinity and selective agonists for TAAR1 were reported that were based on either 2-benzyl-imidazoline (Galley et al., 2012), or 2-aminooxazole backbones (Galley et al., 2016). The first agonist is RO5166017 (Revel et al., 2011) which has very good pharmacokinetic properties, and was the first TAAR1 selective ligand to be tested in vivo. Electrophysiological studies in mouse brain slices treated with RO5166017 showed a decrease in the firing rate of dopaminergic neurons in the VTA, with no activity in brain slices from the Taar1-KO mice. This result is consistent with the results from EPPTB, whereby TAAR1 signalling alters the firing rate of dopaminergic neurons (agonist decreases firing, while antagonist increase firing). When injected into mice, this compound decreased the locomotor stimulating effects of psychostimulant drugs, such as cocaine (Revel et al., 2011). This was consistent with the observation that TAAR1 activation decreases the firing rate of dopaminergic neurons, and therefore, decreases dopaminergic tone. Importantly, reduction of psychostimulant-induced hyperlocomotor activity is a hallmark for antipsychotic drug efficacy which are used for the treatment of positive symptoms in schizophrenia (Peleg-Raibstein et al., 2008). This suggested that TAAR1 is a potentially novel target for the treatment of schizophrenia.

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Dopaminergic ligands

Methamphetamine Amphetamine MDMA Apomorphine

Catecholamine Metabolites

3-Methoxytyramine 4-Methoxytyramine

Imidazoline ligands

Guanabenz

Thyronamines

T1AM T0AM

Synthetic Agonists

RO5073012 RO5263397 RO5203648 RO5166017 RO5256390 ‘Compound 1’* ‘Compound 8’+ ‘Compound 16’ +

Synthetic Antagonists

EPPTB

Figure 1.3. Known ligands for human TAAR1. Potent agonists for TAAR1 are found within the following classes of known synthetic ligands: dopaminergic and imidazoline agonists. In addition, it has been shown that catecholamine metabolites and are potent TAAR1 agonists. Novel and selective synthetic agonists for TAAR1 have also been developed and discovered by Hoffmann-La Roche (RO compounds) as well as novel chemical scaffolds found from in silico screens (compound 1*, 8+, and 16+). Lastly the only known antagonist for TAAR1 is the synthetic ligand EPPTB. Figure adapted from (Lam et al., 2017). * (Cichero et al., 2014) + (Lam et al., 2015)

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New analogues of RO5166017 (including RO5256390) were developed, and also showed efficacy in reducing psychoactive drug-induced hyperlocomotion (Revel et al., 2013). Treatment with this analog resulted in improve outcomes in behavioural models of cognitive impairment, such as PCP- induced attentional set-shifting task in and object retrieval tasks in monkeys. Since cognitive impairment is another hallmark of schizophrenia, these studies suggest that TAAR1 agonists could represent a new class of drug for the treatment of schizophrenia and all of its associated symptoms.

Based on the full agonist pharmacophore RO5166017, three new analogues were developed that displayed partial agonism on TAAR1 in vitro (Galley et al., 2012; Revel et al., 2012a; Revel et al., 2012b; Revel et al., 2013). These three new partial agonists (RO5263397, RO5203648, and RO5073012) are highly selective for TAAR1 and have similar favourable pharmacokinetic profiles as the full agonist, RO5166017. However, counterintuitively, these partial agonists seem to act as antagonists in in vitro experiments, and as agonists in in vivo experiments. For instance, in vitro experiments with both RO5263397 and RO52603648 show an increased firing rate of dopaminergic neurons in the VTA, similar to what was observed with the antagonist EPPTB. However, in vivo behavioural tests showed the partial agonists to act in a similar fashion to TAAR1 full agonists, where RO5263397, RO5203648, and RO5073012 reduced hyperlocomotion induced by psychostimulant administration (Revel et al., 2012a; Revel et al., 2012b; Revel et al., 2013). Furthermore, both RO5263397 and RO52603648 exhibited -like effects in the forced-swim test. In addition, studies with the partial agonist RO5263397 showed that it attenuated the rewarding effects of cocaine (Thorn, et al., 2014a; Thorn, et al., 2014b), as well as methamphetamine in rats (Thorn et al., 2014a). Meanwhile, agonists RO5203648 and RO5256390 prevented the relapse of cocaine seeking behaviour in rats (Pei et al., 2014). Interestingly, both the full and the partial agonist, RO5166017 and RO5203648 respectively, were able to decrease impulsivity, a distinct behaviour involved in the pathophysiology of several brain pathologies, including ADHD and drug (Espinoza et al., 2015a). Please see section 1.2.12 for additional detail on the role of TAAR1 and addiction.

One of the approaches for discovering novel TAAR1 ligands is the rational modification of known TAAR1 ligands. One of the TAAR1 agonists, T1AM, is of specific interest, due to it being the most potent endogenous ligand for TAAR1 (Scanlan et al., 2004). Unfortunately, as a derivative of the thyroid hormone, thyroxine, T1AM has various off-target effects, including binding to amine transports and mitochondrial proteins (Chiellini et al., 2015). Therefore, using T1AM as the

26 chemical backbone, an effort was made to generate analogues that would be more selective for TAAR1. While initial strategies found analogues that were amendable to further modification, none of these compounds showed a significant increase in either TAAR1 selectivity, or improvement in off-target effects (Chiellini et al., 2015, 2016).

Lastly, with the use of computational modelling, homology models of TAAR1 were generated for the purposes of both understanding the molecular determinants responsible for ligand-receptor interaction, as well as, for use in in silico screens to identity novel TAAR1 ligands (Tallman and Grandy, 2012; Cichero et al., 2013, 2014; Reese et al., 2014). The first published homology model was the human TAAR1 homology model based off of the agonist bound β2AR (PDB: 3PDS) (Cichero et al., 2013). This method provided several novel low potency, agonists and one antagonist for TAAR1 (Cichero et al., 2014). Based on the fact that the template has low sequence similarity to TAAR1, the homology model was therefore not accurate enough for the discovery of novel high affinity ligands for TAAR1. In addition, due to the fact that all, but one, of the currently known TAAR1 ligands are agonists, the homology model is inevitably biased for a conformation that would bind agonists during the optimization phase for this model (see section 1.3.2). However, by developing a theoretical model of the human TAAR1 via homology modelling and docking studies with known TAAR1 agonists, important residues for the activity of these ligands were identified (Cichero et al., 2013, 2014).

In particular, two residues (Asp 103 and Gln 286) have been indicated as potential anchor-points for the ligand recognition process with TAAR1. Using mutagenesis and homology models for the mouse and rat TAAR1, other important structural components of the ligand-binding pocket were determined. As predicted from previous models, of the conserved Asp 103 abolished the binding of known TAAR1 agonists, such as bPEA, to TAAR1. In addition, residue 268 was important for the strength of binding of amphetamine and methamphetamine, while position 287 conferred the selectivity to specific enantiomers of amphetamine (Reese et al., 2014). These studies, and others, provide crucial information in order to improve the current homology models for TAAR1, since a crystal structure for TAAR1 has not been crystalized.

1.2.9 Cellular Localization of TAAR1

The subcellular localization of TAAR1, in heterologous cell systems, appears to be primarily in the intracellular space, with poor plasma membrane localization (Xie et al., 2008; Xie and Miller,

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2009). However, due to technical limitations (i.e. lack of specific and selective ), the precise cellular localization of TAAR1 protein in an endogenous system, such as neurons, is currently unknown. There are conflicting reports in the literature, with regards to the subcellular localization of TAAR1, where it is widely believed that TAAR1 is present as an intracellular receptor. This is not a novel concept, as other GPCRs like the β2AR have been shown to be expressed on the nuclear membrane (Tadevosyan et al., 2012) and endosomes (Irannejad et al., 2013) in addition to the plasma membrane. Early studies on TAAR1 led to this “intracellular receptor” hypothesis, showing intracellular localization of the rat TAAR1 in HEK293 cells, which ultimately led the authors to postulate that TAAR1 may function as an intracellular receptor (Bunzow et al., 2001). Further studies, using GFP-tagged rhesus monkey TAAR1 in HEK293 cells, showed intracellular localization (Miller et al., 2005). Cell fractionation studies showed that TAAR1 was only present in the total membrane fraction, further confirming TAAR1 localization in intracellular membranes (Xie et al., 2008).

The intracellular localization of TAAR1 led to the issue of how intracellular receptors (TAAR1 in this case) can access their ligands. Several mechanisms were hypothesized by which TAAR1 could gain access to ligands in the intracellular space: 1) monoamine transporters could provide an avenue for TAAR1 ligands to gain access to the intracellular space, or 2) the predominant endogenous agonists of TAAR1 (i.e. trace amines) were localized within the . Indeed, independent groups have provided evidence to support the transport of TAAR1 ligands through monoamine transporters. For instance, in rat neo-natal spinal cords, trace amine treatment induced locomotor-like activity in motoneurons within the spinal cord. The authors discovered the requirement of the transmembrane solute carrier SLC22A for this effect. Pharmacological blockade of this transporter abolished the trace amine effect, further supporting the requirement of membrane bound transporters to allow TAAR1 ligands access to the intracellular space and activation of the receptor (Gozal et al., 2014).

Although it is possible that TAAR1 is localized in intracellular compartments, other GPCRs, such as the olfactory receptors, are not expressed on the plasma membrane when transfected in heterologous cell lines such as HEK293. It is known that some GPCRs require the expression, and binding, of ‘specific’ molecular chaperones for proper surface expression (see section 1.1.6.3).

Such receptors include the metabotropic GABAB receptors (White et al., 1998), olfactory receptors (Saito et al., 2004), and calcitonin receptors (McLatchie et al., 1998). Since the vast majority of

28 the TAAR family of receptors (except TAAR1) function as a subset of olfactory receptors, it is possible that TAAR1 may also require a specific molecular chaperone for proper plasma membrane expression. Indeed, using cell fractionation and microscopy studies in HEK293 cells, it has been shown that the co-expression of the dopamine D2 receptor with TAAR1 increases the localization of TAAR1 on the plasma membrane (Harmeier et al., 2015). In addition, in rat and mouse thyroid epithelial cells, TAAR1 is expressed on the plasma membrane of the primary cilium at the apical poles of these cells (Szumska et al., 2015). Therefore, dependent on the tissue or cells, it is possible that TAAR1 can exist and function at the plasma membrane, as well as intracellular compartments. This would not be a unique feature to TAAR1. The sigma 1 receptor, which is a single transmembrane receptor, is normally found in the ER; however, its binding to select membrane proteins results in the localization of this receptor to the plasma membrane (Alonso et al., 2000)

1.2.10 Cellular Signalling

TAAR1 is a Gαs coupled GPCR that increases cAMP levels upon agonist stimulation (Borowsky et al., 2001; Bunzow et al., 2001; Barak et al., 2008). In addition to G-protein mediated signalling, TAAR1 activation also leads to increased ERK and CREB phosphorylation in the mouse brain (Sotnikova et al., 2010), as well as phosphorylation of PKA and PKC in HEK293 transfected cells, rhesus monkey activated lymphocytes (Panas et al., 2012), and human T lymphocytes (Sriram et al., 2016). Furthermore, it was discovered that TAAR1 signalling in VTA brain slices leads to the activation of GIRK channels via the βγ subunits of G-proteins (Bradaia et al., 2009). Interestingly, TAAR1 directly influences the signalling of the dopamine D2 receptor through its heterodimerization with the dopamine D2 receptor (Espinoza et al., 2011). Specifically, TAAR1 regulates dopamine D2 receptor signalling through the β-arrestin2/Akt/GSK3 pathway in the striatum (Revel et al., 2012a; Espinoza et al., 2015b; Harmeier et al., 2015). While the dopamine D2 receptors traditionally signal through the Gαi pathway to reduce cAMP levels in the cell, it has been shown that the dopamine D2 receptor can also signal through the G-protein independent β- arrestin2/Akt/GSK3β pathway (Beaulieu et al., 2005, 2008). Importantly, both the Gαi and β- arrestin2/Akt/GSK3β pathways are important for dopamine mediated behaviours (Beaulieu and Gainetdinov, 2011).

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TAAR1 has been a challenging receptor to study in vitro, due to difficulty in expressing the native receptor at the plasma membrane in heterologous cell lines (Grandy, 2007). It has been proposed that the lack of expression of TAAR1 at the plasma membrane is due to its intracellular localization (as previously mentioned) (Xie and Miller, 2007; Xie et al., 2007; Miller, 2011). Much of the early pharmacological characterization of TAAR1 required modifications to the receptor in order to promote the trafficking of TAAR1 to the plasma membrane. These modifications included: exchanging the third intracellular loop, N-, and C-terminus of the human TAAR1 with the residues from the rat TAAR1 (Lindemann and Hoener, 2005; Reese et al., 2007); the addition of a 16 amino acid signal sequence to the N-terminus of the rat TAAR1 (Bunzow et al., 2001); co-expression of human TAAR1 with the rat Gαs (Wainscott et al., 2007); and the addition of the first nine amino acids of the β2AR to the N-terminus of TAAR1 (Barak et al., 2008). With these receptor modifications, it became possible to study TAAR1 pharmacology in heterologous expression systems (Borowsky et al., 2001; Bunzow et al., 2001; Barak et al., 2008; Lam et al., 2015). cAMP reporter assays have been instrumental in assessing TAAR1 signalling in vitro (Miller et al., 2005; Xie et al., 2007; Barak et al., 2008; Revel et al., 2011; Panas et al., 2012). In particular, the use of bioluminescence resonant energy transfer (BRET) based cAMP biosensors has proven to be a powerful tool for the discovery of novel ligands for TAAR1 (Barak et al., 2008; Sotnikova et al., 2010; Espinoza et al., 2011, 2013; Salahpour et al., 2012; Sukhanov et al., 2014; Lam et al., 2015).

Furthermore, functional and molecular interactions between the dopamine D2 receptor and TAAR1 have been shown both in vitro and in vivo. Due to the lack of a specific TAAR1 antibody in early TAAR1 research, evidence for TAAR1 and dopamine D2 interactions were mostly found using indirect methods, where it was shown that antagonism of TAAR1 in mouse brain slices resulted in increased dopamine D2 receptor agonist potency (Bradaia et al., 2009). Furthermore, in vitro studies showed the formation of heterodimers between the dopamine D2 receptor and TAAR1 in HEK cells, where treatment (a dopamine D2 ) enhanced TAAR1 signalling in these cells (Espinoza et al., 2011). Later studies with the Taar1-KO mouse showed the functional interaction between TAAR1 and both post synaptic (Espinoza et al., 2011; Espinoza et al., 2015b) and presynaptic dopamine D2 receptors (Leo et al., 2014) (see below). The interaction between TAAR1 and the dopamine D2 receptor was not shown directly until the generation of the specific anti-TAAR1 monoclonal antibody. Immunoprecipitation studies showed that TAAR1 co-immunoprecipitates with the dopamine D2L receptor, in both rat brain tissue and

30 transfected cells (Harmeier et al., 2015). Furthermore, cell fractionation studies in transfected cells showed enhanced TAAR1 expression on the plasma membrane when the receptor was co- expressed with the dopamine D2L receptor. While dopamine D2 receptor’s interaction with TAAR1 remains the most studied system, others have reported functional and molecular interactions between TAAR1 and monoamine transporters DAT, SERT, and NET in HEK cells (Miller et al., 2005; Xie and Miller, 2007; Xie et al., 2007) and in mouse and rhesus monkey synaptosomes (Xie and Miller, 2009). While it is currently not known what the physiological consequences of TAAR1 and monoamine transporter interactions have, these data show that TAAR1 interacts with a number of different membrane bound proteins.

1.2.11 TAAR1 Mutant Mice

In the absence of selective ligands modulating TAAR1 activity, much of the early insight into the physiological role of TAAR1 was gained through the study of Taar1-KO animals (Wolinsky et al., 2007; Lindemann et al., 2008; Di Cara et al., 2011). Generally, Taar1-KO mice do not show major basal behavioural abnormalities, with no differences in body weight, temperature, or basal locomotor activity compared with WT animals. In contrast, at the biochemical level, studies of the Taar1-KO mice showed small, but significant, changes in the dopamine system. The striatum of these mice showed an upregulation of both pre- and post- synaptic dopamine D2 receptor protein and mRNA levels (Leo et al., 2014; Espinoza, Ghisi, et al., 2015), as well as a higher population of high affinity dopamine D2 receptors (Wolinsky et al., 2007).

Further characterization of the Taar1-KO mice found that there were changes in the homeostasis of monoamine systems in the brains of these animals. Ex vivo studies, looking at the of neurons from the VTA and DRN, showed that neurons derived from Taar1-KO mice had an increase in their basal firing rate (Bradaia et al., 2009; Revel et al., 2011; Revel et al., 2012a; Revel et al., 2012b). The increase in the basal firing rate of aminergic neurons from the Taar1-KO mice indicates that TAAR1 may be constitutively active, or tonically activated, by endogenous trace amines (Revel et al., 2012b). While the Taar1-KO mice did not have altered basal levels of dopamine or 5-HT in the striatum (Lindemann et al., 2008; Bradaia et al., 2009; Revel et al., 2011), studies have shown an enhanced release of dopamine in the NAc, following amphetamine administration (Leo et al., 2014). In addition, the Taar1-KO mice show an increased

31 sensitivity in their post synaptic dopamine D2 receptors (Espinoza et al., 2015b), as well as a dysregulation of NMDA receptor mediated glutamate signalling in the pre frontal cortex (Espinoza et al., 2015a)(see below). Behavioural changes in the Taar1-KO mice include increased sensitivity to psychostimulants (i.e. MDMA and cocaine); increased behavioural and reinforcing effects of other drugs of abuse such as ethanol, (Lynch et al., 2013) methamphetamine (Achat-Mendes et al., 2012) and amphetamine; and impaired sensorimotor gating (Wolinsky et al., 2007; Lindemann et al., 2008; Di Cara et al., 2011). Indeed it has been postulated that these behavioural and biochemical changes in the Taar1-KO mice are associated with the ‘positive symptoms’ of schizophrenia; with the Taar1-KO mice being proposed as a potential mouse model for this disease (Wolinsky et al., 2007).

Interestingly, it was found that the DBA/2J inbred strain of mice have a non-synonymous single nucleotide polymorphism (C229A) in the Taar1 gene, leading to the expression of a non-functional TAAR1 receptor. The authors postulate that, while this receptor does not bind TAAR1 ligands, the receptor can still participate in important protein-protein interactions, such as those with the dopamine D2 receptor (Harkness et al., 2015; Shi et al., 2016).

Mechanistically, it is understood that TAAR1 signalling acts as a negative regulator of monoamine neurotransmission. Initial experiments with the administration of amphetamine (Lindemann et al., 2008), or MDMA (Di Cara et al., 2011), in the Taar1-KO mice showed significant increases in the striatal release of dopamine, norepinephrine, and serotonin, when compared with WT animals. These results indicated that the lack of TAAR1 expression, and signalling, resulted in an increase in the release of monoamines in the presence of amphetamine. These studies, together with electrophysiological data (see section 1.2.11), suggest that TAAR1 regulates monoamines at the neuron level via regulation of the firing rate of neurons. Lastly, when the Taar1-KO mice were crossed with the dopamine transporter knockout mouse, a model of chronic hyperdopaminergia, the DAT/TAAR1 double knockout mice had a significantly higher basal locomotor phenotype, when compared with either knockout alone, further supporting the modulatory effect of TAAR1 on dopamine signalling (Revel et al., 2011).

As described previously, TAAR1 interacts with the long isoform (postsynaptic) of the dopamine D2 receptor in vitro, and modulates some aspects of postsynaptic dopamine D2 receptor functions in vivo (Espinoza et al., 2011). Indeed, it has been found that in the striatum of the Taar1-KO

32 mice, post-synaptic dopamine D2 receptors are overexpressed, with these receptors selectively activating the -independent AKT/GSK3 signalling pathway (see section 1.2.10) (Espinoza et al., 2015b). In accordance with this finding, the Taar1-KO mice were also more sensitive to the behavioural effect of dopamine D2 receptor stimulation (Espinoza et al., 2015b). In addition, TAAR1 has been shown to modulate the activity of presynaptic dopamine D2 dopamine receptors. In dopaminergic neurons found in the VTA, stimulation of TAAR1 results in decreased dopamine D2 receptor activity, as well as the promotion of D2 receptor desensitization through an unknown mechanism (Bradaia et al., 2009; Revel et al., 2011). Similarly, dopamine D2 auto-receptor functions were also reduced in the NAc of Taar1-KO mice (Leo et al., 2014). All these studies reveal an important pre- and post-synaptic role of TAAR1 in the modulation of dopamine D2 receptor signalling.

Recently, the role of TAAR1 in modulating prefrontal cortex processes has also been reported (Espinoza et al., 2015a). Using a transgenic rat Taar1-KO model, where a Ds-Red fluorescent protein is expressed under the control of the TAAR1 promoter, TAAR1 expression was shown in layer V neurons of the prefrontal cortex. In agreement with this expression pattern in rats, Taar1- KO mice showed significant deficiency in NMDA-mediated current of layer V pyramidal neurons, as well as altered subunit composition of NMDA receptors. Although previously thought to be basally normal, behaviourally, the Taar1-KO mice presented with aberrant cognitive behaviours, indicating an impulsive and perseverative phenotype (Espinoza et al., 2015a). These data indicate that TAAR1 also plays an important role in the modulation of NMDA receptor-mediated glutamate transmission in the prefrontal cortex and in certain aspects of cognition (Espinoza et al., 2015a).

1.2.11.1 Basal Ganglia and the Regulation of Locomotor Activity

Locomotor activity is mediated in part by dopamine release in the basal ganglia (see figure 1.4 for an outline of the basal ganglia circuitry). The basal ganglia is a group of interconnected nuclei that regulates a variety of behaviours such as locomotor activity. These nuclei include the dopamine releasing neurons of the substantia nigra pars compacta (SNc); the GABA releasing neurons of the substantia nigra pars reticula (SNr), striatum (caudate and putamen), pars externa (GPe), and globus pallidus pars interna (GPi); and the glutamate releasing neurons of sub thalamic nucleus (STN) (Obeso et al., 2008). The primary center of input into the basal ganglia is the striatum, where neurons consist of mostly (95%) medium spiny neurons (MSN) (Kreitzer and

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Malenka, 2008). The MSN express either the excitatory dopamine D1 (i.e. coupled to Gαs) or inhibitory dopamine D2 (i.e. coupled to Gαi) receptor. While a single MSN expresses only one of the dopamine D1 or D2 receptors, there are a small proportion of MSN that express both the dopamine D1 and D2 receptor (Lee et al., 2004; Rashid et al., 2007; Bertran-Gonzalez, 2010). MSN provides inhibitory output by releasing GABA to the output centers of the basal ganglia, GPi/GPe. Dopamine regulates locomotor activity by the activation of two distinct pathways: the ‘direct’ and ‘indirect’ pathway. The ‘direct’ pathway follows the following nuclei in the basal ganglia: SNc -> striatum -> Gpi/SNr -> . The ‘indirect’ pathway includes the following pathway in the basal ganglia: SNc -> striatum -> Gpe -> STN -> GPi/SNr. The direct pathway involves dopamine stimulation of dopamine D1 receptors on the MSN in the striatum, which leads to the release of GABA (an inhibitory tone), which then projects to the GPi/SNr. The GPi/SNr nuclei then project GABA releasing neurons to the thalamus, the primary output controlling locomotor activity. The activation of dopamine D2 receptor expressing MSN leads to activation of the ‘indirect’ pathway. Activation of dopamine D2 receptor expressing MSN leads to GABA release, and inhibition of neurons in the GPe. The GPe innervates the STN and tonically releases GABA to the STN. Therefore, dopamine D2 receptor signalling from the striatum leads to the disinhibition of glutamate neurons of the STN that project to the GPi/SNR.

The net result of dopamine D1 receptor activation is a net reduction of inhibition of the thalamus leading to voluntary locomotion. Conversely, dopamine D2 receptor activity leads to the net inhibition of the thalamus resulting in inhibition of movements (Russo and Nestler, 2013). The delicate balance of the ‘direct’ and ‘indirect’ pathways leads to voluntary locomotion. In diseases such as Parkinson’s disease, the death of dopaminergic neurons in the SNc leads to the ablation of the ‘indirect’ pathway, causing an imbalance in the ‘direct’ and ‘indirect’ pathways, that results in the dysregulated motor symptoms that characterize Parkinson’s disease (Wichmann and DeLong, 1998; Obeso et al., 2008).

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Figure 1.4. The circuitry of the basal ganglia. The basal ganglia recieves direct input from neurons from the cortex. The basal ganglia is comprised of the dopamine releasing (green) neurons of the substantia nigra pars compacta (SNc); the GABA releasing (yellow) neurons of the substantia nigra pars reticula (SNr), striatum (caudate and putamen), globus pallidus pars externa (GPe), and globus pallidus pars interna (GPi); and the glutamate releasing neurons (blue) of sub thalamic nucleus (STN). The direct pathway follows the signalling of dopamine D1 receptors from the SNc → striatum → Gpi/SNr → thalamus. The indirect pathway follows the signalling of the dopamine D2 receptor from the SNc → striatum → GPe → STN → Gpi/SNr → thalamus.

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1.2.12 TAAR1 and Disease

1.2.12.1 TAAR1 Agonists and Disease

Since it has been shown that TAAR1 regulates dopamine transmission, research with selective TAAR1 agonists has been primarily focused on determining TAAR1 effects on the regulation of behavioural actions of drugs of abuse. As mentioned previously, TAAR1 agonists have been shown to block the behavioural effects of chronic cocaine administration. When administered systematically, in rats, TAAR1 agonists block the seeking (Pei et al., 2014), reinstatement of seeking (Liu et al., 2016), self-administration (Pei et al., 2015), behavioural sensitization (Thorn et al., 2014a), and conditioned place preference behaviours for cocaine (Thorn et al., 2014b). While these studies show the effects of systemic administration of TAAR1 agonists, the role of TAAR1 in specific brain regions of the mesocorticolimbic system were elucidated through micro injections of RO5166017 in rats. When RO5166017 was injected into the VTA and prelimbic regions of the prefrontal cortex of rats, the animals demonstrated decreases in cocaine-induced cue and drug priming. On the other hand, injection into the NAc core and shell inhibited only drug priming-induced cocaine seeking (Liu et al., 2017). These results suggested that TAAR1 has different effects on cocaine seeking behaviour in different brain regions of the mesocorticolimbic system.

Similar to cocaine, the effect of these ligands on the behavioural effects of methamphetamine have also been studied. For instance, RO5263397 was found to reduce the motivation to seek and self- administer methamphetamine, blocked relapse of methamphetamine seeking, and prevented methamphetamine-induced increase in dopamine transmission in the NAc (Pei et al., 2016). Furthermore, it was found that RO5263397 alone was not self-administered and had no effect on dopamine transmission. The authors concluded that based on RO5263397’s low abuse liability, and its effects at blocking methamphetamine based models of addiction, that Taar1-based can be potential therapies for addiction. These results are in agreement with other studies that used TAAR1 agonists, such as RO5203648, where these agonists were also found to block, or attenuate, the behavioural effects of methamphetamine (Cotter et al., 2015).

In addition to addiction studies, the treatment of schizophrenia, using TAAR1 ligands, has been the focus of the company Hoffmann-La Roche. Current are very efficacious in the treatment of the positive symptoms of schizophrenia, but are relatively poor in improving the

36 negative symptoms and cognitive deficits associated with this disease (Carpenter and Buchanan, 1994). When compared to olanzapine, an , the TAAR1 partial agonist, RO5263397, had similar efficacy in improving positive symptoms in animal models of schizophrenia. However, unlike olanzapine, TAAR1 agonists also improve the negative symptoms (i.e. sociability) and the cognitive deficits. Interestingly, RO5263397 does not have the same adverse metabolic side effects as olanzapine, and co-treatment of RO5263397 with olanzapine actually reduced its metabolic side effects (Revel et al., 2013). The authors speculated that TAAR1 agonists could be stand alone, or adjunct, therapies with current antipsychotics for the treatment of schizophrenia. Indeed, phase I trials with RO5263397 showed promise for TAAR1 being a target for pharmacotherapy. Unfortunately a small portion of the human population were found to be slow metabolizers for RO5263397, which reduced the clinical development of RO5263397 (Fowler et al., 2015).

In terms of other disease states, it was found that the administration of the extracellular dopamine metabolite 3-methoxytyramine (also a TAAR1 agonist) in a mouse model of Parkinson’s disease led to temporary, mild hyperactivity and abnormal movements that were partially mediated by TAAR1, and were independent of dopamine (Sotnikova et al., 2010). These Taar1-mediated abnormal movements may play a part in the L-DOPA-induced dyskinesia observed in human patients suffering from Parkinson’s disease. Indeed, it is known that 3-methoxytyramine levels are increased in the putamen, and urine, of Parkinson’s disease patients, a result of chronic L-DOPA administration (Siirtola et al., 1975; Muskiet et al., 1979; Rajput et al., 2004).

Lastly, a study explored the possibility that apomorphine, a non-selective dopamine D1 and D2 receptor agonist, might exert part of its behavioural actions via TAAR1 activation (Sukhanov et al., 2014). Apomorphine-induced climbing behaviour and stereotypies were reduced in Taar1-KO mice, while locomotor behaviour was not affected. Interestingly, the injection of a combination of 1) a selective TAAR1 agonist with 2) a dopamine D1 and D2 receptor selective agonist in WT mice, could reproduce a level of climbing behaviour similar to what is obtained with apomorphine (Sukhanov et al., 2014). Since apomorphine-induced climbing has been used for the screening test for new antipsychotics (Costall et al., 1978), it was suggested that other receptors besides the dopamine receptors (e.g. TAAR1), could be responsible for the behavioural effects of apomorphine. Compounds with putative antipsychotic activity identified by using this test could also have TAAR1 activity.

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1.2.12.2 TAAR1 Antagonists and Disease

In contrast to TAAR1 activation, it has been hypothesized that the antagonism of TAAR1 can be beneficial for the treatment of diseases resulting from hypodopaminergic states, such as Parkinson’s disease. Parkinson’s disease is characterized by a progressive loss of dopaminergic neurons that project from the SNc to the striatum. This loss of dopaminergic neurons leads to a decrease in dopamine release, and tone, in the (Elsworth and Roth, 1997). Dopamine input to the nigrostriatal pathway controls the direct and indirect pathways of locomotion (see section 1.2.11.1)(Alexander and Crutcher, 1990). Therefore, patients suffering from Parkinson’s disease eventually develop bradykinesia, rigidity, resting tremor, and postural imbalance due to dysregulated dopamine circuits (Lees et al., 2009). Currently, the gold standard therapy for Parkinson’s disease is dopamine replacement therapy, specifically L-DOPA supplementation. However, prolonged treatment with L-DOPA leads to a shortened and more variable therapeutic effect, which eventually leads to L-DOPA-induced dyskinesia (Iravani and Jenner, 2011). It has been postulated that trace amines could potentially mediate L-DOPA induced dyskinesia in mouse models of Parkinson’s disease (Sotnikova et al., 2010). Therefore, antagonism of TAAR1, and subsequent enhancement of dopamine transmission, has been proposed as a potentially novel avenue for the treatment of Parkinson’s disease (Pei, Asif-Malik, and Canales, 2016).

Apart from using TAAR1 antagonists as a treatment for the symptoms of Parkinson’s disease, recent evidence has shown that TAAR1 signalling could also have a role in the progression of Parkinson’s disease. It has been shown that TAAR1 agonists potentiate the degeneration of dopaminergic neurons, while also attenuating the behavioural response of L-DOPA, and glutamate neurotransmission in the striatum (Alvarsson et al., 2015). Furthermore, the dysfunction of dopamine and glutamate transmission (see section 1.2.11 for TAAR1 regulation of glutamate signalling) in the striatum is implicated in the pathophysiology, and , of Parkinson’s disease, along with the emergence of L-DOPA-induced dyskinesia (Calabresi et al., 2007; Lau and Tymianski, 2010; Gerfen and Surmeier, 2011). Indeed, it has been shown that TAAR1 could potentially modulate corticostriatal glutamate transmission in Taar1-KO mice (Espinoza et al., 2015a). Further evidence of TAAR1 regulation in the prefrontal cortex involves a study with the TAAR1 agonist, RO5256390, and binge-like eating in rats. Administration of RO5256390 in the infralimbic subregion of the medial prefrontal cortex reduced binge-like eating

38 in rats, by restoring impaired dopamine transmission that arose from obsessive food intake (Ferragud et al., 2017). Therefore, it is reasonable to propose that dopamine dysfunction can lead to aberrant TAAR1 signalling in the prefrontal cortex which could play an important role in the progression of Parkinson’s disease.

1.2.12.3 Summary of TAAR1 and Disease

With the recent discovery of selective ligands for TAAR1, the potential of TAAR1 as a target for treating neurological disorders has been explored. Due to role of TAAR1 in modulating dopamine signalling, much of the focus of targeting TAAR1 has been on treating diseases that arise from dopamine dysfunction. Indeed, TAAR1 full and partial agonists have been shown to be effective at attenuating the rewarding properties of cocaine and amphetamine. In addition, TAAR1 full and partial agonists have been shown to be effective in treating the symptoms of schizophrenia (i.e. positive, negative, and cognitive deficits) in pre-clinical models. In addition, TAAR1 antagonists could also be used to treat specific neurological disorders. For instance, it has been postulated that antagonizing TAAR1 could treat the symptoms of Parkinson’s disease (i.e. increase dopamine signalling) as well as reduce the progression of Taar1-mediated neurodegeneration in Parkinson’s disease. Because EPPTB is the only known TAAR1 antagonist, limited research has been performed with TAAR1 antagonists. The discovery of novel TAAR1 antagonists with suitable pharmacokinetic properties will be important in advancing the field of TAAR1 research.

1.3 Drug Discovery

In the early days of drug discovery, therapeutic drugs were derived mostly from natural products. Indeed, many of the early medicines used were derived from plants; examples include morphine and aspirin (Butler, 2004). GPCRs are attractive drug targets, due to their role in many pathological conditions, ranging from asthma, disease, to Parkinson’s disease.

Modern drug discovery efforts have primarily focused on the use of unbiased high throughput screening (HTS) for the identification of lead compounds. In an HTS, a single target is screened against a large chemical compound library. Once an HTS has been performed, hits are characterized, where any lead compounds are further optimized in a lead-identification program. This method, while robust and successful in discovering novel drugs for diseases, is costly and has caveats for finding hits with challenging targets (Macarron et al., 2011). The main challenges for

39 a successful HTS are two-fold. First, the target of interest must be amenable to HTS and the assay properly optimized. Secondly, access to a relevant chemical compound library that is available for screening is necessary (Macarron et al., 2011). It is argued that the advent of molecular biology, and the focus on target based screens, has led to the overall simplification of complex biology that classical tissue based techniques do not provide (Keiser et al., 2010; Gleeson et al., 2011). In addition, computational methods have been developed in order to augment current drug discovery paradigms. Recent innovations in the methodology for crystalizing the structures of GPCRs has led to an ever increasing number of solved crystal structures (Rasmussen et al., 2007; Warne et al., 2008). With the advent of more crystalized GPCR structures, computational modelling of GPCRs, and in silico screening, has become a powerful tool in the drug discovery process involving GPCRs.

1.3.1 Computational Screens of GPCRs

Currently, computational screens for GPCRs require the following steps. First, a three-dimensional crystal structure is required as a template for any models that are created. Secondly, a library of commercially available small organic molecules is necessary. Lastly, a docking algorithm that enables the sampling of ligand conformations and binding energy of small molecules in the modeled or crystal structure binding pocket (Shoichet and Kobilka, 2012). One of the initial challenges for computational screens is the availability of public databases for commercially available small molecules. However, recently, databases of over ten million commercially available compounds have been made publically available, such as the database (Irwin et al., 2012). Early docking studies on GPCRs relied on generating homology models using available GPCR crystal structures that were crystalized in the inactive state. The result of screens based on these homology models generated primarily novel antagonists and inverse agonists (Kolb et al., 2009; Carlsson et al., 2010; Katritch et al., 2010). However, with the crystallization of the nanobody and Gαs bound β2AR, it was revealed that the active conformation for a GPCR requires the interaction of the Gαs with the receptor (Rasmussen et al., 2011a; Rasmussen et al., 2011b). Comparing the active and inactive states of the β2AR revealed small changes in individual amino acids in the orthosteric binding site, where the overall volume of the binding pocket was reduced in the active state model. These subtle, but significant, changes in the orthosteric binding site allowed for more accurate in silico screens and discovery of agonists (Katritch and Abagyan, 2011). Given these recent advances in GPCR structural biology research, the use of in silico

40 screens with homology models, based on the newly crystalized structures, has been successful for the discovery of novel chemical structures for a wide variety of aminergic GPCRs, including adrenergic, dopaminergic, , muscarinic, TAAR1, and serotonergic (Carlsson et al., 2011; de Graaf et al., 2011; Kruse et al., 2013; Rodríguez et al., 2014a; Lam et al., 2015). Indeed, the strategy we employed to discover novel antagonists in this study, was based on the method of molecular docking on a TAAR1 homology model, generated based on an inverse agonist bound β2AR.

1.3.2 Generation and Optimization of a GPCR Model

In order to generate an accurate homology model, a crystalized GPCR with similar structure is required. Although the number of GPCR structures crystalized has increased, the structural information for the vast majority of drugable GPCRs is still missing. In general, there are two methods for the generation of a three-dimensional model of a receptor. First, fold recognition is based on the principle that the number of protein folds is finite. This approach is primarily used when there are no known structures with significant sequence similarity to the receptor of interest. Second, homology modelling is used when a template is available with sufficient sequence similarity. This method is based on the principle that homologous proteins have similar structures (Martí-Renom et al., 2000).

Once a model has been generated, the model is further optimized, and refined, using conformational sampling approaches, such as Monte Carlo or Molecular Dynamics sampling, followed by ligand guided receptor optimization. The primary goal of ligand guided receptor optimization is to ensure the model is able to discriminate between active compounds and structurally similar decoys (Katritch et al., 2012).

A library of compounds with ‘lead-like’ properties is screened against the binding site of the refined optimized model. Lead-like compounds are defined as compounds with molecular properties that allow for further optimization, and in general, have better qualities for use in in vitro assays (Oprea, 2002; Shoichet and Kobilka, 2012). A rule of three has been coined for compounds with lead-like properties. These include, molecular weight < 300, log P < 3, H-bond donors and acceptors < 3, and rotatable bonds <3 (Lipinski, 2004).

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When the in silico docking screen has been completed, the compounds from the screen are ranked based on their predicted binding affinities, with the top 0.1 to 0.01% ranked compounds being selected for experimental testing (Shoichet and Kobilka, 2012). In addition, visual scrutiny of the top hits is necessary before the compounds are chosen for experimental evaluation. The visual evaluation is necessary since the docking screen does not properly filter out common unfavourable features such as, ligand conformational strain, improper tautormerization, and improper protonation of ionizable groups (Tirado-Rives and Jorgensen, 2006).

1.3.2.1 Effectiveness of Computational Screens

An interesting benchmark for accuracy in the modelling of GPCRs has been the community-wide assessments, involving blind predictions, for various GPCR structures. In particular, the GPCR Dock assessments have challenged the molecular modelling community to predict the structures of specific GPCR-ligand complexes before the release of the crystal structures. GPCR Dock has been run in 2008, 2010, and 2013 for the adenosine A2A, dopamine D3/CXCR4, and 5- HT1B/2B/ receptors, respectively (Michino et al., 2009; Kufareva et al., 2011, 2014). In general, these GPCR Dock assessments have shown that having access to receptor templates with high sequence identity, as well as, having ligand data, is important to model accuracy.

During GPCR Dock 2010, an interesting result was obtained from the dopamine D3 receptor homology model. In this study, in silico screening of the dopamine D3 receptor homology model (based on the β1- and β2-adrenergic receptors) was able to provide a 23% hit rate of novel ligands with Ki values ranging from 0.2 – 3.1 μM. When the crystal structure was subsequently released, the in silico screen was redone with this new structure. The results of this new docking screen yielded similar results in hit rate (20%), and affinity, as the previous study based on the homology model (Carlsson et al., 2011). This observation confirmed that in silico screening based on a homology model, or crystal structure, yields similar success rates for identifying novel compounds; however, the compounds identified through the homology screen vs the crystal structure screen were completely different. Likewise, in other studies with the histamine H4 and the dopamine D2 receptors, high accuracy homology models were able to obtain high hit rates (between 20-30%) for novel ligands (Istyastono et al., 2011; Weiss et al., 2013). However, it has been found that the hit rate for novel ligands decreases when the model is of intermediate, or low accuracy, due to low sequence similarity with published GPCR crystal structures. Examples of

42 such homology models are the CXCR5 and adenosine A2A receptors, which obtained 4 and 9% hit rates respectively (Langmead et al., 2012; Mysinger et al., 2012). This was due to the lack of crystal structures of similar GPCRs at the time the homology models were created.

1.3.2.2 Statements of Significance

The overall goal of this project was to discover novel TAAR1 antagonists with in vivo activity, where none exists. Recent research has shown TAAR1 to be a modulator of dopamine transmission in the brain. Specifically, TAAR1 antagonism has been shown to increase the firing rate of dopaminergic neurons ex vivo. While there are many studies involving Taar1-selective agonists showing their potential for treatment of psychiatric diseases arising from hyper-dopaminergia, there has been little research on the potential role of TAAR1 antagonists in neurological disorders arising from hypo-dopaminergia, such as Parkinson’s disease. Studies with TAAR1 antagonists have been challenging, due to the existence of only one published high affinity TAAR1 antagonist, EPPTB. Furthermore, this compound has poor pharmacokinetic properties, with no published in vivo studies (Bradaia et al., 2009). Therefore, the overarching goal of this project was to discover novel TAAR1 antagonists with in vivo activity. Previously, in silico screening studies, based on TAAR1 and other aminergic GPCR homology models, have yielded success in discovering novel chemical compound scaffolds that were unknown (Carlsson et al., 2010, 2011; Cichero et al., 2014). Therefore, using a TAAR1 homology model we performed an in silico screen with both fragment-like and lead-like compound libraries. The ultimate goal for using this method was the discovery of novel TAAR1 antagonists that could be tested in vivo.

1.3.3 Hypothesis

The hypothesis of this study was that TAAR1 represents a novel target for the treatment of neurological disorders and TAAR1 antagonists represent potential new treatments for Parkinson’s disease by increasing dopamine transmission in the striatum.

This study can be summarized in two independent aims.

Aim 1: Discover novel antagonists for TAAR1 using an in silico screen of a TAAR1 homology model and characterize these ligands using TAAR1 activity assay.

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Aim 2: Assess the effects of novel TAAR1 antagonists on dopamine transmission in vivo by measuring locomotor activity.

1.3.4 Rationale for Hypothesis

Our knowledge of the role of TAAR1 in Parkinson’s disease is limited compared with other diseases, such as schizophrenia. However, one study has shown that TAAR1 is important for the development, and progression, of Parkinson’s disease in animal models (see section 1.2.12.2.) (Alvarsson et al., 2015). That study can be summarized in four parts. 1) Taar1-KO mice showed a reduced loss in dopaminergic markers in 6-OH-Dopamine (6-OHDA) lesioned mice when compared to WT. 2) WT mice treated with a Taar1-selective agonist showed an increase in the loss of dopaminergic markers. 3) Taar1-KO mice had an enhanced response to L-DOPA in 6- OHDA lesioned mice. 4) TAAR1 agonists reduced evoked firing of glutamate neurons. These results show that TAAR1 is important in the progression of Parkinson’s disease, and therefore could be a potential target for the management of the disease. This research led us to propose two research aims:

Aim 1: Discover novel antagonists for TAAR1 through an in silico screen of a TAAR1 homology model.

Previous attempts at discovering novel TAAR1 antagonists, using computational modelling, has yielded one low potency antagonist (Cichero et al., 2014). Therefore, we hypothesized that the generation of a new TAAR1 homology model, based on an inverse agonist bound β2AR, could yield novel TAAR1 antagonists from an in silico screen. The compounds with the highest predicted affinity from the in silico screen were tested in vitro using a BRET cAMP EPAC biosensor as described previously (Barak et al., 2008). Since the TAAR1 homology model was optimized, and enriched, for its ability to bind known TAAR1 ligands (which are mostly agonists), it was expected that the bulk of the hits identified would be agonists. However, since the template for our homology was the inverse agonist bound β2AR, it was also expected that antagonists could also be discovered using this homology model.

Once TAAR1 antagonists were found, the ability for the compounds to potentially cross the blood brain barrier was assessed, based on the compounds’ predicted physical properties, such as the lipid-water coefficient (logP) values. Once a compound with suitable predicted physical properties

44 was identified from the list of hits, the TAAR1 antagonist was tested in vivo. While there have not been any TAAR1 antagonist studies done in vivo, the framework for these experiments were based off of the known responses observed in Taar1-KO mice to psychostimulants. We hypothesized that a TAAR1 antagonist would replicate some of the behavioural responses seen in Taar1-KO. This therefore leads into aim 2:

Aim 2: Assess the effects of novel TAAR1 antagonists on dopamine transmission in vivo by measuring locomotor activity.

It has been shown that the Taar1-KO mice are more sensitive to psychostimulant-mediated locomotor activity (see section 1.2.11). Mechanistically, it is thought that a lack of TAAR1 signalling leads to an increase in the firing rate of dopaminergic neurons, resulting in an increase in dopamine release (see section 1.2.10). While a basal increase of dopamine levels did not alter the basal locomotor activity of the Taar1-KO mice, the administration of psychostimulants, such as cocaine or amphetamine, led to a significant increase in dopamine release, resulting in the potentiation of locomotor activity in Taar1-KO mice compared to WT animals. Therefore, we hypothesized that TAAR1 antagonists should potentiate amphetamine- and cocaine-mediated locomotor activity, similar to what was observed in Taar1-KO mice. While it is possible that the Taar1-KO mice have fundamental changes to their neurochemistry that result in these animals being more sensitive to psychostimulants, having access to the Taar1-KO mice should serve as a proper control group for our studies. Since TAAR1 antagonists have been shown to enhance the firing rate of dopaminergic neurons, treatment with psychostimulants would then result in increased signalling in the ‘direct’ pathway, leading to increased locomotor activity (see section 1.2.11.1). Indeed, if TAAR1 antagonists potentiate cocaine- and amphetamine-mediated locomotor activity through TAAR1, the same behavioural experiments performed on the Taar1- KO mice should result in no differences between antagonist and saline treated animals. For these in vivo experiments, locomotor activity was the main behavioural assay used.

In conclusion, this study aimed to identify and characterize TAAR1 antagonists, with a potential for in vivo effects. TAAR1 signalling remains a tantalizing target for the treatment of neurological diseases arising from dopamine dysfunction. With ever-improving methods for the generation of homology models, it was hoped that this method would accurately model the orthosteric binding site for TAAR1, leading to accurate prediction of novel ligands, including novel antagonists.

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2 Methods 2.1 Generation of the TAAR1 Homology Model and Molecular Docking

The sections, section 2.1 and 2.1.1, were completed by collaborator Dr. Jens Carlsson. The following method was adapted from previously published work (Lam et al., 2015)

A homology model of TAAR1 was generated based on a crystal structure of the β2AR (PDB accession code: 2RH1 [Cherezov et al., 2007]) and a sequence alignment generated with PROMALS3D (Pei et al., 2008) using MODELLER9v8 (Sali and Blundell, 1993). Additional side chain restraints were put on binding site residues to improve ligand recognition, as previously described.(Rodríguez et al., 2014b) A total of 1,000 models were generated and ranked by their DOPE scores (Shen and Sali, 2006). The 200 models with the best structure quality scores were further evaluated using molecular docking screens using the program DOCK3.6 (Lorber and Shoichet, 2005; Irwin et al., 2009; Mysinger and Shoichet, 2010). A set of 63 known TAAR1 ligands (agonists) from the ChEMBL09 database (Gaulton et al., 2012), together with 160,000 fragment-like molecules from the ZINC database (Irwin et al., 2012), were docked to each model. The flexible-ligand sampling algorithm in DOCK3.6 superimposes atoms of the docked molecule onto binding site matching spheres, which represent favourable positions for ligand atoms. Forty- five matching spheres based on the co-crystallized ligand of the template structure and docking poses of known ligands were used. The degree of ligand sampling is determined by the bin size, bin size overlap and distance tolerance, which were set to 0.4 Å, 0.3 Å, and 1.5 Å, respectively, for both the matching spheres and the docked molecules. The receptor-ligand binding energy was calculated as the sum of the electrostatic and van der Waals interaction energies, corrected for ligand desolvation. These three energy terms were estimated from pre-calculated grids. For the top scoring conformation of each molecule, 50 steps of rigid-body energy minimization were also carried out. The enrichment of known TAAR1 ligands by each homology model was quantified using the adjusted LogAUC metric (Mysinger and Shoichet, 2010). The receptor model with the strongest enrichment of known ligands was further refined manually by modifying the side chain rotamers of binding site residues to match those observed in adrenergic receptor crystal structures (Cherezov et al., 2007; Warne et al., 2008). In addition, the Protein Local Optimization Program was used to optimize the second extracellular loop two with the rest of the receptor held rigid

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(Jacobson et al., 2002, 2004). The ZINC fragment- and lead-like libraries of commercially available compounds (0.357 and 2.7 million unique molecules, respectively) (Irwin et al., 2012) were screened against the orthosteric site of the resulting TAAR1 model. All docked compounds were prepared for docking using the ZINC database protocol (Irwin et al., 2012). Prior to compound selection, molecules with high internal energy motifs were removed automatically, as described previously (Carlsson et al., 2011).

2.1.1 2D Molecular Similarity Calculations

Human TAAR1 ligands were extracted from ChEMBL19 database (Gaulton et al., 2012). This compound set was used to assess the novelty of the discovered ligands by calculating the maximum

Tanimoto coefficient (Tc) to all TAAR1 ligands using 2D ECFP4 fingerprints as implemented in the ScreenMD software from ChemAxon.

2.2 Reagents, Cells, and Drugs

Cell culture reagents and buffers were obtained from Sigma-Aldrich (St. Louis, MO) and Life Technologies (Carlsbad, CA). HEK293T (CRL-3216) and HEK293 (CRL-1573) cells were purchased from American Type Culture Collection (Hopkinton, USA). bPEA was purchased from Sigma-Aldrich (St. Louis, MO). Poly-D- was purchased from Sigma-Aldrich and prepared by dissolving the powder to a concentration of 1 mg/mL in ddH2O. Polyethylenimine (PEI) was purchased from Polyscience Inc (Warminster, PA) and dissolved to a concentration of 1mg/mL. Aliquots of PEI were stored at -80 ˚C. Cocaine hydrochloride (Medisca, New York, NY; Batch: 0723-06) and amphetamine (Tocris Bioscience, Bristol, United Kingdom; Batch: 4A/137502) were handled and stored according to regulations set by Health Canada. All compounds from the molecular docking study were obtained from commercial sources: Enamine Ltd (Kiev, Ukraine), Chembridge (San Diego, USA), Tocris Bioscience (Bristol, United Kingdom), Toronto Research Chemicals (Toronto, Canada), and Asinex (Winston-Salem, USA). Compounds were dissolved in DMSO at a concentration of 100 mM and stored at -20˚C. Coelenterazine h was purchased from NanoLight Technologies (Pinetop, AZ) and dissolved at a concentration of 2mM in ethanol. Coelenterazine h is sensitive to humidity and light and was stored at -20˚C away from light sources.

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2.3 Plasmids

2.3.1 Human β2TAAR1

Plasmids containing cDNA of human β2TAAR1 was the same construct as published previously (Barak et al., 2008). Briefly, the full-length human TAAR1 cDNA was cloned with the following additions at the 5’ of the start codon of TAAR1: triple-HA epitope and first nine amino acids of the β2AR (β2N9). This modified 3HA-β2N9–TAAR1 sequence was then cloned into the pcDNA3 plasmid.

2.3.2 BRET EPAC cAMP Biosensor

The Exchange Proteins directly Activated by cAMP (EPAC) BRET biosensor was the same construct as published previously (Barak et al., 2008). The BRET EPAC cAMP biosensor contains a truncated EPAC (residues 149-881), flanked by Renilla reniformis luciferase and citrine fluorescent protein on the 5’ and 3’ ends respectively. This construct was generated by removing the cyan fluorescent protein moiety of ICUE2(Violin et al., 2008) and replaced with Renilla reniformis luciferase (Barak et al., 2008).

2.3.3 Human HA-DAT

The human HA-DAT construct was provided by Dr. Alexander Sorkin (Sorkina et al., 2006). The backbone of this construct is the peYFP-c1 vector, where the YFP is located on the N-terminus of DAT. In addition, an HA epitope was added onto the second extracellular loop replacing residues 193-203.

2.4 Cell Culture and Transfections 2.4.1 Cell Transfections

HEK293T and HEK293 cells were cultured in Dulbecco’s Modified Eagle Serum (DMEM), supplemented with 10% fetal bovine serum (Sigma-Aldrich), and maintained at 37 ˚C with 5%

CO2 in a humidified atmosphere. Cells were passaged 24 hours prior to transfection at 50% confluency (~2 x 106 cells in a 10 cm plate). Transfections were carried out using the PEI method as described previously(Ehrhardt et al., 2006; Lam et al., 2013; Beerepoot et al., 2016). PEI and plasmid DNA (3µl:1µg PEI:DNA ratio) were added into separate tubes (tube 1:PEI, tube 2:DNA) followed by 200 µL of DMEM into each tube, containing no supplements. Tubes were allowed to

48 incubate for 5 minutes before the two tubes were combined (PEI with DNA). The PEI:DNA mixture was then further incubated for 30 minutes at room temperature and subsequently added drop wise to a 10 cm plate containing HEK293T or HEK293 cells at 50% confluency. For transient transfections, cells (HEK293T) were seeded in 96 wells plates 6 hours post transfection. For stable cell line generation (HEK293) for the HA-DAT construct, 24 hours after transfection, media was replaced with selection media containing G418 (500 µg/mL, Bioshop, Burlington, Canada). Clonal cell lines were generated by picking individual colonies ~2 weeks post transfection. Expression was confirmed by western blot and fluorescence microscopy.

2.5 BRET Assays 2.5.1 TAAR1 Signalling Assay

HEK293T cells were transiently transfected with the EPAC biosensor (1µg) and the β2TAAR1 (10µg) plasmids. 6 hours post transfection, cells were seeded on to poly-D-lysine coated white clear bottom 96 well plates (Corning Catalog #: 3610) at a density of 1 x 105 cells per well. Assays were conducted 24 hours post transfection.

2.5.2 Dopamine D2-β-arrestin Recruitment Assay

HEK293T cells were transiently transfected with 3µg of D2-Rluc and 2µg of YFP-βarrestin-YFP plasmids. Twenty-four hours post transfection, cells were seeded on to poly-D-lysine coated white clear bottom 96 well plates (Corning Catalog #: 3610) at a density of 1 x 105 cells per well. Assays were carried out 48 hours post transfection.

2.5.3 BRET Assay Protocol

BRET assays were carried out 24 or 48 hours following transfection (see Section 2.5.1 and 2.5.2). First, the wells were aspirated and washed twice with 100 µL PBS (Containing Mg2+ and Ca2+). BRET assays were all carried out at a final volume of 100 µL per well, and were performed at room temperature. For agonist testing (both for TAAR1 signalling and D2 βarrestin recruitment), the wells were filled with 80 µL of PBS, followed by the addition of 10 µL of 50 µM coelenterazine-h (5 µM final concentration). After an incubation of 10 minutes, 10 µL of vehicle or agonist were added, and the plate was placed into the Mithras LB940 instrument (Berthold Technologies, Bad Wildbad, Germany). For antagonist testing (TAAR1 signalling only), the wells were filled with 70 µL of PBS, followed by the addition of 10 µL of vehicle or antagonist.

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Following a 30 minute incubation at 37 °C, 10 µL of 50 µM coelenterazine-h (5 µM final concentration) was added. After a 10 minute incubation, 10 µL of vehicle or bPEA were added and the plate was placed into the Mithras LB940 instrument, as described above. The BRET signal was calculated via the ratio of light emitted at 540 nm to the light emitted at 480 nm. Note: for data analyses, the ratios were inverted due to the fact that the EPAC biosensor BRET ratios decrease with increasing concentrations of cAMP (Barak et al., 2008), therefore the ratios were inversed for the purposes of clarity.

2.6 Fluorescent Dopamine Uptake Assay

Fluorescent dopamine uptake assay kits were purchased from Molecular Devices (Sunnyvale, CA; catalog #: R6138). Stable cells expressing human HA-DAT were seeded on poly-D-lysine treated, black clear-bottom 96-well plates (Corning Catalog #: 3603) at a density of 1 x105 cells/well, and incubated for 24 hours prior to the start of the uptake experiment. The media was removed and replaced with 80µL of assay buffer (20 mM HEPES, 1x HBSS, pH 7.4), followed by 10 µL of either 2x concentrated compound 22, 10 µL 2x concentrated cocaine, or vehicle solutions previously dissolved in assay buffer. The plates were then incubated for 30 minutes at 37 °C. Following incubation, 100 µL of dye solution was added and fluorescence intensity was measured for 30 minutes at 37 °C using the SpectraMax M3 (Molecular Devices, excitation: 440 nm, emission: 520 nm). The rate of reaction (slope of the curve in the linear range) was taken as the readout for the assay.

2.7 Animal Studies 2.7.1 Housing

All animals were housed in the Division of Comparative Medicine at the University of Toronto. Procedures were conducted in accordance with the Canadian Council for Animal Care and the University of Toronto Faculty of Medicine and Pharmacy Animal Care Committee. Mice were housed 1-4 per cage with 12 hour light/dark cycles (7:00-19:00), with ad libitum access to food (Teklad 2018, Envigo, IN, USA) and water.

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2.7.2 Generation of Experimental Mice

The Taarl-/- (Taar1-KO) were obtained from Lundbeck (Wolinsky et al., 2007). Briefly, the Taar1- KO mice were generated using targeted homologous recombination of the 3.6 kb Taar1 gene with a neo cassette (Wolinsky et al., 2007). Linearized targeting vectors were electroporated into W9.5 ES cells (129S1/Sv background) and selected for with G418. One positive clone was microinjected into blastocyst stage embryos from C57BL/6J donors. The subsequent heterozygous Taar1-KO mice were obtained from crossing male chimeras with C57BL/6J females, resulting in a mixed background C57BL/6J x 129S1/Sv heterozygous Taar1-KO mice. All WT and Taar1-KO mice used for experiments were generated from Taar1-KO heterozygous mice.

2.7.3 Behavioural Experiments

Experimentally naïve mice, of at least 12 weeks of age, were used for all behavioural experiments. Mice were randomly assigned to treatment or control groups, with balanced sex in both groups.

2.7.3.1 Locomotor Activity

Locomotor activity was assessed using the automated locomotor analysis monitors (Omnitech Electronics, Columbus, OH). Mice were first weighed, and then placed into the plexiglass chamber (20 cm x 20 cm x 20 cm) and allowed to habituate for 30 minutes. Following habitation, the mice were then removed from the behavioural chamber and injected with drug (see below for administration) or vehicle, and were immediately returned to the locomotor chamber. Locomotor activity was then measured for 1 hour post injection in 5 minute increments, where total distance was determined as distance traveled over a 1 hour period. After the conclusion of the locomotor run, the animals were euthanized by cervical dislocation.

2.7.3.2 Drug Administration

In all studies, compound 22 was co-injected with saline, cocaine or amphetamine. All drug treatments were freshly prepared on the day of the experiment and injected i.p. at 0.1 mL of solution per 10g of mass of mouse. Cocaine hydrochloride was dissolved in 0.9% NaCl at a concentration of 1 mg/mL. Amphetamine was dissolved in 0.9% NaCl at a concentration of 0.2 mg/mL. Compound 22 was dissolved in the cocaine or amphetamine solution to the correct dose for the experiment.

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2.8 Statistical Analysis

Data analyses were performed with Graphpad Prism 5.01 (Graphpadsoftware inc). Linear regression analysis was used to quantify fluorescent DAT uptake activity. Dose response curves were fitted with non-linear curve fitting using the following equation:

Y = Ymin + (Ymax – Ymin) / (1 + 10[(pEC50 – logX ) * Hill Slope])

Y represents % response, with Ymin and Ymax being the minimum and maximum response respectively. pEC50 was defined as the negative log of the molar concentration to yield % maximal response, with logX defined as the molar concentration for response Y. Hill slope represents the degree of the Hill slope within the linear portion of the sigmoidal graph.

Two-tailed Student’s t tests or one-way ANOVA analysis with Dunnet post-hoc correction was used where appropriate to determine the differences between data sets.

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3 Results 3.1 TAAR1 Homology Model and in silico Screen

The TAAR1 homology models were generated based on the β2AR (PDB accession code: 2RH1). To refine the model to a TAAR1 context, 63 known TAAR1 agonists and 161,000 commercially available decoys were used. The structure with the best ability to identify known ligands, with an enrichment factor of 30-fold better than random selection in the top 1% of the ranked database, was selected and this model was taken forward for prospective. The predicted binding modes of the TAAR1 agonist bPEA were anchored in the binding site by a salt bridge with residue Asp1033.32 and formed stacking interactions with residues Phe2676.51 and Phe2686.52.

Two molecular docking screens were carried out against this optimized TAAR1 homology model. The first screen consisted of 357,000 fragment-like molecules (molecular weight = <200Da) that were docked in the orthosteric binding site. The second screen involved 2.7 million commercially available lead-like compounds (molecular weight = 200-500 Da) and were docked in the orthosteric binding site of the same TAAR1 homology model. Thousands of orientations for each docked molecule were generated and the complementarity of each molecule to the receptor surface was evaluated using a physics-based scoring function. The top 750 molecules, from each of the two screens previously mentioned, were inspected visually. This corresponded to 0.2% and 0.03% of the fragment- and lead-like libraries, respectively. Each molecule was evaluated based on novelty, physical properties, commercial availability, and energy terms that are not included in the docking scoring function (see section 2.1.1). A set of 42 molecules was selected for experimental evaluation, of which 21 originated from the fragment-like library and 21 from the lead-like library. All compounds were predicted to form a salt bridge with Asp1033.32 and extended towards TM helix 5 with an aromatic moiety (Figure 3.1A).

3.2 In vitro Evaluation of predicted ligands

Of the top ranked ligands, 42 were purchased from commercial vendors (Compounds 1-42, Table 3.1). Note, these 42 compounds do not correspond with the top 42 ligands with the highest predicted affinity, because some of the compounds were not commercially available at the time. All 42 ligands were assayed for TAAR1 activation to determine agonists, as well as the blocking of bPEA mediated TAAR1 signalling to determine potential antagonist activity.

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Using HEK293T cells that transiently express β2TAAR1 and the cAMP EPAC biosensor, each compound was initially assayed at a single-dose concentration of 100 M, with a hit cut-off set at the 95% confidence interval of the negative and positive controls for the agonist and antagonist screens, respectively. Based on this exclusion criteria, this initial screen identified nine potential TAAR1 agonists (compounds 6, 8, 11, 14, 15, 16, 25, 37, and 41; Figure 3.2A) and eight potential antagonists (compounds 2, 9, 16, 22, 24, 35, 38, and 39; Figure 3.2B. To assess the potencies of these identified compounds, secondary follow-up dose-response experiments were carried out on the identified agonist and antagonist hits. The overall hit rate for these compounds was 38%. The hit rate for the lead-like and fragments were 5% and 33% respectively.

3.2.1 Characterization of Agonist Hits

Dose response experiments with the initial agonist hits, yielded compounds 8, 16, and 25 with

EC50 values of 18.1 ± 5.9, 1.23 ± 0.9, and 51.6 ± 19.3 μM respectively, with maximal responses compared to bPEA of 55.8%, 24%, and 67.5%, respectively (Figure 3.3, Table 3.2). These maximal responses of compounds 8, 16, and 25 indicated that these compounds were partial agonists. The remaining six compounds (6, 11, 14, 15, 37, and 41) also activated TAAR1, and achieved maximal responses between 43.7 and 74.6% of the maximal response obtained with bPEA at 100 M; however, their EC50 values were too high to be precisely determined (Figure 3.4, Table 3.3). In addition, the nine selected agonists (6, 8, 11, 14, 15, 16, 25, 37, and 41) were also screened against cells not expressing TAAR1. None of these compounds caused an increase in cAMP in these cells, confirming that they are TAAR1 selective ligands (Figure 3.5). The novelty of the discovered ligands was also assessed by calculating the Tc, in which the Tc values for the nine agonists ranged from 0.23 to 0.61. Four agonists (6, 8, 11, 37) had Tc values < 0.3, while compound 8, was dissimilar to all previously reported TAAR1 ligands (Tc = 0.25) (Table 3.2 and

Table 3.3). Interestingly, compound 16 had a high Tc value (0.61) due to its similarity to a known TAAR1 agonist, Gunabenz. The proposed binding mode of compound 8 and 16 in the TAAR1 model was predicted to occupy the same part of the orthosteric site as bPEA (Figure 3.1C-D).

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Figure 3.1. Binding poses of TAAR1 ligands in the orthosteric binding site. (A) Homology model of TAAR1 and predicted binding poses of (B) bPEA, (C) compound 8, (D) compound 16, (E) compound 9, and (F) compound 22 in the orthostertic binding site of the TAAR1 homology model. The receptor is shown in white cartoon. The ligands and key residues are depicted in sticks. Key interactions are shown as black dashed lines. Figure adapted from(Lam et al., 2015)

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Table 3.1. Chemical structures of the purchased compounds 1-42. Table adapted from (Lam et al., 2015)

1 15 29 Frag Frag Lead

2 16 30 Frag Frag Lead

3 17 31 Frag Lead Lead

4 18 32 Frag Lead Lead

5 19 33 Frag Lead Lead

6 20 34 Frag Lead Frag

7 21 35 Frag Lead Frag

8 22 36 Frag Lead Frag

9 23 37 Frag Lead Lead

10 24 38 Frag Lead Lead

11 25 39 Frag Lead Lead

12 26 40 Frag Lead Lead

13 27 41 Frag Lead Frag

14 28 42 Frag Lead Frag

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Six of the tested agonists were of fragment-size, including two of the most potent compounds (8 and 16), while the remaining three agonists (e.g. compound 25) originated from the lead-like library. Since compound 8 and 16 were from the fragment library, their small size makes the compounds amenable to modifications via medicinal chemistry. Analogues of compound 8 and 16 were purchased and assessed for any improvement in TAAR1 potency or activation. In total, ten commercially available analogues of compounds 8 (compounds 8a-e) and 16 (compounds 16a-e) (five analogues for each compound) were evaluated.

3.2.1.1 Characterization of Compound 8 Analogues

All five analogues of compound 8, showed some activation of TAAR1 at a concentration of 100 M, while compound 8b had similar potency and efficacy as the parent compound 8 (Table 3.4, Figure 3.6). None of the analogues exhibited improved the potency or efficacy over the parent compound 8. Lastly, compounds 8a-e were tested in cells that do not express TAAR1 (figure 3.7). Compounds 8b-e did not show any increase in cAMP signal, indicating that these compounds also did not activate any endogenous receptors expressed by HEK293T cells. However, compound 8a showed minor enhancement of the cAMP signal, resulting in an EC50 = 0.8 nM, and a maximal response of 15% of isoproterenol activation of β2AR receptors. These results indicate that compound 8a may be a high affinity partial agonist for an endogenous GαS coupled receptor expressed in HEK293T cells. In conclusion, the five analogues of compound 8 did not have improved potency or efficacy compared with compound 8.

3.2.1.2 Characterization of Compound 16 Analogues

Two analogues of compound 16 (16a and 16b) showed an improvement in TAAR1 potency and activation compared with the original compound 16 (Table 3.5, Figure 3.8). Of the three remaining analogues (16c-e), only compound 16c displayed significant activation of TAAR1 (75%), but had an EC50 value greater than 100M (figure 3.8). None of the analogues of compounds 16 (16a-e) showed any enhancement of cAMP signal in cells that do not express TAAR1, indicating that none of these compounds activated any endogenous receptors expressed in HEK293T cells (Figure 3.9). These results confirm that the activity of compounds 16a and 16b were, in fact, TAAR1 selective. In conclusion, two of the five analogues tested (16a and 16b) were able to improve both the potency and efficacy of compound 16. These results indicated that compound 16 was amendable to chemical modification to potentially improve its potency, selectivity, and efficacy for TAAR1.

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Figure 3.2. Identification of TAAR1 agonists and antagonists using a BRET EPAC cAMP biosensor. (A) Agonist identification, where bpea is used as a full agonist (positive control). All compounds were assayed at 100 µM. Hits are represented in black squares (Compounds 6, 8, 11, 14, 15, 25, 37, and 41). (B) Antagonist identification through the blockade of bPEA signalling on TAAR1. The compounds (100 μM) were added 30 minutes prior to the addition of the full agonist bPEA (0.3 μM). Inhibition of bPEA is indicative of antagonism. Hits are represented with black squares (compounds 2, 9, 16, 22, 24, 35, 38 and 39). Dotted red line indicates the 95% confidence interval for the relevant controls, which were used to set hit cut-offs. Figure adapted from (Lam et al., 2015)

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Figure 3.3. Dose response curves for the three most potent of the discovered agonists. Dose response curves were generated for agonists by the addition of a range of doses (0.8 – 100 µM) to HEK293T cells transiently expressing both EPAC and β2-TAAR1. Compounds 8 (A), 16 (B), and 25 (C) were compared to the TAAR1 agonist bpea (D) with EC50 values of 18, 1.0, and 52 μM respectively. Error bars represent standard error of mean at N=3. Figure adapted from (Lam et al., 2015)

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Table 3.2. Functional data for agonists discovered by the docking screen against the TAAR1 homology model. Table adapted from (Lam et al., 2015)

EC50 (M) Most similar Cmpd (% activation c 2D structure known TAAR1 Tc (frag/lead)a of bpea) ligandb

0.11 ± 0.03 bPEA 1.00 (100%) 8 18.1 ± 5.9 0.25 (frag) (55.8%)

16 1.23 ± 0.9 0.61 (frag) (24.0%)

25 51.6 ± 19.3 0.43 (lead) (67.5%) a Compound from the fragment- (frag) or lead-like screening library. b Most similar TAAR1 ligand in the ChEMBL19 database. c Tanimoto coefficient, calculated with ECFP4 fingerprints.

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Figure 3.4. Dose response curves for discovered agonists. Dose response curves were generated for agonists by the addition of a range of doses (0.8 – 100 µM) to HEK293T cells transiently expressing both EPAC and β2-TAAR1. Compounds 6, 8, 11, 15, 16, 25, 37, and 41 were tested. Error bars represent standard error of mean at N=3. Figure adapted from(Lam et al., 2015)

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Table 3.3. Functional data for weak agonists discovered by the docking screen against the TAAR1 homology model (EC50 > 100 μM). Table adapted from (Lam et al., 2015)

% activation Most similar Cmpd c 2D structure of bpea known TAAR1 Tc (frag/lead)a (10 µM) ligandb

6 43.7% 0.29 (frag)

11 58.3% 0.23 (frag)

14 74.6% 0.55 (frag)

15 62.0% 0.40 (frag)

37 54.7% 0.26 (lead)

41 46.1% 0.57 (frag) a Compound from the fragment- (frag) or lead-like screening library. b Most similar TAAR1 ligand in the ChEMBL19 database. c Tanimoto coefficient, calculated with ECFP4 fingerprints.

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Figure 3.5. Effect of discovered agonist on cells not expressing TAAR1. HEK293 cells stably expressing EPAC were tested with agonists, bPEA, and the β2AR full agonist isoproterenol (red). Compounds 6, 8, 11, 14, 15, 16, 25, 37, and 41 were tested at doses from 1 pM – 100 µM. Error bars represent standard error of mean at N=3. Figure adapted from (Lam et al., 2015)

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Figure 3.6. Dose response curves for analogues of compound 8. Dose response curves were generated for the analogues by the addition of a range of doses (0.8 – 100 µM for compound 8a- d, 1nM - 100 µM for bPEA) to HEK293T cells transiently expressing both EPAC and β2-TAAR1. Compounds 8 and analogues 8a-e were tested. Error bars represent standard error of mean at N=3. Figure adapted from (Lam et al., 2015)

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Table 3.4. Functional data for five analogues of compound 8. Table adapted from (Lam et al., 2015)

EC50 (M) (% activation cmpd 2D structure of bpea)

18.1 ± 5.9 8 (55.8%)

>100 8a (22.1%)

12.1 ± 22 8b (43.4)

>100 8c (42.9%)

>100 8d (38.4%)

>100 8e (21.6%)

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Figure 3.7. Dose response curves for analogues of compound 8 on cells that do not express TAAR1. HEK293 cells stably expressing EPAC were tested with compounds 8a-e (doses: 0.8 – 100 µM) as well as the β2AR full agonist isoproterenol (doses: 0.1 pM – 1.0 µM) as a positive control. Error bars represent standard error of mean at N=3. Figure adapted from(Lam et al., 2015)

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Figure 3.8. Dose responses curves for analogues of compound 16. Dose response curves were generated for the analogues by the addition of a range of doses (0.8 – 100 µM for compound 8a- d, 1nM - 100 µM for bPEA) to HEK293T cells transiently expressing both EPAC and β2-TAAR1. Compounds 16 and analogues 16a-e were tested. Error bars represent standard error of mean at N=3. Figure adapted from (Lam et al., 2015)

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Table 3.5. Functional data for five analogues of compound 16. Table adapted from (Lam et al., 2015)

EC50 (M) (% activation cmpd 2D structure of bpea)

1.23 ± 0.9 16 (24.0%)

0.09 ± 0.02 16a (35.5%)

0.17 ± 0.06 16b (85.5%)

>100 16c (75.0%)

>100 16d (6.9%)

>100 16e (-5.4%)

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Figure 3.9. Dose response curves for analogues of compound 16 on cells that do not express TAAR1. HEK293 cells stably expressing EPAC were tested with compounds 16 a-e (doses: 0.8 – 100 µM) as well as the β2AR full agonist isoproterenol (doses: 0.1 pM – 1.0 µM) as a positive control. Error bars represent standard error of mean at N=3.

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3.2.2 Characterization of Antagonist Hits

Of the eight initial antagonist hits tested, four of these compounds inhibited bPEA induced TAAR1 signalling (compounds 9, 16, 22, and 24) (Table 3.6, Figure 3.10). These four compounds inhibited bPEA induced TAAR1 signalling at the highest concentrations tested (100 µM). Among these compounds, compounds 9 and 22 displayed the greatest inhibition of TAAR1 signalling at 100 M. Conversely, compounds 16 and 24 were less efficacious and both reduced the activity of bPEA to a similar extent. Of the remaining compounds, neither compounds 2 and 38 showed antagonist activity when re-tested and were considered false positives. Compounds 35 and 39 were considered false positives due to their insolubility at the highest concentrations used. As with the agonist hits, the novelty of the discovered ligands was assessed by calculating Tc values. The Tc values for the four antagonists ranged from 0.21 to 0.61 (Table 3.6). Compound 22 (Tc = 0.51) had similarities to a previous hit from an unpublished assay deposited into PubChem following the completion of our screen, whereas compound 9 represented a novel scaffold for TAAR1 (Tc = 0.36). Compounds 9 and 16 originated from the screen of fragment-like compounds whereas compound 22 and 24 were from the lead-like library. The predicted binding modes of compounds 9, 16, and 22 are shown in (Figure 3.1E-F).

3.2.2.1 Characterization of Compound 16 Analogues for Antagonist Activity

Since compound 16 showed up in both the agonist and antagonist screens, the same analogues (16 a-e) tested for improvement in agonist potency and efficacy were also tested for their ability to block bPEA mediated signalling. Since compounds 16a and 16b were previously reported to be TAAR1 agonists, these compounds were not tested for their ability to antagonize TAAR1. The other 3 analogues (16c-e) tested, had similar dose response curves as compounds 16 (Figure 3.11). Since the drug responses were not saturated at the highest concentrations tested, dose response curves could not accurately determine IC50 values. Lastly, compound 16d showed a modest leftward shift of the dose response curve, indicating higher inhibition of TAAR1 signalling at the highest dose. This higher inhibitory activity was not statistically significant (p=0.27). In conclusion, none of the analogues of compound 16 displayed improved potency or efficacy at antagonizing TAAR1 signalling.

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Figure 3.10. Dose response curves for potential TAAR antagonists. Dose response curves for the antagonists were generated by incubating HEK293T cells transiently expressing EPAC and β2- TAAR1 for 30 minutes and a subsequent addition of 100 nM bPEA to each well. Compounds 2, 9, 16, 22, 24, 35, 28 and 39 were tested (doses: 0.8 – 100 µM). Error bars represent standard error of mean at N=3. Figure adapted from (Lam et al., 2015)

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Table 3.6. Potential antagonists discovered by the docking screen against the TAAR1 homology model. Table adapted from (Lam et al., 2015)

Cmpd Most similar known c 2D structure Tc (frag/lead)a TAAR1 ligandb 9 0.36 (frag)

16 0.61 (frag)

22 0.51 (lead)

24 0.21 (lead) a Compound from the fragment- (frag) or lead-like screening library. b Most similar TAAR1 ligand in the ChEMBL19 database. c Tanimoto coefficient, calculated with ECFP4 fingerprints.

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Figure 3.11. Dose response curves for analogues of compound 16 on inhibiting TAAR1 signalling. Dose response curves for compounds 16, 16c, 16d, and 16e (doses: 0.8 – 100 µM) were generated by incubating HEK293T cells transiently expressing EPAC and β2-TAAR1 for 30 minutes and a subsequent addition of 100 nM bPEA to each well. Error bars represent standard error of mean at N=3.

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3.3 In vivo Characterization of Compound 22 3.3.1 Chemical Properties of Compound 9, 16, 22, and 24

While the molecular docking screen yielded potentially low potency antagonists, these hits were assessed for their potential suitability for use in vivo. The physical properties of the antagonist hits (compound 9, 16, 22, and 24) were estimated (Table 3.7). These four compounds shared similar chemical properties, with the largest differences seen in the liquid water partition coefficient (logP) and topological polar solvent area (tPSA). Based on these predicted values, compound 22 and 24 had the most favourable logP at 3.30 and 2.98, respectively, whereas compound 9 and 16 had logP values of 1.95 and 1.18, respectively. Therefore, compound 22 and 24 had the most ideal predicted chemical properties for crossing the blood brain barrier. However, due to the constraints of commercial availability, compound 22 was chosen for use in the in vivo studies. When compound 22 is compared to other drugs that are known to cross the blood brain barrier (i.e. haloperidol, cocaine, and ), compound 22 has similar chemical properties to those compounds (Table 3.8).

3.4 In vivo Effects of Compound 22

Given that the logP (liquid water partition coefficient) of compound 22 was 3.30, it was hypothesized that compound 22 could cross the blood brain barrier, and potentially represent the first TAAR1 antagonist that could be tested in vivo (Pajouhesh and Lenz, 2005). It has been previously shown that the Taar1-KO mice have a potentiated response to the psychostimulants, cocaine and amphetamine (see section 1.2.11). Therefore, a functional TAAR1 antagonist in WT mice should mimic the phenotype that is seen in the Taar1-KO mice. Behavioural experiments with compound 22 were carried out on C57BL/6J mice, as well as in mixed background (C57BL/6J x 129S1/Sv) Taar1-KO mice.

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Table 3.7. Comparison of predicted physical properties of antagonist hits from the PubChem database (Wang et al., 2012). H-Bond H-Bond tPSA M.W. Rotatable Cpd 2D structure LogPa Donor Acceptor (A2)b (g/mol) Bonds 9 1.95 4 3 61 227.29 4

16 1.18 5 5 85 193.23 4

22 3.3 2 4 47 348.26 6 24 2.98 2 4 39 309.43 7

a Predicted using xlogP(Cheng et al., 2007) b Topological Polar Surface Area (tPSA)

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Table 3.8. Comparison of predicted physical properties of compound 22 against known drugs that cross the blood brain barrier: clozapine (Cloz), cocaine (coc), and haloperidol (Halo). The chemical properties were taken from the PubChem database (Wang et al., 2012).

H-Bond H-Bond tPSA M.W. Rotatable Cpd 2D structure LogPa Donor Acceptor (A2)b (g/mol) Bonds

22 3.30 2 4 47 348.26 6

Cloz 4.14 1 4 35 326.83 1

Coc 2.87 1 5 57 304.37 5

Halo 4.3 2 3 42 376.88 6

a Predicted using xlogP(Cheng et al., 2007) b Topological Polar Surface Area (tPSA)

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3.4.1 Compound 22 Potentiates the Locomotor Stimulating Activities of Amphetamine and Cocaine in Wildtype C57BL/6J Mice

It had been previously shown that the systemic administration of amphetamine and cocaine to Taar1-KO mice enhances locomotor activity (Wolinsky et al., 2007; Lindemann et al., 2008). Therefore, it was hypothesized that a TAAR1 antagonist could potentially show a similar behavioural phenotype in WT animals.

3.4.1.1 Effects of Compound 22 on Amphetamine-Induced Locomotion in Wildtype C57BL/6J

Using a single sub-maximal dose of amphetamine (2 mg/kg), a dose response study of compound 22 was completed at 5, 15, 20, 30, and 50 mg/kg. The traces for all dose response curves of compound 22 are shown in figure 3.12 A,B. At doses of 5, 15, 20, and 30 mg/kg of compound 22, all mice showed enhanced amphetamine-induced locomotor activity. It was interesting to note, that at the dose of 30 mg/kg of compound 22, there was an initial depression in locomotor activity, followed by enhancement of locomotor activity. At a dose of 50 mg/kg of compound 22, the mice did not have altered locomotor activity compared to vehicle treated mice (Figure 3.12B) indicating that at this higher dose the stimulating effects of compound 22 were not present. It is important to note that the mice did not have altered behaviour at this dose of compound 22 where there was no statistically significant difference in their vertical activity and stereotypy after drug administration (data not shown). Total distance for all doses of compound 22 after 60 minutes are shown in figure 3.12C. One-way ANOVA analyses yielded a statistically significant difference between group means F(5, 126) = 4.788, ***p = 0.0005. Co-administration of compound 22 with amphetamine yielded statistically significant increases in locomotion after 60 minutes at doses of 15, 20 and 30 mg/kg, compared with the vehicle treated group. Mice treated with 15 mg/kg of compound 22, displayed a 44% increase in their total locomotor activity compared with amphetamine treated mice only (*p = 0.04). At doses of 20 or 30 mg/kg of compound 22, mice exhibited 57% (*p = 0.02) and 77% (***p = 0.0009) increased total locomotor activity compared to vehicle treated mice, respectively. Although not significant, there was a trend towards an increase in locomotor activity at doses of 5 mg/kg (28% increase, p = 0.32).

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Figure 3.12. In vivo studies with compound 22 co-injected with amphetamine. Wild type C57BL/6J mice were first habituated for 30 minutes, followed by co-injection of amphetamine (2 mg/kg), with saline or compound 22 (5, 15, 20, 25, and 30 mg/kg). The time course of locomotor activity was assessed for 60 min following injection. A) Locomotor activity over time for 2 mg/kg amphetamine only or co-injected with 5, 15, or 20 mg/kg compound 22. B) Locomotor activity over time for 2 mg/kg amphetamine only or co-injected with 30 or 50 mg/kg compound 22. C) Sum of locomotor activity over 60 minutes after injection of amphetamine and compound 22. Data are means ± S.E.M.; N=12-18 for compound 22 treated alone and N=64 for amphetamine treated alone. A one-way ANOVA was performed (**p < 0.001) followed by Dunnet’s post hoc analyses (*p < 0.05, ***p < 0.001).

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Based on these amphetamine co-administration studies above, it appeared that 15 mg/kg of compound 22 was the minimum dose needed to induce a statistically significant increase in locomotor activity. This dose was the principal dose that will be tested in future in vivo experiments with WT C57BL/6J mice.

3.4.1.2 Effects of Compound 22 on Cocaine-Induced Locomotion in WT C57BL/6J

Similar to amphetamine, we assessed if compound 22 could enhance cocaine-induced locomotion in WT C57BL/6J mice (Figure 3.13). Using a single dose of cocaine (10 mg/kg- sub-maximal dose), a single dose of compound 22 was tested (15 mg/kg). At this dose, there was a statistically significant increase in locomotor activity of animals co-injected with cocaine and compound 22 compared to only cocaine treated mice (74% increase, *p = 0.02) (Figure 3.13B). These data showed that at a dose of 15 mg/kg, compound 22 also enhanced cocaine-induced locomotion in WT mice.

3.4.1.3 Effects of Compound 22 on Basal Locomotor Activity in WT C57BL/6J

In order to assess the effects that compound 22 could have on basal locomotor activity, C57BL/6 mice were injected with doses of 5, 15, and 30 mg/kg of compound 22 or saline. Based on previous studies, the doses were chosen to ensure that they spanned the range of doses that showed locomotor potentiation with both amphetamine and cocaine. The locomotor traces for the three doses of compound 22 are shown in Figure 3.14A. At all doses tested, locomotor activity was not enhanced compared to saline treated mice. However, a one-way ANOVA analysis yielded a statistically significant difference between group means F(3, 32) = 3.490, *p = 0.027. Indeed, all doses showed a trend towards an inhibition of locomotor activity, where the dose of 5 mg/kg was statistically significant (43% decrease, *p = 0.014). The doses of 15 mg/kg (16% decrease, p = 0.58) and 30 mg/kg (26% decrease, p = 0.21) were not statistically significant. These data showed that compound 22, at lower doses, could potentially have an inhibitory effect on basal locomotion. However, compound 22 on its own did not enhance locomotor activity in these mice, indicating compound 22 enhancement of locomotor activity requires the presence of cocaine or amphetamine.

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Figure 3.13. In vivo studies with compound 22 co-injected with cocaine. Wild type C57BL/6J mice were first habituated for 30 minutes followed by co-injection of cocaine (10 mg/kg) with saline or compound 22 (15 mg/kg). The time course of locomotor activity was assessed for 60 minutes following injection. A) Locomotor activity over time for cocaine (10 mg/kg) only or co- injected with compound 22 (15 mg/kg) B) Sum of locomotor activity over 60 minutes after injection of cocaine and compound 22. Data are means ± S.E.M.; N=16-18m *p < 0.05; student’s t-test between vehicle and drug conditions.

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Figure 3.14. In vivo studies with compound 22 on basal locomotor activity. Wild type C57BL/6J mice were first habituated for 30 minutes followed by injection with saline or compound 22 (5, 15, or 30 mg/kg). The time course of locomotor activity was assessed for 60 minutes following injection. A) Locomotor activity over time for saline or compound 22 (5, 15, or 30 mg/kg) B) Sum of locomotor activity over 60 minutes following injection of saline or compound 22 (5, 15, or 30 mg/kg). Data are means ± S.E.M.; N=6 for compound 22 treated alone and N=18 for amphetamine treated alone. A one-way ANOVA was performed (*p = 0.03) followed by Dunnet’s post hoc analyses (*p < 0.05).

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3.5 Effects of Compound 22 in Taar1-KO mice

In order to assess whether or not compound 22 mediated its effects on the potentiation of psychostimulant effects through TAAR1, we tested the ability of compound 22 to enhance psychostimulant-induced motor activity in Taar1-KO mice. We hypothesized that if compound 22 mediating its behavioural effects selectively through antagonizing TAAR1, than Taar1-KO mice would not respond to compound 22 when co-injected with psychostimulants. It is important to note that the Taar1-KO mice tested in this section were on a mix C57BL/6J x 129S1/SV background (Wolinsky et al., 2007). Therefore, in the following experiments, both the Taar1-KO and their WT littermates were tested to control for confounds of a mixed genetic background vs the studies described in the previous section on C57BL/6J mice.

3.5.1 Effects of Compound 22 on Amphetamine-Induced Locomotion in Taar1-KO mice

As with the previous in vivo experiments with compound 22 (see section 3.4.1.1), a single dose of amphetamine (2 mg/kg) was used. In these experiments, doses of 2.5, 5, and 15 mg/kg of compound 22 were tested in Taar1-KO mice and their WT littermates (Figure 3.15). In both WT and Taar1-KO mice, one-way ANOVA analyses yielded a statistically significant difference between group means for the WT F(3, 43) = 2.862, *p = 0.048, and Taar1-KO mice F(3, 43) = 4.159, *p = 0.011. At a dose of 2.5 mg/kg of compound 22, WT mice showed a slight, but not significant, inhibition in locomotor activity (7% decrease, p = 0.97). In contrast, at the same dose of 2.5 mg/kg of compound 22, the Taar1-KO animals showed a trend towards increased locomotor activity (13% increase, p = 0.91). At a dose of 5 mg/kg of compound 22, WT mice showed a statistically significant increase in locomotor activity (44% increase, *p = 0.049). Taar1-KO mice, at the same dose, showed a similar trend towards locomotor potentiation (45% increase, p = 0.19), which was not statistically significant. Lastly, at a dose of 15 mg/kg of compound 22, WT mice showed a decrease in locomotor activity (17% decrease, p = 0.80). In contrast, treatment with 15 mg/kg of compound 22 caused significant potentiation of locomotor activity in Taar1-KO mice (84%, **p = 0.004).

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Figure 3.15. in vivo studies with Taar1-KO mice co-injected with compound 22 and amphetamine. Taar1-KO mice and WT littermates (C57BL/6J x 129S2/Sv) were first habituated for 30 minutes, followed by co-injection of amphetamine (2 mg/kg) with saline or compound 22 (2.5, 5, and 15 mg/kg). The time course of locomotor activity was assessed for 60 minutes following injection. A) WT locomotor activity over time for amphetamine (2 mg/kg) only or co- injected with compound 22 (2.5, 5, and 15 mg/kg). B) Taar1-KO locomotor activity over time for amphetamine (2 mg/kg) only or co-injected with compound 22 (2.5, 5, and 15 mg/kg). C) Sum of locomotor activity over 60 minutes following injection of amphetamine and compound 22 in WT (solid bars) or Taar1-KO mice (dotted bars). Data are means ± S.E.M.; N=7-23. A one-way ANOVA was performed for each genotype; WT (*p = 0.048) and Taar1-KO (*p = 0.011) followed by Dunnet’s post hoc analyses (*p < 0.05, **p < 0.01).

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Interestingly, it was expected that the Taar1-KO mice would show potentiated locomotor activity, compared to WT littermates, when injected with amphetamine (Wolinsky et al., 2007; Lindemann et al., 2008; Achat-Mendes et al., 2012). However, comparing WT with Taar1-KO mice, amphetamine treatment resulted in no difference in locomotor activity in the Taar1-KO mice (6% decrease, p=0.70) (Figure 3.15).

In conclusion, compound 22 showed potentiation of amphetamine-mediated locomotor stimulation in Taar1-KO mice in a dose dependent manner. Moreover, the WT littermates did not respond to compound 22 co-injection with amphetamine to the same extent that was observed in treated WT C57BL/6J mice (section 3.4.1.1.).

3.5.2 Effect of Compound 22 on Cocaine-Induced Locomotion in Taar1-KO mice

Next, a number of doses of compound 22 were assessed with cocaine co-injection in the Taar1- KO mice and their WT littermates. In these experiments, a dose of 5, 15, and 25 mg/kg of compound 22 were used. As with previous studies (section 3.4.1.2.), a dose of 10 mg/kg of cocaine was used for all locomotor assays (Figure 3.16). In both WT and Taar1-KO mice, one-way ANOVA analysis yielded a statistically significant difference between group means for the WT F(3, 38) = 17.97, ****p < 0.0001, and Taar1-KO mice F(3, 52) = 13.93, ****p < 0.0001. At a dose of 5 mg/kg of compound 22, there was a statistically significant increase in the locomotor activity, both in the WT (94%, **p = 0.0087) and Taar1-KO mice (62%, **p = 0.0024), when compared with vehicle treated animals. Similarly, at a dose of 15 mg/kg, both the WT (185%, ****p < 0.0001) and Taar1-KO (105%, ****p < 0.0001) had statistically significant increases in their locomotor activity. Lastly, the trend of increased locomotor activity continued at a dose of 25 mg/kg of compound 22, in both the WT (185%, ****p < 0.0001) and Taar1-KO mice (100%, ****p< 0.0001). As with amphetamine treatment, cocaine-treated Taar1-KO mice treated should have potentiated locomotor activity when compared to WT mice. However, our results showed that the locomotor activity of the Taar1-KO mice was only 19% greater than WT mice when injected with cocaine alone (Figure 3.16), and this was not statistically significant (p = 0.22). These data indicated that compound 22 was able to potentiate the locomotor response of cocaine in both the Taar1-KO mice and their WT littermates in a dose dependent manner and to the same extent.

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Figure 3.16. in vivo studies with Taar1-KO mice co-injected with compound 22 and cocaine. Taar1-KO mice and WT littermates (C57BL/6J x 129S2/Sv) were first habituated for 30 minutes, followed by co-injection of cocaine (10 mg/kg) with saline or compound 22 (5, 15, and 25 mg/kg). The time course of locomotor activity was assessed for 60 minutes following injection. A) WT locomotor activity over time for cocaine (10 mg/kg) only or co-injected with compound 22 (5, 15, and 25 mg/kg). B) Taar1-KO locomotor activity over time for cocaine (10 mg/kg) only, or co- injected with compound 22 (2.5, 5, and 15 mg/kg). C) Sum of locomotor activity over 60 minutes following injection of cocaine and compound 22 in WT (solid bars) or Taar1-KO mice (dotted bars). Data are means ± S.E.M.; N=7-29. A one-way ANOVA was performed for each genotype; WT (****p < 0.0001) and Taar1-KO (****p < 0.0001) followed by Dunnet’s post hoc analyses (**p < 0.01, ****p < 0.0001).

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3.5.3 Effect of Compound 22 on Basal Locomotion in Taar1-KO mice

To investigate the effects of genetic background on drug response, Taar1-KO and WT littermates were tested with different doses of compound 22 alone. Previous experiments in C57BL/6J mice indicated that compound 22 did not stimulate basal locomotor activity.

A dose response of compound 22 (5, 15, and 25 mg/kg) was performed in order to assess if compound 22 could modulate the basal activity of the Taar1-KO mice or their WT littermates (Figure 3.17). At all three doses tested, compound 22 did not significantly increase the locomotor activity of the Taar1-KO mice. However, a one-way ANOVA analysis yielded a statistically significant difference between group means for the WT animals F(3, 88) = 4.68, **p = 0.009. In these WT mice, compound 22 had no effect on basal locomotor activity at doses of 5 mg/kg (30% decrease, p = 0.433) and 25 mg/kg (18% decrease, p = 0.91). A dose of 15 mg/kg of compound 22 significantly enhanced basal locomotor activity in WT mice (42% increase, *p = 0.026). These data indicated that compound 22 enhanced the basal locomotor activity of the WT animals derived from the mix genetic background of Taar1-KO mice.

3.5.4 Compound 22 Screens in Collaboration with PDSP

Since our results with the Taar1-KO mice indicated that compound 22 was mediating the in vivo effects through a TAAR1 independent manner, we next aimed to determine the target for compound 22.

We determined the potential pharmacological targets of compound 22 using the Psychoactive Drug Screening program (PDSP) at University of North Carolina-Chapel-Hill. PDSP provides a platform for screening potentially novel psychoactive compounds on human or rodent receptors expressed in the central nervous system in order to identify the biological target of psychoactive compounds (Besnard et al., 2012). Binding studies were done on 47 targets at a single dose of compound 22 (10μM). This primary screen yielded a total of 5 hits for compound 22 (Supplemental Table 1). These hits were the serotonin, dopamine, and norepinephrine transporters, as well as the sigma 1 and sigma 2 receptors. The affinity for compound 22 for SERT, DAT, and NET were relatively low with Ki = 1800, 1053, and 1902 nM, respectively

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Figure 3.17. in vivo studies with Taar1-KO mice and compound 22 on basal locomotor activity. Taar1-KO mice and WT littermates (C57BL/6J x 129S2/Sv) were first habituated for 30 minutes followed by saline or compound 22 (5, 15, and 25 mg/kg). The time course of locomotor activity was assessed for 60 minutes following injection. A) WT locomotor activity over time for saline or compound 22 (5, 15, and 25 mg/kg). B) Taar1-KO locomotor activity over time for saline only or compound 22 (2.5, 5, and 15 mg/kg). C) Sum of locomotor activity over 60 minutes after injection of compound 22 in WT (solid bars) or Taar1-KO mice (dotted bars). Data are means ± S.E.M.; N=3-23. A one-way ANOVA was performed for each genotype; WT (**p = 0.009) and Taar1-KO (p = 0.332) followed by Dunnet’s post hoc analyses (*p < 0.05).

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(Supplemental Table 2). However, compound 22 had higher affinity for the sigma 1 and 2 receptors at Ki = 276 and 412 nM, respectively.

Furthermore, PDSP also conducted functional assays for GPCR activation using the Tango functional assay. The Tango assay measures the recruitment of β-arrestin to activated GPCRs and subsequent expression of luciferase (Kroeze et al., 2015). Compound 22 was tested at 1μM on ALL 320 non-olfactory human GPCRs. The primary assay yielded one hit for compound 22, the dopamine D2 receptor (Supplemental Figure 1). Secondary experiments were performed in our lab to validate whether the D2-Dopamine receptor is indeed a target of compound 22. Using a D2- Rluc construct transfected with YFP tagged β-arrestin, we carry out β-arrestin recruitment assay. Our results showed that with increasing doses of compound 22, recruitment of β-arrestin was not observed (Figure 3.18). Quinpirole, a full agonist of D2 receptor was used as positive control and it induced β-arrestin recruitment (EC50 = 155 ± 43.5 nM). In accordance with these data, a secondary screen experiments also performed by PDSP showed that compound 22 was not recruited to β-arrestin in the Tango assay, and that there was no signalling through the D2 receptor (Supplemental Figure 2). These results indicated that compound 22 did not activate the dopamine D2 receptor and that the original hit from the Tango assay was most likely a false positive.

3.5.5 Compound 22 Interaction with the Dopamine Transporter (DAT)

We also assessed the ability for compound 22 to interact with DAT using dopamine uptake experiments. Since PDSP had shown that compound 22 bound to DAT (Ki = 1053nM), it was hypothesized that compound 22 could block dopamine uptake, which could underlie the in vivo effects we observed in previous sections (Section 3.4.1.2). Cells stably expressing an HA-DAT construct were pre-treated with increasing doses of compound 22 or cocaine (positive control). The ability for compound 22 to directly disrupt uptake was assessed with a fluorescent uptake assay (Figure 3.19). As shown in Figure 3.19A compound 22 did not directly inhibit uptake in a dose dependent manner when compared with cocaine, which was used as a positive control (EC50 = 0.95 ± 0.02 μM) (Figure 3.19A). This was in contrast to the results obtained from PDSP and rather indicated that compound 22 does not block uptake by blocking DAT.

Next, compound 22 was assayed in the presence of cocaine to determine whether compound 22 enhanced or inhibited cocaine blockade of dopamine uptake through an allosteric mechanism (Figure 3.19B). Mechanistically, it was hypothesized that compound 22 enhancement of cocaine

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Figure 3.18. Dose response curves for β-arrestin recruitment to the dopamine D2 receptor using quinpirole and compound 22. Dose response curves were generated for compound 22 or quinpirole by the addition of a range of doses (1 pM – 100 µM) to HEK293T cells transiently expressing both 3µg D2-Rluc and 2µg YFP-βarrestin-YFP. Error bars represent standard error of mean at N=3.

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Figure 3.19. Dose response curves for cocaine and compound 22 effects on dopamine transporter uptake activity. Dose response curves were generated for compound 22 or cocaine by the addition of a range of doses (1 nM – 100 µM) to HEK293 cells stably expressing human HA-DAT. A) Dose response of cocaine and compound 22 on inhibition of uptake. B) Cocaine co- treatment with: vehicle, 1, 10, or 100 µM of compound 22. Error bars represent standard error of mean at N=3.

90 binding could underlie the behavioural results obtained our in vivo studies (Figure 3.13 and 3.16).

Based on the EC50 values, compound 22 at doses of 1 μM (0.95 ± 0.02 μM), 10 μM (1.12 ± 0.22 μM) and 100 μM (0.92 ± 0.11 μM), did not shift the potency of cocaine blockade (1.79 ± 0.79 μM) of dopamine uptake. These results indicated that compound 22 does not affect dopamine uptake in in vitro assays with transfected human HA-DAT.

4 Discussion 4.1 Evaluation of the TAAR1 Homology Model

The TAAR1 homology model was generated based on the inverse agonist bound, inactive β2AR structure (PDB accession code: 2RH1). This receptor was chosen due to its 38% sequence homology with TAAR1 in the transmembrane regions (Cherezov et al., 2007). In addition, the inactive state of the receptor was chosen as the template in order to increase the probability for the discovery of antagonists. The orthosteric binding site of the TAAR1 homology model was very similar to the template and to other available structures for aminergic GPCRs. For example, several residues in the core of the binding site were identical to the corresponding residues in the template, e.g. Asp1033.32, Trp2646.48, Phe2676.51, Phe2686.52, and Tyr2947.43 (superscripts represent Ballesteros-Weinstein nomenclature) (Ballesteros and Weinstein, 1995). In our model, bPEA was anchored into the binding site by a salt bridge with residue Asp1033.32, which is conserved among aminergic GPCRs, and is also found in other homology models of human and mouse TAAR1 (Cichero et al., 2013, 2014; Reese et al., 2014; Chiellini et al., 2016). In accordance with a previous human TAAR1 homology model, our model showed that the phenyl ring of bPEA formed π- stacking interactions with residues Phe2676.51 and Phe2686.52 (Cichero et al., 2013). These results indicated that the orthosteric binding site of our homology model adopted a conformation that was suitable for binding agonists. Since previous models were based on agonist bound β2AR structure, this result was unexpected since our model was based off of the inactive state β2AR structure, which was hypothesized to result in an orthosteric binding site that was less suitable for the binding of agonists. The fact that our homology model was similar to previous models (agonist bound vs. inactive) was mainly due to the limited selection of TAAR1 ligands available. The enrichment process for the homology model relies on the model being able to predict known ligands over decoy compounds (see section 1.3.2). Since essentially all TAAR1 ligands are agonists (except one antagonist, EPPTB), the orthosteric binding site of our model adopted a conformation in which

91 agonists will preferentially bind. With the continued discovery of new TAAR1 antagonists, improvements in homology model generation for TAAR1 can be made. In summary, despite using the inactive state β2AR structure as a template, the TAAR1 homology model generated in this study resulted in an orthosteric binding site similar to previously based agonist binding models. Therefore, these results indicate that our homology model was able to accurately model the orthosteric binding site of TAAR1 which would allow for molecular docking of the homology model.

4.1.1 Molecular Docking of the TAAR1 Homology Model

Using our newly generated TAAR1 homology model, two molecular docking screens were performed. In the first screen, a fragment-like library of 357,000 molecules from the ZINC database were virtually docked into the orthosteric binding site of the homology model. While most molecular docking screens are done with larger, lead-like libraries (Carlsson et al., 2010, 2011), a fragment sized library was used due to the fact that most known TAAR1 ligands are of fragment size. Therefore it was hypothesized that a fragment sized library could have a larger probability for success. One of the challenges of molecular docking with fragment sized libraries stems from the inaccurate docking of these ligands to the orthosteric binding site. Due to the small size of these fragments, these ligands can bind in a large number of orientations that could be difficult for the docking algorithms to score accurately (Rodríguez et al., 2014b). However, despite these potential challenges with fragment based screening, molecular docking screens with homology models were able to achieve hit rates of up to 73% (de Graaf et al., 2011). Further success with fragment based screening has been reported with molecular docking screens of adenosine A1 and A3 receptor homology models, where the docking screen was able to discover novel antagonists for the with nanomolar affinity (Rodríguez et al., 2014b). While most of the known TAAR1 ligands were of fragment size, the homology model indicated that the orthosteric binding site could bind larger molecules. Therefore, a second screen was performed, this time using a lead-like library of 2.7 million compounds, which were docked on the same homology model.

From the two previously described screens, 21 lead-like and 21 fragment-like compounds were experimentally tested for their abilities to be agonists or antagonists for TAAR1 in vitro. Of the 42 compounds tested, the hit rates for agonist activity were 5% and 33% for the lead-like and

92 fragment-like compounds, respectively (see section 3.2). This difference in hit rate indicates that the orthosteric binding site for TAAR1 is more suitable for the binding of fragment sized ligands. Indeed, the endogenous ligands and several high affinity agonists for TAAR1 are also fragment- sized (see Table 3.1).

4.2 In vitro Evaluation of Predicted Ligands Yielded Novel Agonists and Potentially Low Potency Antagonists

The 42 identified ligands (21 lead-like and 21 fragment-like) were assayed in a cell based in vitro assay for TAAR1 signalling, which was based on the BRET EPAC cAMP biosensor. This assay was previously shown to be effective at quantifying TAAR1 activation (Barak et al., 2008; Cichero et al., 2013, 2014). The 42 identified compounds were tested for agonist activity (i.e. TAAR1 activation), and antagonist activity, which was measured by the ability for these compounds to antagonize TAAR1 signalling that was induced by bPEA, a full TAAR1 agonist. Nine of the compounds induced TAAR1 signalling, whereas eight compounds blocked bPEA-mediated TAAR1 signalling (see section 3.2, Figure 3.2). The overall hit rate for this screen was 38%, which as similar to that reported for molecular docking screens of other GPCRs (Carlsson et al., 2010, 2011).

Based on this initial screen, it can be concluded that the TAAR1 homology model was able to successfully model the orthosteric binding site of TAAR1. It was expected that both agonists and antagonists would be discovered, since there are only small differences in overall volume of the orthosteric binding site between the active and inactive state of the β2AR (Rasmussen et al., 2011a; Rasmussen et al., 2011b). Indeed other molecular docking screens of TAAR1, and the dopamine D2 receptor, also yielded a mixture of agonists, inverse agonists, and antagonists (Weiss et al., 2013; Cichero et al., 2014). Therefore, it can be concluded that the structural features responsible for either receptor activation, or inactivation, may be difficult to discern in a homology model.

4.3 Characterization of Agonist Hits

4.3.1 Three Partial Agonists for TAAR1 were Discovered

While both agonists and antagonists were discovered from this initial screen, full dose responses for the potential agonist and antagonist hits were tested in order to distinguish legitimate hits from false positives. Of the original nine hits that were shown to induce TAAR1 signalling, only three

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compounds (8, 16, and 25) yielded EC50 values that were < 100µM (see section 3.2.1., Figure 3.3, Table 3.2). The other six compounds did not yield saturated dose response curves, preventing accurate estimation of their EC50 values. In addition, the three compounds that did have a saturated dose response (8, 16, and 25), only yielded partial activation of TAAR1 compared with the full agonist bPEA. Control experiments with cells that do not express TAAR1 did not yield any stimulation of endogenous Gαs coupled receptors (Figure 3.5). This control experiment was performed since HEK293 cells express several endogenous GPCRs that couple to Gαs (Mundell and Benovic, 2000). These results showed that the Gαs activation detected in our assay for compound 8, 16, and 25 were TAAR1 selective.

In order to assess the novelty of our discovered compounds compared with known ligands for TAAR1, the Tc values were calculated. The Tc values were calculated with extended-connectivity fingerprints between each hit from the screen and TAAR1 ligands in the ChEMBL19 database (Gaulton et al., 2012). A Tc value equal to one is obtained for identical compounds, whereas values close to zero suggest low similarity to previously reported ligands. The Tc values for the nine agonists ranged from 0.23 to 0.61 (see section 3.2.1., Table 3.2 and 3.3). Four agonists (6, 8, 11, 37) had Tc values < 0.3, which indicated that these compounds represented novel chemical scaffolds that could bind to TAAR1 (Wawer and Bajorath, 2010). One of the most potent agonists from the screen, compound 8, was dissimilar to all previously reported TAAR1 ligands (Tc = 0.25). Interestingly, compound 16 had a very high Tc value (0.61), due to its similarities to known TAAR1 agonists. One such compound had been discovered in an unpublished PubChem assay (AID686984, AID686985)(Wang et al., 2012). Unfortunately, the results of this previous high- throughput screen were not deposited in the ChEMBL database when our docking screen was performed. In addition, compound 16 is structurally related to the α2AR agonist , which was previously shown to be a potent TAAR1 agonist (Hu et al., 2009). The predicted binding mode of compound 8 and 16 shows that they occupy the same part of the orthosteric site as bPEA.

In summary, secondary in vitro screens of the initial nine agonist hits yielded three partial agonists, with moderate affinity for TAAR1 (compounds 8, 16, and 25). Of the three hits, compounds 8 and 16 were from the fragment-like library and compound 25 was from the lead-like library. This distribution of hits from the two libraries shows that the orthosteric binding site of TAAR1 may preferentially bind fragment sized ligands, but it is also capable of binding larger lead-like ligands.

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Lastly, of the three agonists, compound 8 was the most unique compared to previously discovered TAAR1 ligands. Compound 16, however, was similar to other TAAR1 agonists.

4.3.2 Characterization of Agonist Analogs

Due to the fact that compounds 8 and 16 were of fragment, further optimization by medicinal chemistry was possible. While we did not perform the medicinal chemistry, analogues of compound 8 and 16 were ordered and assessed to see if they had improved binding and efficacy for TAAR1. In total, five analogues were ordered for each of the compounds. None of the analogues for compound 8 improved the potency or efficacy for activation of TAAR1. Based on these results, the following properties did not affect compound 8 activity at TAAR1: increased bulk of the methyl group located on the (8a and 8b); alteration of the benzimidazole to a benzthiazole (8c); or altered size of the ring (8d and 8e) (Table 3.4).

Interestingly, when the five analogues for compound 16 were ordered, two previously characterized TAAR1 agonists (16a and 16b) were also purchased. As mentioned in section 4.3.1., 16a was found to be a TAAR1 agonist from an unpublished PubChem assay, and 16b (guanabenz) was previously reported to be a potent TAAR1 agonist (Hu et al., 2009). Subsequent testing showed that compound 16a and 16b were partial agonists for TAAR1, with 13.6 and 7.2 times increased potency for TAAR1 compared with compound 16. These results highlight that modification of the phenyl ring is capable of significantly altering the activity of compound 16 analogues for TAAR1. However, adding bulk to the phenyl ring does not improve the activity of these analogues at TAAR1 (16c-e) (Table 3.5).

In summary, none of the analogues of compound 8 showed improved potency or efficacy for TAAR1 activation. In comparison, compound 16 analogues, 16a and 16b, showed improvements in potency for TAAR1 while remaining partial agonists. Lastly, analogues 16c-e did not show any improvements in potency or efficacy.

4.3.3 The Discovery of Low Potency Antagonists for TAAR1

Dose responses of the eight compounds shown to inhibit bPEA-mediated TAAR1 signalling were conducted to further characterize these compounds. Of the eight compounds, four were false positives. Compound 2 and 38 did not show any antagonist activity. Compound 35 and 39 were insoluble at the highest tested concentration of 100 µM (Section 3.2.2., Figure 3.10, Table 3.6).

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The last four compounds tested (compounds 9, 16, 22, and 24), inhibited bPEA-mediated signalling of TAAR1 at the highest doses tested. Unfortunately, dose response curves could not be accurately fitted to these curves and IC50 values could not be estimated. Based on these results, compounds 9, 16, 22, and 24 could potentially be low potency TAAR1 antagonists. It is important to note that in our studies, compound 16 showed up as both an agonist, as well as an antagonist. Since compound 16 is a partial agonist for TAAR1 (see section 3.2.1.), it is possible for it to also exhibit antagonist activity for TAAR1. Indeed, partial agonists can act as antagonists depending on the properties of the agonist they are assayed against (Bolonna and Kerwin, 2005). In addition, the backbone of compound 16 could represent a starting point in medicinal chemistry terms, allowing for the conversion of compound 16 into an antagonist. There have been numerous examples of minor chemical modifications that change agonists into antagonists, which has been extensively reviewed elsewhere (Dosa and Amin, 2016). Indeed, three analogues for compound 16 were tested (section 3.2.2.1., Figure 3.11), where none were more potent, or efficacious, at antagonizing bPEA-mediated TAAR1 signalling. It should be noted that compound 16e had a slightly left shifted curve compared to compound 16, indicating that additional medicinal chemistry of compound 16 could potentially yield higher affinity antagonists.

4.3.4 Chemical Properties of Compound 22 Allow for Access Across the Blood Brain Barrier

One of the main goals of this study was to discover novel antagonists that could be tested in vivo.

We first assessed the predicted physical properties of the four antagonist hits (compound 9, 16, 22, and 24), showing that compound 22 and 24 had the most favourable properties for crossing the blood brain barrier (section 3.3.1, Table 3.7). Extensive reviews of marketed drugs for the CNS had determined a series of chemical properties that would predict if compounds were capable of crossing the blood brain barrier (Pajouhesh and Lenz, 2005). Averaged together, the following properties have been found in drugs that cross the blood brain barrier: logP < 5 (mean logP = 2.5), molecular weight < 450 g/mol, number of H-bond donor < 3, number of H-bond acceptor < 7, number of rotatable bonds < 8, and polar surface area < 60-70Ǻ2. Based on these criteria, all four of our compounds fall within these limits. The main differences between compounds 22 and 24, when compared to the other antagonist hits, were the higher logP values, as well as lower polar surface area when compared with compounds 9 and 16. Compound 22 was eventually chosen over compound 24 due to compound 22’s commercial availability. Indeed, compound 22 has

96 similar structural properties when compared to other drugs that are known to cross the blood brain barrier (Table 4.1).

4.4 Compound 22 Potentiates Amphetamine and Cocaine- Induced Locomotor Activity

4.4.1 Compound 22 Potentiates Amphetamine Induced Locomotor Activity

We hypothesized that compound 22 would cross the blood brain barrier and potentially be the first TAAR1 antagonist with in vivo activity. The in vivo studies performed in mice were based on the following two premises. First, it is known that TAAR1 signalling regulates dopamine transmission (see section 1.2.10). Secondly, the Taar1-KO mice have been shown to have increased sensitivity to the locomotor-stimulating effects of psychostimulants (see section 1.2.11). Therefore, the behaviour experiments conducted with compound 22 used the dopamine system as an output, focusing on locomotor activity.

To begin in vivo characterization, we first assessed the effect of a dose response of compound 22 on amphetamine induced locomotor activity. The dose of amphetamine chosen (2 mg/kg) was based off previous studies, where 2 mg/kg was a sufficient dose to induce an increase in locomotor activity (Yates et al., 2007). However and importantly, at a dose of 2 mg/kg, maximal locomotor activity is not seen (O’Neill and Gu, 2013), allowing for any potentiation of amphetamine response to be quantified. Indeed, compound 22 was found to enhance amphetamine-induced locomotor activity at doses of 15, 20, and 30 mg/kg (section 3.4.1.1, Figure 3.12). Interestingly, at higher doses of compound 22 (30 and 50 mg/kg), a biphasic response was seen where compound 22 inhibited the locomotor stimulating effects of amphetamine. Specifically, at a dose of 30 mg/kg of compound 22, mice exhibited an initial depression in locomotor activity, followed by enhancement of locomotor activity. However, at a dose of 50 mg/kg of compound 22, there was no potentiation in locomotor activity.

Biphasic responses due to high doses of compounds have been observed for other drugs acting on other receptors. For example, high doses of the dopamine D1 agonist SKF 38393 induced locomotor suppression followed by hyperlocomotion (Tirelli and Terry, 1993). Further examples include drugs of abuse such as ethanol, amphetamine, and MDMA (Gingras and Cools, 1996; Yates et al., 2007; Lizarraga et al., 2014). These data indicate that compound 22 is able to increase

97 dopamine transmission in conjunction with amphetamine, consistent and potentially due to the antagonism of TAAR1.

4.4.2 Compound 22 Potentiates Cocaine-Induced Locomotor Activity

Next, compound 22 effects on cocaine-induced locomotor activity were assayed. Previous research with Taar1-KO mice has shown that these animals have increased sensitivity to the locomotor stimulating effects of cocaine (Wolinsky et al., 2007). Similar to the amphetamine studies, a single dose of cocaine (10 mg/kg) was used to assess the actions of compound 22. This dose of cocaine has previously been shown to stimulate locomotor activity (Orsini et al., 2005). As with the amphetamine studies, this dose of cocaine does not induce maximum locomotor response, allowing for measuring any potentiation in the cocaine response by compound 22. In addition, the only dose tested for compound 22 in combination with cocaine, was 15 mg/kg since this was the most effective dose at potentiating amphetamine response. The dose of 15 mg/kg of compound 22 was able to significantly potentiate the locomotor stimulating effects of cocaine (section 3.4.1.2, Figure 3.13) indicating that compound 22 can increase cocaine-induced locomotor activity, similar to what was seen in the Taar1-KO mice.

In conclusion, these in vivo results indicate that compound 22 could potentially be mediating the enhancement of amphetamine- and cocaine-mediated locomotor activity, through TAAR1.

4.4.3 Compound 22 Alone Does Not Stimulate Locomotor Activity

It is possible that the observed potentiation of cocaine- and amphetamine-mediated locomotor hyperactivity by compound 22 could be mediated by the direct action of compound 22 to stimulate locomotor activity. Although the Taar1-KO mouse have been found to have dysregulated dopamine transmission (see section 1.2.11), the basal locomotor activity of these mice is not different from WT littermates (Wolinsky et al., 2007; Lindemann et al., 2008; Di Cara et al., 2011). Therefore, we hypothesized that if compound 22 was a TAAR1 antagonist, injection of compound 22 would not significantly induce locomotor activity. Indeed, when injected at doses of 5, 15, or 30 mg/kg, compound 22 did not enhance the basal locomotor activity of mice (section 3.4.1.3, Figure 3.14A). Therefore, these results indicate that compound 22 does not induce locomotor activity, and that the previous results with amphetamine and cocaine are not due to an additive effect of two locomotor stimulating compounds.

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4.5 Effects of Compound 22 in Taar1-KO mice

In order to confirm that compound 22 is, indeed, a TAAR1 antagonist, the effects of compound 22 were assessed on cocaine- and amphetamine-induced locomotor activity in Taar1-KO mice. We hypothesized that if compound 22 was a TAAR1 antagonist, there would be no enhancement of locomotor activity in the presence of amphetamine or cocaine. It should be noted, that the initial compound 22 in vivo experiments were done in mice with a congenic C57BL/6J background, but the Taar1-KO mice that we obtained were of a C57BL/6J x 129S1/SV mixed background (Wolinsky et al., 2007). It has been shown that different strains of mice have different responses to psychostimulants (see section 4.5.2.1). The mixed background mice were used for all subsequent Taar1-KO experiments. Importantly WT littermates of the Taar1-KO mice were used in order to control for strain differences.

4.5.1 Compound 22 Potentiates Amphetamine Locomotor Activity in Taar1- KO Mice

As with the previous amphetamine studies performed with congenic C57BL/6J mice, a dose response of compound 22 was done in the presence of a single locomotor-stimulating dose of amphetamine (2 mg/kg), in both Taar1-KO and WT littermates. The results from this study showed that compound 22 dose-dependently potentiated amphetamine-mediated locomotor activity in both genotypes (section 3.5.1, Figure 3.15). These results indicate that compound 22 potentiates locomotor activity of amphetamine through a Taar1-independent mechanism in the Taar1-KO mice. Interestingly, the WT mice had attenuated responses to compound 22 and amphetamine. This result was unexpected and could potentially be explained in part by the strain differences observed between our initial studies on the C57BL/6J and the C57BL/6J x 129S1/SV Taar1-KO mixed background mice (see section 4.5.2.1). Lastly, it is interesting to note that there were no differences between Taar1-KO mice and their WT littermates when injected with amphetamine only (Figure 3.15).

While Taar1-KO mice are reported to be more sensitive to amphetamine-mediated locomotor activity (Wolinsky et al., 2007; Lindemann et al., 2008), the response dependent on the route of administration and dose used. Indeed, during the initial characterization of the Taar1-KO mice, subcutaneous administration of amphetamine only showed locomotor potentiation at 1 mg/kg (Wolinsky et al., 2007). Conversely, in a different study, Taar1-KO mice treated with escalating

99 doses of amphetamine (intraperitoneal administration, doses: 0.5, 1.0, 2.0, 3.0, 4.0, 5.0, and 6.0 mg/kg) only show increased locomotor activity at a dose of 3 mg/kg of amphetamine, with no differences seen at the other doses of amphetamine (Achat-Mendes et al., 2012). Finally, other groups have reported that Taar1-KO mice are sensitive to amphetamine at all doses tested (intraperitoneal administration, doses: 1.0 and 2.5 mg/kg) (Lindemann et al., 2008). These discrepancies in amphetamine response in the Taar1-KO mice could be due to several factors, including route of administration (intraperitoneal or subcutaneous) and other experimental conditions (i.e. housing conditions). It is important to note that the genetic background of these Taar1-KO mice was not the same. In certain studies, Taar1-KO mice were in a mixed C57B/L6J x 129S1/Sv (Wolinsky et al., 2007), whereas others used Taar1-KO mice in a congenic C57BL/6J background (Lindemann et al., 2008).

4.5.2 Compound 22 Potentiates Cocaine Locomotor Activity in Taar1-KO mice

Furthermore, the effects of compound 22 on the enhancement of cocaine-induced hyperlocomotion was tested in Taar1-KO mice. As with the previous study (section 3.4.1.1), a dose response of compound 22 was performed against a single dose of cocaine (10 mg/kg), (Figure 3.16). Both Taar1-KO, and their WT littermates, exhibited similar potentiation of locomotor activity when cocaine was co-injected with compound 22 in a dose dependent manner, indicating that this effect of compound 22 is TAAR1 independent.

4.5.2.1 Strain Differences in Response to Psychostimulants

One of the interesting observations in our study was the strain differences in response to psychostimulants. The response to compound 22 and amphetamine differed between congenic C57BL/6J WT mice and mixed (C57BL/6J x 129S1/Sv) background WT mice. Specifically, the WT C57BL/6J mice showed a dose-dependent potentiation of amphetamine-mediated locomotor activity with compound 22, whereas the mixed background WT mice (C57BL/6J x 129S1/Sv) did not. This was not a surprising finding, as it has been previously shown that C57BL/6J and 129S1/Sv strains of mice have modest, but significant, differences in their response to amphetamine- or cocaine-induced locomotion. Congenic WT C57BL/6J mice are more sensitive to both amphetamine and cocaine, and therefore have an exaggerated locomotor response to these psychostimulants, when compared with other strains (Schlussman et al., 1998, 2003; Zhang et al.,

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2002; Chen et al., 2007; Eisener-Dorman et al., 2011). In conclusion, it is possible that several genetic components between the strains can explain the differences observed in compound 22 potentiation of amphetamine-mediated locomotor activity.

Despite these behavioural differences, no differences in DAT levels, or function of the transporter, between the two mouse strains has been reported (C57BL/6J vs. mixed background) (Chen et al., 2007). However, it has been postulated that further downstream proteins, that regulate amphetamine response (i.e. PKC), may mediate, and ultimately manifest, the behavioural differences observed in the amphetamine response of mice with differing genetic backgrounds (Chen et al., 2007). Furthermore, it has been hypothesized that differences in other monoamine transporter systems may also mediate these strain differences to psychostimulants. For instance, it is known that amphetamine induces dopamine release in the medial pre-frontal cortex through the blockade of the norepinephrine transporter, therefore it is possible that norepinephrine transporter dysregulation could mediate some of the strain differences (Shoblock et al., 2004). However, there have been no reports of monoamine transporter dysregulation in different mouse strains. It is important to note that there have been reports of genetic in downstream effector genes of the C57BL/6N that lower acute responses to cocaine (Kumar et al., 2013).

Furthermore, dysregulation of receptor systems could also explain the observed and reported strain differences. For instance, it is also possible that the 129S1/Sv and C57BL/6J strains may have different expression levels of TAAR1. Indeed, for example, it has recently been shown that the DBA-02 mouse carries a polymorphism that results in an expressed, but non-functional TAAR1 receptor (Harkness et al., 2015; Shi et al., 2016). Therefore, it would not be surprising if there were other yet to be discovered genetic differences between the 129S1/Sv and C57BL/6J strains that would lead to the varying behavioural responses to psychostimulants. This further highlights the importance of mouse strain used for behavioural results

Interestingly, a study investigating the effects of genetic background on behavioural response was completed with the cocaine insensitive dopamine transporter knock-in mouse (DAT-CI) (Chen et al., 2006; O’Neill and Gu, 2013). The initial characterization of the DAT-CI mouse was done in a mixed C57BL/6J x 129Sv/J background (Chen et al., 2006). The authors discovered that the mixed background mice (both WT and DAT-CI) had the following differences when compared to backcrossed C57BL/6J mice: 1) lower basal locomotor activity, 2) greater efficiency in habituation

101 to a novel environment, and 3) locomotor stimulation at a high dose of amphetamine (20 mg/kg) (O’Neill and Gu, 2013). The authors concluded that these behavioural differences were not genotype specific, but primarily due to the differences in strain background. Lastly, the authors further proposed that a detailed study pertaining to the genetics of these two strains could possibly shed insight into how specific mechanisms can mediate certain behavioural disorders.

Up until very recently, the generation of genetic knock-out/in mice was generally done using ES cells derived from the 129S1/Sv strain of mice. These ES cells would then be injected into C57BL/6J surrogates, leading to mice of a mixed genetic background (C57BL/6J x 129S1/Sv) (O’Neill and Gu, 2013). However, behaviour experiments are historically performed on congenic C57BL/6J background strains. This is due to the fact that this strain is the most ‘drug preferred’ and ‘accepting’ strain of mice known (Seale and Carney, 1991; Owen et al., 1997). Therefore, we suggested, that for future studies, mixed background mice (C57BL/6J x 129S1/Sv) should be backcrossed to a pure, congenic C57BL/6J background. 10 generations of backcrossing would be required to generate >99% C57BL/6 congenic mice.

4.5.3 Compound 22 Alone does not Stimulate Locomotor Activity in WT and Taar1-KO mice

Next, the effects of compound 22 alone were assessed on the Taar1-KO mice. When compound 22 was injected into both WT and Taar1-KO mice, no significant changes in basal locomotor activity was observed in these mix background mice (section 3.5.3, Figure 3.17). This observation was similar to our previous experiments with the congenic C57BL6/J mice indicating that compound 22 alone does not stimulate locomotor activity

4.5.4 Conclusion of the in vivo Studies with Compound 22

In the initial in vitro assays, compound 22 appeared to be a potential weak antagonist for TAAR1. The favourable predicted chemical properties of compound 22 led to the hypothesis that compound 22 would cross the blood brain barrier and have effects in vivo. Indeed, our experiments confirmed that compound 22 was acting centrally and potentiating the locomotor stimulating effects of amphetamine and cocaine in wild type animals.

Since Taar1-KO mice show potentiated locomotor response to amphetamine and cocaine, we hypothesized that compound 22 effects were consistent with TAAR1 antagonism in WT mice.

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However, contrary to this hypothesis, we observed that compound 22 also potentiated cocaine- and amphetamine-mediated locomotor activity in the Taar1-KO mice, indicating that the in vivo locomotor responses of compound 22 were TAAR1 independent. The main conclusion from this portion of our study was that compound 22 potentiated the locomotor stimulating activity of amphetamine and cocaine through a TAAR1 independent mechanism. In order to determine the mechanism of compound 22 action, compound 22 was sent for screening through the psychoactive drug screening program (PDSP).

4.6 PDSP Screen showed that Compound 22 Binds to Monoamine Transporters and Sigma Receptors 4.6.1 PDSP Binding Studies and Results

At PDSP, two screens were performed in order to determine potential pharmacological targets of compound 22 in the brain. First, binding studies were completed on a series of targets that are expressed in the brain. The list of targets that were tested can be found in supplemental table 1. This first binding screen showed that compound 22 had triple digit nM affinity for sigma 1 and 2 receptors, and single digit µM affinity for SERT, NET, and DAT (section 3.5.5). All of these identified targets for compound 22 have the potential to mediate the behavioural results we observed in vivo (see section 4.6.4 for a breakdown of these targets). However, the first screen performed was not extensive, omitting a number of targets (see table 4.2) that could also be responsible for the behavioural responses observed with compound 22 (see section 4.8). Even further, some of negative targets that were identified for compound 22 binding could also potentially explain the observed behaviour results (see section 4.7). The implication of these targets will be discussed further below.

4.6.2 Functional GPCR Assay Showed Compound 22 does not Activate GPCRs

Lastly, PDSP also screened compound 22 against all 320 non-olfactory GPCRs using a Tango assay, a functional assay that quantifies GPCR activation through β-arrestin recruitment (Kroeze et al., 2015). The initial screen showed that compound 22 was able to activate the dopamine D2 receptor (section 3.5.5). Follow-up experiments performed by PDSP and our lab found this result to be a false positive. Indeed, using BRET based β-arrestin recruitment to the dopamine D2 receptor we found that compound 22 not recruit β-arrestin to the dopamine D2 receptor (Figure

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3.18). In accordance with this observation, a dose response for compound 22 was also done in the Tango assay by PDSP (Supplemental Figure 2), as well as dopamine D2 activation of the Gαi pathway, with the use of the glo-sensor assay. In both of these experiments performed by PDSP, no response to compound 22 was observed. While the secondary screens were negative for dopamine D2 receptor activation, the initial hit remains intriguing and tantalizing.

Due to the fact that all of the initial screens performed at PDSP were of an automated nature, it stands to reason that experimental error (i.e. pipetting errors) would be unlikely to lead to a false positive. Therefore, it is possible that other variables contributed to the hit on the dopamine D2 receptor. For instance, the preparation of compound 22 that was used for the screens was from a dissolved stock of in DMSO. By comparison, the dose response studies done by PDSP and our lab, were done with freshly prepared compound 22 (still in DMSO). Additionally, in the Tango assay, the assay plates containing the transfected cells are incubated with drug overnight. Therefore, it is possible that compound 22 could have 1) degraded while in storage for the primary screen, and 2) undergone further degradation while being incubated overnight. Thus, it is possible that a degradation product of compound 22 may actually be the active component that mediates the D2R activation seen with the Tango assay, as well as potentially our in vivo results. Finally, the ability for compound 22 to antagonize receptors in the Tango assay was not assessed. It is possible that compound 22 is an inverse agonist or antagonist for some of the 320 tested GPCRs.

In summary, using the Tango assay performed by PDSP, compound 22 does not appear to activate any GPCRs that were tested. Although an initial hit for activation of the dopamine D2 receptor was found, subsequent dose response studies indicated that this hit was a false positive.

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Table 4.1 PDSP Targets that were not tested Target 5-HT4 Imidazoline 1 A1 KA A2 M3D A2A M4D A2B mGlur2 A2B2 mGluR3 A2B4 mGlur4 A3B2 mGlur5 mGluR5_Guinea A3B4 pig A4B2 mGluR5_RatBrain A4B2** mGlur6 A4B4 mGluR7 A7 mGluR8 A7** NK-1 B2 NOP NR2B CB1 NTS1 CB1 H NTS2 CB2 EP1 PKCalpha EP2 PKCbeta EP3 PKCdelta EP4 PKCepsilon GABA a1 PKCgamma GABAa a2 Smoothened GABAa a3 Channel GABAa a5 V1A GABAa a6 V1B GABAB V2 HCA2 VMAT1 HERG VMAT2 HERG binding Y2

** Represents splice variants

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4.6.3 Compound 22 Does Not Effect Dopamine Uptake

Based on the studies done by PDSP, the only targets that compound 22 appeared to bind to were the three monoamine transporters, along with the sigma 1 and sigma 2 receptors. Based on these results, compound 22 disruption of dopamine uptake by DAT was next assessed. Using a fluorescent dopamine uptake assay, compound 22 did not block dopamine uptake. It is possible that binding results of PDSP could be due to compound 22 binding to an allosteric site of DAT that does not alter dopamine uptake (Janowsky et al., 2016).

The in vivo results presented in this thesis paint an interesting picture of the mechanism of compound 22. Based on predicted chemical properties, it was expected that compound 22 would cross the blood brain barrier. Our in vivo experiments showed that indeed, compound 22 was acting centrally by potentiating cocaine and amphetamine induced locomotor activity. However, further experiments showed that these in vivo effects were not mediated by TAAR1. Therefore, these studies posed the following question: What is the mechanism of action compound 22 and how does it mediate its in vivo effects. In this section, several receptor systems will be reviewed based on how they affect dopamine transmission in the brain and whether or not these systems could be potential mechanisms of action for compound 22.

4.6.4 PDSP Positive Hits and Their Ability to Effect Dopamine Signalling

In this section, PDSP positive hits for compound 22 will be reviewed. Compound 22 was shown to have low affinity for NET, DAT, and SERT; as well as moderate affinity for sigma 1 and sigma 2 receptors. Focus will be placed on these neurotransmitter systems, and pharmacological manipulations of these targets/pathways can potentiate amphetamine and cocaine locomotor stimulation, and whether they could represent the ‘real’ in vivo target of compound 22. In addition, the downstream receptors of NET, DAT, and SERT are also reviewed for their ability to mediate the in vivo results we obtained. Receptors that have been shown in other studies to enhance amphetamine- or cocaine-mediated locomotor activity will be reviewed in this section, while receptors with indirect or unclear effects on dopamine signalling are reviewed and discussed in appendix B.

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4.6.4.1 Dopamine

4.6.4.1.1 Dopamine Transporter (DAT)

The DAT is a transmembrane transporter that is expressed in pre-synaptic dopaminergic terminals (Nirenberg et al., 1996). The function of DAT is to regulate dopamine homeostasis in the (Torres et al., 2003); a common target for psychostimulants such as cocaine and amphetamine. Psychostimulant changes in dopamine signalling are well known for mediating the enhancement of locomotor activity in rodents (Carlsson, 2001; Greengard, 2001; Beaulieu and Gainetdinov, 2011). Amphetamine is a substrate for monoamine transporters, as well as vesicular monoamine transporters (Schuldiner et al., 1993). Mechanistically, amphetamine enters the pre-synaptic neuron by active transport through monoamine transporters. Once inside the neuron, amphetamine is further transported into vesicles by vesicular monoamine transporters (Rudnick and Clark, 1993). This action of amphetamine disrupts the uptake process for monoamines, resulting in a displacement of neurotransmitters from vesicles to the cytoplasmic space, followed by a reversal of monoamine transporters (i.e. DAT), leading to the release of monoamines into the synapse (Jones et al., 1998).

Cocaine, on the other hand, is a blocker of monoamine transporters, binding primarily to the dopamine, serotonin, and norepinephrine transporters (Ritz et al., 1990; Andrews and Lucki, 2001). Cocaine-mediated increases in locomotor activity involve the elevation of striatal dopamine levels through increases in dopamine transmission, and subsequent activation of dopamine receptors (Di Chiara, 1995; Neisewander et al., 1995; Filip and Siwanowicz, 2001). In addition, cocaine has been shown to elevate the tonic and phasic firing rates of dopamine neurons (Venton et al., 2006; Koulchitsky et al., 2012). It was later discovered that cocaine-mediated increases in norepinephrine, via blocking of reuptake through NET, activated α1AR receptors located on presynaptic dopamine neurons, is mediated by the decreased activity of small calcium-activated potassium channels (SK channels) (Goertz et al., 2014).

Similar to cocaine, amphetamine was also found to increase the firing rate of dopamine neurons through the activation of the α1AR on dopamine neurons, through amphetamine-mediated release of norepinephrine (Shi et al., 2000). Based on these studies, it is clear that amphetamine and cocaine increase dopamine release in the striatum to induce locomotor activity. While this thesis showed that compound 22 did not induce significant locomotor stimulation on its own (section

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3.4.1.3 and 3.5.3), PDSP studies with compound 22 showed single digit µM affinity for DAT. However, uptake studies indicated compound 22 did not block DAT uptake. Nonetheless, it is possible that compound 22 could be acting as an allosteric modulator of DAT. Previous studies have discovered adenine nucleoside derivatives acting as DAT allosteric modulators, that enhance the binding of known DAT ligands to DAT (Janowsky et al., 2016). Unfortunately, experiments investigating dopamine uptake in the presence of compound 22 showed that compound 22 did not alter cocaine-mediated blocking of dopamine uptake. Therefore, based on these data, it is unlikely compound 22 is acting on the dopamine transporter.

4.6.4.2 Serotonin

4.6.4.2.1 Serotonin Transporter

Based on PDSP data, another potential hit for compound 22 is SERT. Similar to DAT, SERT acts as a regulator of 5-HT levels within the synapse, by transporting synaptic 5-HT into the pre- synaptic neuron (Blakely et al., 1991). Changes in serotonergic signalling have been shown to regulate locomotor activity, by modifying dopamine signalling in the striatum. However, selective serotonin reuptake inhibitors (SSRI) do not lead to an increase in locomotor activity in the presence of cocaine or amphetamine in rats. Nonetheless, and , both SSRIs, can potentiate the stimulatory effects of amphetamine (Sills et al., 1999a; b). Additionally the SSRIs, fluoxetine and , can also enhance the stimulatory effects of cocaine (Herges and Taylor, 1998; Bubar et al., 2003; Fletcher et al., 2004). In contrast, other SSRIs, such as , did not yield locomotor potentiation with cocaine or amphetamine (P Fletcher et al., 2004). These conflicting results of SSRI action on amphetamine and cocaine locomotor potentiation were found to be caused by pharmacokinetic effects. In an experiment where rats were depleted of serotonin, via the injection of 5,7-dihydroxytryptamine, fluoxetine was still able to potentiate the locomotor stimulating effects of cocaine. Further analyses found that fluoxetine increased cocaine concentration in the brain by preventing cocaine metabolism by cytochrome P450 2B and 3A family (Fletcher et al., 2004). A similar mechanism has been proposed for fluoxetine-mediated potentiation of amphetamine-mediated locomotion (Sills et al., 1999a). While SSRI-mediated effects on psychostimulant-mediated locomotor stimulation remains unclear, therefore, the inhibition of SERT should not yield an increase in locomotor activity in the presence of cocaine or amphetamine. It is important to note that compound 22 could act in a similar fashion to fluoxetine, and inhibit cytochrome P450 , increasing the local concentrations of

108 amphetamine and cocaine in the brain. This would ultimately lead to increased locomotor effects in response to psychostimulants.

4.6.4.2.2 5-HT Receptors

While PDSP did not show compound 22 to bind to 5HT receptors (section 3.5.4), it is possible for serotonergic ligands to enhance cocaine- or amphetamine-mediated locomotor activity. The 5-HT family of receptors are the largest family of GPCRs, consisting of seven classes (Family members: 5-HT 1-7) and comprised of at least 15 subtypes (Hoyer et al., 2002). 5-HT receptors are abundantly expressed throughout the brain (Di Matteo et al., 2008). In vertebrates, 5-HT containing neurons are expressed in the in the brain stem, where the dorsal raphe nuclei innervate the basal ganglia (Dahlstrom and Fuxe, 1964). Specifically, DRN projections are primarily located on dopaminergic and GABAergic neurons in the SNc and striatum (Hervé et al., 1987; van Bockstaele et al., 1993; Moukhles et al., 1997). The major receptors expressed in the striatum, where locomotor activity is regulated, are the 5-HT1A, 5-HT1B, 5-HT2A, and 5-HT2C (reviewed previously [Di Matteo et al., 2008]).

4.6.4.2.2.1 5-HT2A and 5-HT2C

The 5-HT2A receptor is localized primarily in MSN and interneurons in the striatum (Morilak et al., 1993; Ward and Dorsa, 1996). 5-HT2A receptor signalling enhances both dopamine release and synthesis (Schmidt et al., 1992). In accordance with these observations, 5-HT2A antagonists MDL1000907 and SR 46349B reduced amphetamine-mediated dopamine release (Schmidt et al., 1992; Yamamoto et al., 1995; Porras et al., 2002).

The 5-HT2C receptor is found throughout the striatum, with a similar expression profile to 5-

HT2A receptors. 5-HT2C receptors are localized primarily in MSN and interneurons (Ward and

Dorsa, 1996). The effect of 5-HT2C signalling on dopamine appears to be in direct opposition to

5-HT2A effects, where activation of 5-HT2C inhibits dopamine release (Porras et al., 2002; Alex et al., 2005). In accordance with these observations, the 5HT2C receptor antagonist, SB232082, potentiates the locomotor stimulating effects of psychostimulants MDMA, amphetamine, , cocaine, , , and morphine (Fletcher et al., 2006). In contrast, 5-HT2C agonism, via lorcaserin, inhibits cocaine-induced locomotor activity (Harvey-

Lewis et al., 2016). Mechanistically, the activation of the 5HT2C receptors reduces firing rate of

109 dopaminergic neurons in the VTA (Millan et al., 1998; Di Giovanni et al., 1999; Di Matteo et al., 1999, 2002). These results indicate that compound 22 could mediate its effects through either

5-HT2C or 5-HT2A specific mechanisms.

4.6.4.2.2.2 Serotonin Receptor Conclusion

In summary, 5-HT is important in the regulation of dopamine signalling in the striatum. Based on the results presented in this thesis, it is plausible that compound 22 could be increasing 5-HT levels in the basal ganglia by blocking SERT. However, the binding and functional studies by PDSP showed that compound 22 did not bind or activate any of the 5-HT receptors, indicating compound 22 activity at these receptors is unlikely to mediate the in vivo effects observed. However, it remains possible that compound 22 is an inactive precursor. If an active metabolite for compound 22 is mediating the in vivo effects observed, it is possible that this metabolite could be acting on the serotonin system.

4.6.4.3 Norepinephrine

4.6.4.3.1 Norepinephrine Transporter

Similar to SERT and DAT; NET regulates norepinephrine levels within the synapse by the transport of synaptic norepinephrine into the pre-synaptic neuron (Streby et al., 2015). The role of norepinephrine on dopamine signalling is less clear than the actions of 5-HT on dopamine. There have been no reported studies with norepinephrine reuptake inhibitors potentiating amphetamine- or cocaine-mediate locomotor activity.

4.6.4.4 Sigma Receptors

PDSP results also showed sigma receptors as potential targets of compound 22. The sigma receptors are small membrane bound receptors that are found in the ER. These receptors were first reported in 1976, and were originally thought to be a subtype of opioid receptors (Martin et al., 1976). Further characterization using benzomorphans ( selective ligands) classified the sigma receptor family into two receptor subtypes based on their enantioselectivity and size: sigma1 and sigma 2 receptors (Hellewell and Bowen, 1990).

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4.6.4.4.1 Sigma 1 Receptors

The sigma 1 receptor is a single transmembrane protein that is primarily localized in the ER. The sigma 1 receptor is expressed in peripheral tissues (Stone et al., 2006), as well as highly expressed in the brain (Alonso et al., 2000; Hayashi and Su, 2005). The sigma 1 receptor has recently been crystalized (Schmidt et al., 2016). Initial characterization of the sigma 1 receptor revealed that the receptor is a molecular chaperone that can interact with a variety of proteins, including ankyrin (Hayashi and Su, 2001), potassium channels (Aydar et al., 2002; Kourrich et al., 2013), dopamine D1 receptor (Navarro et al., 2010), dopamine D2 receptor (Navarro et al., 2013), opioid receptors (Kim et al., 2010), and DAT (Hong et al., 2017). While the receptor primarily shows ER retention, co-expression of the receptor with other proteins, such as the dopamine D1 receptor, (Navarro et al., 2010) or treatment with sigma 1 receptor agonists (Hong et al., 2017) induce the translocation of the receptor to the plasma membrane.

One of the interesting aspects of sigma 1 receptor pharmacology is the large variety of exogenous ligand classes that bind, with medium to high affinity, to the receptor. These classes include: neuroleptics/antipsychotics (i.e. haloperidol), (i.e. fluvoxamine), antitussives (i.e. ), drugs of abuse (i.e. cocaine and methamphetamine), among a number of others (reviewed in [Cobos et al., 2008]). Furthermore, one of the most studied effects with sigma 1 receptor ligands are their effects on cocaine-mediated locomotor activity. It has been shown that sigma 1 agonists potentiate, while antagonists inhibit, cocaine-mediated behaviour and locomotor activity (Menkel et al., 1991; Matsumoto et al., 2001; Rodvelt, Lever, et al., 2011; Rodvelt, Oelrichs, et al., 2011; Lever et al., 2014a; Hong et al., 2017).

In contrast to its effect on cocaine-mediated responses, sigma 1 receptor agonists have been shown to inhibit amphetamine-induced locomotor activity (Poncelet et al., 1993; Rückert and Schmidt, 1993; Guitart et al., 1998; Skuza and Rogóz, 2006), while antagonists have no effect (Skuza and Rogóz, 2006).

Mechanistically, the sigma 1 receptor is found in both monomeric and homotrimeric complexes. Based on in vitro studies with sigma 1 receptors and DAT, it was found that sigma 1 receptor agonists promote the dissociation of the homotrimeric complex into its active monomers. These monomers then interact with DAT, promoting an outward facing confirmation of DAT that enhances its affinity for cocaine (Hong et al., 2017).

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Based on these studies with the sigma 1 receptor, it is reasonable to assume that compound 22 binding to the sigma 1 receptor, as an agonist, could mediate the potentiation of cocaine-induced locomotor activity. However, we also observed potentiation of amphetamine response with compound 22 and sigma 1 receptor agonists are known to inhibit amphetamine-induced locomotor activity, which casts doubt that compound 22 is acting as a sigma 1 receptor agonist.

4.6.4.4.2 Sigma 2 Receptors

In contrast to the sigma 1 receptor, a lot less is known about the function of the sigma 2 receptor in the brain. Sigma 2 receptor implication spans a wide range of diseases, ranging from cancer to neurodegenerative diseases. Much of the research has focused on the role of sigma 2 receptors in cancer (Wheeler et al., 2000; Crawford and Bowen, 2002; Crawford et al., 2002). The genetic sequence of sigma 2 was only recently discovered, and was found to be the TMEM97. TMEM97 is a membrane protein that resides in the ER, that regulates the sterol transporter NPC1 (Alon et al., 2017). The sigma 2 receptor exists as a membrane protein with four transmembrane domains (Alon et al., 2017). While the library of sigma 2 receptor selective ligands is small, it has been found that non-selective sigma 1/sigma 2 agonists, such as 1,3-di(o-tolyl)guanidine (DTG), potentiated the locomotor effects of cocaine in rats. Meanwhile, DTG had no effect on amphetamine-mediated locomotor activity(Walker et al., 1993; Maj et al., 1996; Nakazawa et al., 1999; Skuza, 1999; Ghelardini et al., 2000). On the other hand, selective sigma 2 receptor antagonists, such as (±)-SM-21, UMB24, and tetrahydroisoquinolinyl benzamidine, attenuated cocaine-induced locomotor activity (Matsumoto et al., 2007; Lever et al., 2014b). While no in vivo studies have been done with selective sigma 2 receptor ligands measuring amphetamine-mediated locomotor activity, it was found that sigma 2 receptor agonists potentiate amphetamine-mediated dopamine efflux in PC12 cells in vitro (Izenwasser et al., 1998; Weatherspoon and Werling, 1999). These in vitro results indicate that sigma 2 receptor agonists would potentiate amphetamine-, and potentially cocaine-mediated locomotor activity in vivo.

Due to the lack of selective sigma 2 ligands, the precise mechanism of sigma 2 enhancement of dopamine release is not known. However, it has been postulated that sigma 2 activation leads to an increase in intracellular calcium, either through an interaction with the plasma membrane bound

L-type calcium channels, or via the ER-bound IP3 ligand gated calcium channels (Zhang and Cuevas, 2002; Cassano et al., 2006, 2009). This increase in intracellular calcium is hypothesized

112 to promote the activation of PKC, and therefore the phosphorylation of DAT, leading to an increase in extracellular dopamine (Derbez et al., 2002).

While there is limited data published on the psychostimulant mediated locomotor activity effects of sigma 2 receptor ligands, the available research points to the activation of sigma 2 as enhancing dopamine transmission in the brain. However, as with the sigma 1 receptors, sigma 2 receptor agonists potentiate cocaine locomotor response, but inhibit amphetamine-induced locomotor response, casting doubt that sigma 2 receptors could mediate the in vivo effects we observed with compound 22.

4.7 Negative PDSP Targets

In this section, we will review the PDSP targets that were tested, but that did not bind compound 22 (table 4.2). Specifically, this section will review potential receptors that could mediate the in vivo results we obtained. Other receptor families and subtypes with indirect effects on dopamine signalling were also reviewed and can be found in appendix B. It is important to note that the adrenergic, serotonin, and dopamine receptors were negative hits in the PDSP screen and have been reviewed previously as potentially viable targets for compound 22 (section 4.6.4).

4.7.1 Cholinergic Receptors

Muscarinic receptors (family: M1-5) have been shown to regulate the release of dopamine in the striatum (Jones et al., 2012). While all five subtypes of muscarinic receptors are expressed in the striatum, the localization is different for each subtype.

4.7.1.1 M1 and M4 Muscarinic Receptors

The M1 and M4 receptors are most commonly expressed in MSN neurons with M4 receptors specifically expressed in MSN neurons expressing substance P (i.e. dopamine D1 expressing MSN) (Bernard et al., 1992; Yan et al., 2001). Muscarinic receptors have been shown to reduce the activity of K+ and Ca2+ channels in MSN (Akins et al., 1990; Uchimura and North, 1990; Howe and Surmeier, 1995), based on the expression profile of the muscarinic receptor subtypes, it is thought that M1 and M4 receptors mediate cholinergic signalling in MSN (Yan et al., 2001). The M1 receptor knockout mice were found not have altered dopamine release in response to muscarinic ligands, indicating M1 signalling can regulate dopamine release (Zhang et al., 2002).

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Using M4-KO mice, it was shown that these receptors are required for the regulation of dopamine release by dopamine neurons through an indirect mechanism (Zhang et al., 2002). M4 expressing MSN neurons project to dopamine terminals from the SNc whereby M4 activation release of

GABA and the subsequent inhibition of dopamine release through the activation of GABAA ionotropic receptors (Bolam and Smith, 1990; Marchi et al., 1990; Sugita et al., 1991; Zhang et al., 2002). It is currently unknown how M1 receptors regulate dopamine release; however, it is possible that they share a similar mechanism to the M4 receptor.

The recent discovery of selective positive allosteric modulators for the M1 and M4 receptors has allowed for pharmacological characterization of these receptors. First, M1 positive allosteric modulators TBPB, AC-260584, and BQCA were shown to inhibit amphetamine-mediated locomotor activity (Jones et al., 2008; Vanover et al., 2008; Ma et al., 2009; Chambon et al., 2011). While there no studies have reported M1 positive allosteric modulators affecting cocaine- mediated locomotor activity, studies have shown allosteric modulators also attenuate cocaine reinforcing and discriminative stimulus (Thomsen et al., 2010, 2012). Furthermore, M4 positive modulators VU0152099, VU152100, VU0467485, and VU0467154; have also been shown to attenuate amphetamine-mediated locomotor activity (Jones et al., 2008; Wood et al., 2017). In addition, VU0467154 and VU152100 also attenuate cocaine-mediated locomotor activity (Dencker et al., 2012; Dall et al., 2017). While no negative allosteric modulators have been published for M1 or M4 muscarinic receptors, in theory negative allosteric modulators for these receptors would potentiate cocaine- and amphetamine-mediated locomotor activity, a result we observed for compound 22. Therefore, it is possible that compound 22 could be acting as a negative allosteric modulator for either M1 or M4 muscarinic receptors.

4.7.1.1.1 Muscarinic Receptor Conclusion

Based on these studies, it is possible that compound 22 could bind to muscarinic receptors. Unfortunately, due to a lack of sub-type selective ligands, it is unclear which subtype would mediate the potentiation of cocaine- and amphetamine-induced locomotor activity.

4.7.2 Opioid Receptors

The opioid receptors (Family: δ 1-2, κ 1-3, and μ 1-3) are GPCRs located throughout the nervous system and mediate (Stein et al., 2003). Opioid receptors are heavily involved in the

114 regulation of dopamine transmission, where activation of δ- and μ-opioid receptors leads to an increase in dopamine release (Spanagel et al., 1990a; b). The activation of the κ-opioid receptor decreases dopamine release (Di Chiara and Imperato, 1988; Spanagel et al., 1990b).

κ-opioid receptors are co-expressed with dopamine D1 expressing MSN (Hurd and Herkenham, 1995; van Bockstaele et al., 1995), as well as pre-synaptic dopamine neurons in the NAc (Svingos et al., 2001). κ-opioid activation inhibits the release of dopamine in the striatum (Di Chiara and Imperato, 1988; Yokoo et al., 1992; Chefer et al., 2005), and κ-opioid agonists inhibit amphetamine- and cocaine-induced locomotor activity (Heidbreder et al., 1993; Gray et al., 1999; Smith et al., 2003). Based on these results, binding to the κ-opioid receptor as an antagonist could be a potential mechanism action for compound 22.

In summary, opioid receptors appear to regulate dopamine signalling in the striatum. Of particular interest is the κ-opioid receptor, due to the fact that activation of this receptor inhibits the locomotor stimulating effects of cocaine and amphetamine. Therefore, a κ-opioid antagonist or inverse agonist would in theory potentiate the effects of cocaine and amphetamine. Therefore, it is possible that compound 22, or an active metabolite, could be a κ-opioid receptor antagonist.

4.8 Targets Not Tested by PDSP

The following section will review some of the receptor systems that were not experimentally tested by the binding studies of PDSP. However, some of these receptor systems have previously been shown to regulate dopamine signalling as well as psychostimulant-mediated hyperactivity. As with previous sections, receptors that have been shown to alter amphetamine- or cocaine-mediated locomotor activity will be reviewed in this section. Other receptor systems and sub-types that may also have indirect effects on dopamine signalling were also considered and a discussion on these systems can be found in the appendix B.

4.8.1 Adenosine Receptors

Adenosine receptors (family: A1, A2A, A2B, and A3 receptors) are a family of receptors expressed primarily in the brain, with A1 and A2A receptors as the primary targets for the physiological effects of adenosine in the brain (Fredholm et al., 2011; Sheth et al., 2014). Of specific interest for our study is the A2A receptor, due to its predominant expression in the striatum (Schiffmann et al.,

2007; Fredholm et al., 2011). A2A receptor activity is important in the regulation of the activity of

115 cocaine and amphetamine in the brain (Ferré et al., 1992, 1997; Ongini and Fredholm, 1996).

Mechanistically, it has been shown that the A2A receptor has mutually antagonistic activities with the dopamine D2 receptor. Both the A2A receptor and the dopamine D2 receptor have been shown to dimerize in vitro, as well as in striatal membrane preparations from rats (Ferre et al., 1991; Yang et al., 1995; Dasgupta et al., 1996; Kamiya et al., 2003). A2A receptor activation decreases the binding affinities of dopamine D2 receptor agonists (Dasgupta et al., 1996). The activation of the

A2A receptor via A2A agonists inhibits amphetamine- and cocaine-mediated behaviours (Turgeon et al., 1996; Ferré, 1997; Rimondini et al., 1997; Baldo et al., 1999; Chen et al., 2001; Knapp et al., 2001; Filip et al., 2006). Conversely, the antagonism of the A2A receptor potentiates amphetamine- and cocaine-mediated behaviours (Casas et al., 1989; Turgeon et al., 1996; Ferré,

1997; Fredholm et al., 1999; Shiozaki et al., 1999). Paradoxically however, the A2A receptor KO mice display an attenuated response to cocaine and amphetamine, a response that cannot be obtained pharmacologically with A2A antagonists (Chen et al., 2000). Given the function of the in regulating psychostimulant behaviours, it is possible that compound 22 antagonism of the adenosine A2A receptor, results in the in vivo effects we observed.

Unfortunately, the A2A receptor was not tested in the original PDSP screen for compound 22. Nonetheless it was tested using the Tango based assay, which showed that compound 22 did not induce β-arrestin recruitment to the A2A receptor and was not an agonist of this receptor (see section 3.5.4, Supplemental Figure 1). However, these results do not preclude the possibility that compound 22 acts as an A2A receptor antagonist, which could explain the behavioural effects we observed.

4.8.2 Glutamate Receptors

Glutamate receptors can be separated into metabotropic (mGluR) and ionotropic receptors. Metabotropic glutamate receptors are part of class C of GPCRs, while ionotropic glutamate receptors are separated into NMDA (N-methyl-D-aspartate), AMPA (a-amino-3-hdroxy-5-methyl- 4-isoxazolepropionic acid), and kainate receptors (Willard and Koochekpour, 2013). While ionotropic glutamate receptors regulate dopamine release (Imperato et al., 1990; Mount et al., 1990; Pierce and Kalivas, 1995; Cachope and Cheer, 2014), their ubiquitous expression throughout the brain prevents selective targeting to exclusively modulate dopamine release (Traynelis et al., 2010). It is thought that glutamate regulation of dopamine release is primarily achieved through

116 mGluR receptors, since high concentrations of ionotropic glutamate receptors agonists are required to effect dopamine release (Imperato et al., 1990; Mount et al., 1990; Pierce and Kalivas, 1995).

While mGluR receptors are expressed throughout the brain, several mGluR subtypes are expressed throughout the basal ganglia and mediate neuronal excitability and synaptic transmission (Marino et al., 2002, 2003). The mGluR family consists of eight subtypes that are separated into three groups based on sequence homology and G-protein coupling (Conn and Pin, 1997). These groups of mGluR receptors include group I (Subtype: mGluR1/5), group II (mGlur2/3), and group III (mGlurR4/6/7/8). mGluR5 receptors (group I) are expressed primarily in the striatum, along with brain regions that are innervated by the striatum (i.e. GPe or GPi/SNr) (Hubert et al., 2001) and with specific expression in the STN and SNc (Beurrier et al., 1999; Awad et al., 2000). The mGluR5 receptors have garnered much interest in their potential role in mediating anti-parkinsonian activity (Dekundy et al., 2006). Indeed, mGluR5 activation in the STN increases the activity of dopaminergic neurons in the SNc leading to increased dopamine release (Beurrier et al., 1999; Awad et al., 2000). In accordance with the fact that mGluR5 signalling regulates dopamine activity, the mGluR5 antagonist, MPEP, attenuates amphetamine- and cocaine-induced locomotor activity in rats (Herzig and Schmidt, 2004; Pietraszek et al., 2004; Gormley and Rompré, 2011) and mice (Mcgeehan et al., 2004). These results with mGluR5 antagonists and the attenuation of amphetamine- and cocaine-induced locomotor activity, indicate that compound 22 could potentially be mediated its in vivo effects by acting as an mGluR5 receptor agonist.

Group III metabotropic glutamate receptors (mGluR4/6/7/8) are expressed predominately in striatal pre-synaptic neurons originating from the cortex, where they act as for glutamate and GABA release (Corti et al., 2002; Matsui and Kita, 2003). Activation of group III receptors reduces synaptic transmission (Wittmann et al., 2001; Matsui and Kita, 2003; Valenti et al., 2003a). While group III receptors do not directly modulate dopamine signalling, mGluR4 signalling in the striatopallidal can reduce STN activation, which reduces dopamine release from the SNc (Valenti et al., 2003b). In accordance with these observations, group III metabotropic agonists inhibit psychostimulant-mediated locomotor activity. Indeed, the nonselective group III metabotropic glutamate receptor agonists, AP4 and ACPT-1, inhibit amphetamine- and cocaine-mediated locomotor activity (Mao and Wang, 2000; David and

117

Abraini, 2003; Pałucha-Poniewiera et al., 2008). These results indicate that compound 22 could potentially be mediated its effects in vivo by antagonizing group III mGluR receptors, however the specific sub-type is not known.

In conclusion, metabotropic glutamate receptors can modulate dopamine signalling in the striatum. Based on the published results in the literature, it appears that mGluR 5 and group III mGluR ligands modulate the locomotor stimulating abilities of both cocaine and amphetamine. Therefore, the potentiation of cocaine- and amphetamine-induced locomotor response by compound 22 could be mediated by the antagonism of group III mGluR receptors or being an agonist for mGluR5.

4.9 Limitations and Future Directions

The literature has shown that TAAR1 is a regulator of dopamine signalling in the striatum. Unfortunately, the in vivo effects of TAAR1 antagonists have not assessed, due to the existence of only one selective TAAR1 antagonist, EPPTB, which has poor pharmacokinetic properties. This thesis attempted to discover novel TAAR1 antagonists through the use of molecular modelling. Our studies discovered novel agonists for TAAR1, as well as potentially low potency antagonists.

Of all the potential antagonists identified, compound 22 was selected for more thorough characterization. Based on the chemical properties of compound 22, which suggest blood brain barrier penetrance, in vivo studies were carried out in order to determine if compound 22 was a TAAR1 antagonist. Results showed that compound 22 enhanced the locomotor stimulating effects of cocaine and amphetamine in WT animals; a result that was hypothesized to be mediated via the antagonism of TAAR1. However, compound 22 enhanced the locomotor stimulating activities of cocaine and amphetamine in the Taar1-KO mice. This indicated that the observed effects were not mediated by TAAR1 antagonism.

In order to determine the in vivo targets for compound 22, the services of PDSP were used to identify binding targets in the brain, along with a functional assay for the 320 non-olfactory GPCRs. The results from PDSP revealed that compound 22 had low triple digit µM affinity for mono-amine transporters (DAT, NET, SERT), as well as triple digit nM affinity for sigma 1 and 2, and activated the dopamine D2 receptor. However secondary follow-up assays identified that original D2R hit was as a false positive. With regards to monoamine transporters, follow-up studies showed that compound 22 did not affect uptake activity of DAT. Therefore, the mechanism by

118 which compound 22 enhances of cocaine- and amphetamine-mediated locomotor activity remains unknown.

4.9.1 Limitations

It is important to note that there are some limitations in the studies presented here. First, the TAAR1 homology model was generated using the human TAAR1 sequence and the subsequent in vitro studies (i.e. TAAR1 functional assay and PDSP screens) were also conducted on the human TAAR1 receptor. However, our in vivo studies were done in mice. While the human and mouse TAAR1 share 76% sequence homology (Borowsky et al., 2001), these structural differences can be sufficient to alter ligand selectivity. For example, the TAAR1 antagonist EPPTB preferentially binds to the mouse TAAR1 receptor (Bradaia et al., 2009). Therefore it is possible that our results from PDSP are indeed true, compound 22 does not bind to any human targets in the brain with high affinity. However, it is also possible that compound 22 could bind to a mouse target in the brain that could mediate the in vivo effects we observed. Future experiments should focus on using one species for determining the mechanism of action of compound 22.

Second limitation of our in vivo studies pertains to the genotype of the Taar1-KO mouse. As mentioned in section 4.5.1-4.5.2, we expected Taar1-KO mice to have a potentiated locomotor response compared to WT littermates when administered with cocaine or amphetamine. However, our studies did not show potentiated locomotor activity when the Taar1-KO mice were administered amphetamine or cocaine. Furthermore, the response of compound 22 in both genotypes (WT and Taar1-KO) were similar. These results therefore put into question whether or not these mice were indeed Taar1-KO mice. While genotyping methods using PCR indicated that these mice are of the correct genotype, additional experiments should be performed to confirm the absence of TAAR1in the knock-out animals. Demonstration of absence of TAAR1 can be achieved in several ways including measuring of TAAR1 mRNA or direct sequencing of the genomic DNA to demonstrate disruption of the single coding TAAR1 exon in the knock out mice.

4.9.2 Potential targets of Compound 22

In the basal ganglia, there are multiple systems that can regulate dopamine signalling. While there are a lot of receptor families reviewed, only a select few can explain the in vivo effects of compound 22. In general, it appears that stimulation of the firing rate of dopaminergic neurons,

119 and subsequent increase in dopamine release in the striatum, results in the potentiation of both cocaine- and amphetamine-induced locomotor activity. The following are proposed as potential targets for compound 22 mediated potentiation of amphetamine- and cocaine-mediated locomotor activity.

1) Via the decrease in cocaine and amphetamine metabolism: pharmacokinetic interaction with cytochrome P450 2B and 3A to decrease the metabolism of amphetamine and cocaine within the brain, therefore increasing their action. This is similar to what has been described for fluoxetine (Fletcher et al., 2004).

2) Via the modulation of dopamine neuron firing rate with compound 22 acting as an antagonist for: κ-opioid, group III mGluRs (including mGluR4/6/7/8), or 5-HT2C receptor; or an agonist for the mGluR5 or 5-HT2A receptor

3) Via the enhancement of post-synaptic dopamine D2 receptor function. For example, compound

22 could be an adenosine A2A receptor antagonist, which has been shown to enhance dopamine D2 signalling and increase motor responses to amphetamine and cocaine.

4) Via the allosteric modulation of M1 or M4 muscarinic receptors: compound 22 could represent a novel negative allosteric modulator of either M1 or M4 receptors, which would be consistent with the observed motor effects.

5) Lastly, the actions of compound 22 could be mediated via an active metabolite. Indeed, it is possible that compound 22 is an inactive precursor that requires metabolism by an unknown cytochrome P450 to produce an active metabolite that mediates the observed in vivo effects. This possibility could explain the limited targets identified by PDSP (only 5 targets) and the negative results from the tango assay (no GPCR identified). If this turns out to be the case, then both the active metabolite of compound 22 and its target would need to be identified.

4.9.3 Future Experiments

To address the proposed mechanisms of action for compound 22, I propose five key experiments as future direction of this project:

120

First, I propose to experimentally assess in vitro if compound 22 is an inhibitor of cytochrome P450 enzymes, which could lead to increase in vivo levels of amphetamine and cocaine. If this result is confirmed, in vivo brain cocaine or amphetamine levels could be quantified following co- injection of amphetamine or cocaine with compound 22, similar to published fluoxetine experiments (Fletcher et al., 2004).

Secondly, electrophysiological studies measuring the firing rate of dopaminergic neurons should be done in mouse brain slices to see if compound 22 enhances the firing rate of dopaminergic neurons. If so, follow-up pharmacological experiments using selective ligands should be completed by selectively blocking or activating some of the targets listed above. For example, if a selective 5-HT2C receptor agonist blocks the effect of compound 22, then we can infer that compound 22’s enhancement of dopaminergic firing rate is mediated via its binding to 5-HT2C. Further in vivo experiments can then be performed in order to confirm the brain slice results. Lastly, in vivo studies can be done with genetic knock-out models similar to the experiments performed in this study with the Taar1-KO mice.

Third, in order to assess if compound 22 activates the adenosine A2A receptor (mechanism 3), quantification of A2A receptor signalling can be performed in vitro. Since the A2A receptor is coupled to Gαs, our BRET cAMP assay can be used to quantify A2A receptor signalling. If compound 22 binds to the A2A receptor, further studies could be conducted in vivo, using selective

A2A ligands, as well as genetic A2A knockout animals in conjunction with cocaine and amphetamine.

Fourth, in order to assess if compound 22 is a negative allosteric modulator for M1 or M4 muscarinic receptors (mechanism 4 above), its effects on modulating M1 and M4 receptor signalling should be assessed in vitro. Using calcium mobilization assays, compound 22 effects on M1 and M4 signalling could be assessed in a similar manner as previously published (Brady et al., 2008; Jones et al., 2008). Similar to our study in this thesis, if compound 22 is found to be a negative allosteric modulator for either M1 or M4 receptors, in vivo validation could be done with the M1- or M4-KO mice as negative controls.

Lastly, in order to assess if a metabolite for compound 22 is mediating the in vivo effects (mechanism 5), studies to discover the metabolic products of compound 22 can be performed. First, compound 22 will be incubated in the presence of microsomes whereby compound 22

121 metabolites will be analyzed using such techniques as high-performance liquid chromatography, liquid chromatography/mass spectrometry, or nuclear magnetic resonance. Once the metabolites for compound 22 are discovered, their biological target can be identified by PDSP in a similar manner as described in this thesis.

4.10 Conclusion

In this thesis, we generated a TAAR1 homology model based on the inactive state β2AR receptor, which allowed us to identify novel agonists and potential antagonists for TAAR1. Further in vivo studies for one of the antagonists (compound 22) showed that compound 22 was able to potentiate amphetamine- and cocaine-mediated locomotor activity. However, these findings were also observed in the Taar1-KO mice, suggesting that compound 22 is not mediating amphetamine- and cocaine-induced locomotor response through TAAR1. In collaboration with PDSP, we attempted to determine the target for compound 22; however, the target for compound 22 remains unknown.

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Appendix

Section A: Results

Supplemental Tables

Supplemental Table 1. Compound 22 binding studies from PDSP: primary screen for compound 22 and subsequent hits (50% cut-off, hits highlighted in red). The primary screen was performed by PDSP as described previously(Besnard et al., 2012). % % Target Target Inhibition Inhibition 5-HT1A 9.3 D3 9.4 5-HT1B -13.5 D4 17.6 5-HT1D 9.7 D5 -6.8 5-HT1E -1.7 DAT 60.5 5-HT2A 2.1 DOR 6.2 5-HT2B 6.7 GABAA 5.2 5-HT2C 18.5 H1 6.3 5-HT3 6 H2 45.2 5-ht5a 15.3 H3 17.8 5-HT6 4.6 H4 -9.8 5-HT7 20.2 KOR -10.2 Alpha1A -13.9 M1 18.3 Alpha1B 12.8 M2 7.1 Alpha1D 11.6 M3 15.5 Alpha2A 32.4 M4 15.9 Alpha2B 22.6 M5 1.4 Alpha2C -4.3 MOR -3.7 AMPA 13.4 NET 93.4 Beta1 -3.5 NMDA -1.7 Beta2 -0.6 PBR 23.1 Beta3 -9.1 SERT 57.3 BZP site 1.1 Sigma 1 93.2 D1 16.1 Sigma 2 78.4 D2 36.7

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Supplemental Table 2. Compound 22 binding studies from PDSP: secondary screen for compound 22 and subsequent Ki values. The secondary screen was performed by PDSP as described previously(Besnard et al., 2012).

Target Ki (nM) Compound 22

Sigma 1 276

Sigma 2 412

DAT 1053.5

SERT 1800

NET 1902

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Supplemental Figures

Supplemental Figure 1. Tango assay screen for compound 22 by PDSP. A dose of 1 µM of compound 22 was screened against 320 non-olfactory GPCRs. The positive control (grey dotted line) for this assay is quinpirole activation of the dopamine D2 receptor. The Tango assay was performed by PDSP as described previously (Kroeze et al., 2015).

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Supplemental Figure 2. Secondary screens compound 22 activation of the dopamine D2 receptor by PDSP. A) Activation of D2 was assayed using the gi glosensor kit (Promega catalog #: E1290) that quantifies Gαi/o activity (ie D2 signalling), the positive control was the D2 agonist quinpirole. B) A dose response of compound 22 in the Tango assay for D2 activation (Kroeze et al., 2015). The positive control was the D2 agonist quinpirole.

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Appendix B: Discussion

Dopamine Receptors

Dopamine receptors (family: dopamine D1-D5) are GPCRs that are classified into two groups, based on their pharmacological and structural similarities: D1-like and D2-like. The D1-like family consists of the D1 and D5 receptors, coupling to the G-protein GαS. The D2-Like family consists of the D2, D3, and D4 receptors and couples to Gαi (Sibley et al., 1993; Missale et al., 1998). In addition, the coding regions of D1-like receptors are intronless, while the D2-like receptors all contain a varying amount of (reviewed in [Missale et al., 1998]). This key genetic difference allows for the existence of splice variants for D2-like receptors. For example, the D2 receptor has two main splice variants, the D2S and D2L (Dal Toso et al., 1989). Genetic studies with D2L-deficient mice show that the D2L receptor is primarily localized post-synaptically, while the D2S receptor is localized pre-synaptically and acts as a dopamine autoreceptor (Borrelli et al., 2000). While it is possible for compound 22 to mediate the observed in vivo effects of amphetamine and cocaine, the studies by PDSP showed that compound 22 did not bind or activate any of the dopamine receptors. A summary of the dopamine receptors is provided below.

Dopamine D1 and D2

The dopamine D1 and D2 receptors are the most characterized of the 5 subtypes of dopamine receptors. Both the dopamine D1 and D2 receptors are expressed in all brain regions that are innervated by dopamine neurons (Meador-Woodruff et al., 1989; Dearry et al., 1990; Mansour et al., 1990; Monsma et al., 1990). Dopamine release in the striatum can regulate both dopamine D1 (i.e. ‘direct’) and D2 (i.e. ‘indirect’) receptor-mediated pathways (see section 1.2.11.1). In accordance with this, dopamine D1 agonists are able to stimulate locomotor activity (Molloy and Waddington, 1985, 1987; Mazurski and Beninger, 1991; Desai et al., 2005). In contrast, dopamine D2 agonists have a biphasic effect, where lower doses have been shown to inhibit basal locomotor activity, while higher doses enhance locomotor activity. (Cabib and Puglisi-Allegra, 1985; Horvitz et al., 2001). Mechanistically, it has been postulated that dopamine D2 autoreceptors are more sensitive to D2 selective agonists when compared to post synaptic receptors in vivo (Skirboll et al., 1979). In accordance with these studies, D1 and D2 antagonists inhibit cocaine-induced locomotor activity (Kita et al., 1999; Chausmer and Katz, 2001). Therefore, given the fact that

166 dopamine D2 and D1 agonists enhance basal locomotor activity, it is unlikely that compound 22 is activating on these receptors. It is possible that compound 22 could be a selective dopamine D2 autoreceptor antagonist; however, no compound exists that selectively targets the dopamine D2 autoreceptor.

Dopamine D3

The dopamine D3 receptor shares many similar pharmacological features with the dopamine D2 receptor (Sokoloff et al., 1990), including a high affinity for dopamine and a low affinity for neuroleptics such as haloperidol. While dopamine D2 expression is found in all major brain regions that contain dopamine projections (Meador-Woodruff et al., 1989; Mansour et al., 1990), the dopamine D3 receptor has a more restrictive expression profile, where the highest expression is found in the basal ganglia (Bouthenet et al., 1991). Specifically, dopamine D3 was found to be highly expressed in the striatum, with lower expression in dopaminergic neurons projecting into the striatum (SNc, VTA, and NAc) (Diaz et al., 2000). It has been proposed that the dopamine D3 receptor acts as an autoreceptor for dopamine release (Sokoloff et al., 1990; Gobert et al., 1996). However, the regulation of dopamine signalling by the dopamine D3 receptor is due to post- synaptic receptor activation. Mechanistically, it is suggested that post-synaptic D3 receptors regulate dopamine release in a negative feedback pathway (Koeltzow et al., 1998). Further evidence of D3 receptor regulation of dopamine release arises from behaviour studies with cocaine and amphetamine and the D3 knockout mouse. Administration of amphetamine or cocaine into the D3 knockout mouse led to potentiated locomotor stimulating effects of these psychostimulants. (Karasinska et al., 2005; McNamara et al., 2006). In accordance with these genetic studies, pharmacological antagonism of D3 with U99194A (Manzanedo et al., 1999) or nafadotride (Sautel et al., 1995) stimulated locomotor activity in rodents. In conclusion, it is unlikely that compound 22 binds to the dopamine D3 receptors, since locomotor stimulating activity of compound 22 was not observed in our studies.

Dopamine D4

Another potential target of compound 22 could be Dopamine D4 receptors which are primarily expressed in the cortex, amygdala, hypothalamus, and pituitary; with limited expression in the basal ganglia (Meador-Woodruff et al., 1994, 1997; Mrzljak et al., 1996). The dopamine D4 receptors are expressed as post-synaptic receptors in the striatum (Meador-Woodruff et al., 1997).

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The exact role that dopamine D4 receptors play in dopamine-mediated signalling is still unclear. For instance, the dopamine D4 receptor-KO (D4-KO) mice show a potentiated locomotor response to cocaine and amphetamine when compared with WT mice (Rubinstein et al., 1997; Katz et al., 2003; Thomas et al., 2007). However, in direct contrast to these in vivo studies, the D4-KO mice have decreased baseline levels of dopamine and show a reduction in amphetamine mediated dopamine release (Thomas et al., 2007). Further pharmacological studies using the D4 antagonists, L-745,870 and U-101387, show that they did not affect amphetamine mediated locomotor activity (Merchant et al., 1996; Bristow et al., 1997). In conclusion, the D4 receptor can be seen to regulate dopamine transmission through both genetic and pharmacological studies. However, the exact role of D4 receptors in dopamine transmission remains unclear and therefore it is unlikely to mediate the effects of compound 22.

Dopamine D5

The dopamine D5 receptor is the least studied of all the dopamine receptors. Dopamine D5 receptors are expressed in several brain regions. Of interest, the dopamine D5 receptor is expressed in the SNr, striatum, and NAc (Khan et al., 2000). Within the striatum, the dopamine D5 receptors are primarily expressed in cholinergic interneurons, with low expression detected in MSN (Rivera et al., 2002; Centonze et al., 2003). Mechanistically, tonic dopamine release can be modulated by cholinergic interneurons, which stimulate dopamine release through the activation of nicotinic acetylcholine receptors on dopamine terminals (Cachope et al., 2012; Threlfell et al., 2012). However, the role of dopamine D5 receptors in these neurons has not been extensively studied. Furthermore, the dopamine D5 receptor knockout (D5-KO) mice do not show altered locomotor responses to cocaine when compared to WT animals, indicating that D5 receptors are not involved in dopamine transmission within the striatum (Karlsson et al., 2008). Therefore, it is unlikely that compound 22 mediates its effects through the dopamine D5 receptor.

Dopamine Receptor Conclusion

In conclusion, while PDSP data showed that compound 22 did not bind or activate dopamine receptors, it is still possible that compound 22, or an active metabolite, may bind to dopamine receptors. However, based on the literature, only agonists of dopamine receptors have been shown to enhance cocaine- or amphetamine-mediated locomotor activity. However, these agonists also stimulated locomotor activity when injected alone, a result not seen with compound 22. Therefore,

168 it is unlikely that compound 22 is mediating the observed in vivo effects through the activation of dopamine receptors.

Serotonin Receptors

As mentioned in section 4.6.4.2.2, 5-HT receptors are expressed within the striatum. While only

5-HT2C receptor ligands have been shown to affect amphetamine- or cocaine-mediated locomotor activity; other 5-HT receptor subtypes have been shown to alter dopamine signalling.

5-HT1A

Within the basal ganglia, the 5-HT1A receptors are found in pre-synaptic serotonergic and glutamatergic neurons in the striatum. Activation of 5-HT1A receptors has been found reduce serotonin release (Gerber et al., 1988) as well as glutamate release in the striatum (Mignon and

Wolf, 2005). Furthermore, 5-HT1A signalling has been shown to enhance locomotor activity (Evenden, 1994; Gualda et al., 2011), without affecting dopamine release in the striatum (Bantick et al., 2005); indicating 5-HT1A stimulation of locomotor activity occurs indirectly to dopamine release in the striatum. Based on these results, it is possible for 5-HT1A selective agonists to mediate the effects of compound 22. However, it should be noted that no research has been published for 5-HT1A ligands and their effects on amphetamine- or cocaine-mediated locomotor activity.

5-HT1B

The 5-HT1B receptor is expressed predominantly on pre-synaptic terminals of neurons that project to the striatum (Sari et al., 1999), as well as post-synaptic neurons of the globus pallidus (Chadha et al., 2000) . In the striatum, 5-HT1B receptors have been found in both pre-synaptic serotonergic (Boschert et al., 1994; Sari et al., 1999) and dopaminergic (Sarhan et al., 1999) terminals. Indeed,

5-HT1B signalling has been shown to inhibit dopamine release in rat striatal slices (Ennis et al.,

1981) and synaptosomes (Sarhan et al., 1999). In contrast to these observations, the 5-HT1B/5-

HT1A receptor agonist RU24969 has been shown to potentiate cocaine-induced locomotor activity

(Parsons et al., 1999), while the 5-HT1B/5-HT1D antagonist GR127935 inhibited cocaine-induced locomotor activity. Conversely to these pharmacological observations, the 5-HT1B-KO mice showed potentiation of cocaine-mediated locomotor activity (Castanon et al., 2000; Bronsert et

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al., 2001). These contradictory results may be due to the multiple sites of expression of the 5-HT1B receptor, resulting in the possible inhibition of dopamine release in an indirect manner. Based on these results, the role of 5-HT1B signalling on amphetamine- or cocaine-mediated locomotor activity remains unclear and contradictory. Nonetheless since pharmacological manipulation of 5-

HT1B affects amphetamine and cocaine response, it is possible that compound 22 or one of its metabolites might affect locomotor activity by acting on 5-HT1B receptors.

Serotonin Receptor Conclusion

In summary, apart from the 5-HT2A and 5-HT2C receptors, the effects of 5-HT receptors on dopamine signalling are unclear. While it is possible that compound 22 or an active metabolite could be binding to any of these subtypes, it is unlikely that signalling through these receptors can potentiate both amphetamine- and cocaine-mediated locomotor activity

Adrenergic Receptors

The adrenergic receptors (also known as adrenoceptors) are separated into three major classes, based on G-protein coupling. The three classes are the α1 (α1A, α1B, α1D), α2 (α2A-C), and β (β1-3) adrenergic receptors (Bylund et al., 1994; Hieble et al., 1995). Compared with dopamine and serotonin, the basal ganglia only receives very sparse innervation from noradrenergic neurons originating from the LC (Swanson and Hartman, 1975). The only adrenergic subtypes to be expressed in the basal ganglia are the α1A, α2A, α2C, and β1 (Swanson and Hartman, 1975; Harris and Aston-Jones, 2003; Goertz et al., 2014).

α1A Receptors

While the α1A receptor shows a broad expression profile in the brain, specifically within the basal ganglia, the receptor is only found to be expressed in the SNc and SNr (Papay et al., 2006). α1AR located on dopamine neurons mediate the increase in firing rate and slow oscillation firing of dopamine neurons upon cocaine administration (Zhou et al., 2005; Goertz et al., 2014).

Meanwhile, α1A antagonists, like prazosin, inhibit amphetamine-mediated locomotor activity (Snoddy and Tessel, 1985; Blanc et al., 1994; Drouin et al., 2002; Vanderschuren et al., 2003). Interestingly, prazosin has no effect on cocaine-mediated locomotor activity (Thiebot et al., 1981; Filip et al., 2001; Vanderschuren et al., 2003) while other studies have shown the opposite (Snoddy

170 and Tessel, 1985; Berthold et al., 1992; Harris et al., 1996; Drouin et al., 2002; Wellman et al.,

2002). The effects of α1A ligands on amphetamine- or cocaine-mediated locomotor activity is unclear, therefore these results indicate that compound 22 would most likely not mediate its effects through α1A specific mechanisms.

α2A and α2C Receptors

α2 receptors are widely distributed throughout the brain, and have been shown to negatively regulate dopamine release from dopaminergic terminals (Trendelenburg et al., 1994; Yavich et al.,

1997; Gobert et al., 2004). Specifically, the α2A receptor is expressed in pre-synaptic dopamine terminals in the striatum, as well as generally throughout the brain (Trendelenburg et al., 1994).

The α2A receptor agonist, clonidine, has been shown to inhibit amphetamine- but not cocaine- mediated locomotor activity (Vanderschuren et al., 2003), while others have shown that clonidine can potentiate cocaine-mediated locomotion (Carey et al., 2008).

In comparison, the α2C receptors are expressed most abundantly in the striatum, , hippocampus, and cortex (Nicholas et al., 1996; Winzer-Serhan et al., 1997; Holmberg et al.,

1999). The α2C receptor is predominantly found in post-synaptic MSN in the striatum (Holmberg et al., 1999) and potentially in the pre-synaptic dopamine neurons (Rosin et al., 1996; Lee et al.,

1998). The effects of α2A and α2C ligands on amphetamine- or cocaine-mediated locomotor activity remain unclear and conflicting. These observations indicate that compound 22 would most likely not mediate its effects through α2A or α2C specific mechanisms.

β1 Receptors

Lastly, the β1 receptors are predominantly expressed in MSN in the striatum (Nahorski et al., 1979;

Waeber et al., 1991). β1 receptor signalling increases the excitability of dopamine D2 receptor expressing MSN via the activation of PKA/DARPP-32 signalling (Hara et al., 2010). Interestingly, β1AR/β2AR antagonist propranolol potentiates amphetamine- but not cocaine-mediated locomotor activity (Harris et al., 1996; Vanderschuren et al., 2003; Bernardi and Lattal, 2012).

Therefore, the role of β1 receptor ligands on amphetamine- or cocaine-mediated locomotor activity remains unclear. These results indicate that compound 22 would most likely not mediate its effects through a β1 specific mechanisms.

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Adrenergic Receptor Summary

Taken together, the role of norepinephrine on psychostimulant-mediated locomotion is not precisely known. Based on the results of the study presented in this thesis, it is plausible that compound 22 could be increasing norepinephrine levels in the brain via binding to NET. Unfortunately, it is not known if blocking the uptake of NET is sufficient to potentiate amphetamine- or cocaine-induced locomotor activity. Lastly, the binding and functional studies by PDSP have shown that compound 22 does not bind or activate any adrenergic receptors, indicating compound 22 activity at these receptors is unlikely to mediate the in vivo effects observed. As stated previously it is possible that compound 22 is an inactive precursor. If an active metabolite for compound 22 is mediating the in vivo effects observed, it is possible that this metabolite could be acting on adrenergic receptors.

Cholinergic Receptors

As mentioned in section 4.7.1, muscarinic acetylcholine receptors are expressed in the striatum. While in vivo research with muscarinic receptors has been limited due to the lack of subtype selective ligands, several muscarinic receptors have been shown to alter dopamine signalling in the brain.

M2, M3, and M5 Muscarinic Receptors

In comparison to the M1 and M4 receptors, the role of M2, M3, and M5 receptors on dopamine signalling are not known. M2 receptors are expressed in cholinergic interneurons in the striatum, M3 expression is limited to enkephalin positive neurons (i.e. dopamine D2 expressing MSN), and M5 receptors are expressed in striatum in the pre-synaptic dopaminergic neurons (Vilaró et al., 1990; Weiner et al., 1990). Much of the knowledge about the function of these receptors in the brain is through the study of genetic knock-outs of these receptors. The M2 receptor knockout mice do not have altered dopamine release in response to muscarinic ligands (W Zhang et al., 2002). Studies of M5-KO mice show that the non-selective muscarinic agonist, , do not have potentiated dopamine release compared to WT mice (Yamada et al., 2001) while studies of the M3-KO mice show enhanced oxotremorine-mediated dopamine release, indicating M3 receptor stimulation, but not M5 inhibits dopamine release (W Zhang et al., 2002). These results indicate that M3 and M5 receptors are potentially important for modulating dopamine signalling

172 in the striatum. However, due to the lack of selective ligands for these muscarinic receptors, it is not known how these receptors affect cocaine- and amphetamine-mediated locomotor activity. Therefore, whether it is difficult to conclude whether compound 22 is a selective ligand for the M2, M3, and M5 muscarinic receptors.

Histamine receptors

Histamine receptors (family: H1-H4) have been shown to regulate dopaminergic signalling in the striatum of rodents (Alfaro-Rodriguez et al., 2013). Of all the histamine receptors, the histamine H3 receptor has the most direct link to modulation of dopamine signalling. This receptor is expressed in presynaptic dopaminergic neurons in the striatum, modulating dopamine release (Schlicker et al., 1993). A wide range of antagonists for the H3 receptor have been reported to inhibit amphetamine-mediated locomotor activity. These antagonists include: thioperamide (Clapham and Kilpatrick, 1994), ciproxifan (Motawaj and Arrang, 2011), ABT-239 (Fox et al., 2004), and BF2.649 (Ligneau et al., 2007). However, other H3 antagonists do not potentiate amphetamine-mediated locomotor activity. These antagonists include GSK-207040 (Southam et al., 2009), JNJ-5207852, JNJ-10181457(Komater et al., 2003). It is postulated that some of the discrepancies between H3 antagonists arise from pharmacokinetic interactions with cytochrome P450 enzymes (Brabant et al., 2009). As with the studies with SSRIs (see section 4.6.4.2.1), histamine H3 receptor ligands could inhibit P450 2B and 3A family to increase the brain concentrations of amphetamine or cocaine (Fletcher et al., 2004). Therefore, it is currently unknown if histamine H3 signalling can affect dopamine signalling in the striatum.

Of the other histamine receptors, only the histamine H1 receptor alters the dopaminergic system. Specifically, H1 antagonists cause elevated levels of dopamine in the striatum (Masukawa et al., 1993; Dringenberg et al., 1998; Suzuki et al., 1999). Furthermore, the H1 receptor antagonist diphenylpyraline stimulates locomotor activity in mice (Oleson et al., 2012). Since compound 22 alone did not stimulate locomotor activity in mice, the histamine H1 receptor is most likely not a potential target for compound 22.

In conclusion, histamine H1 and H3 receptors appear to regulate dopamine signalling in the striatum. It is possible that compound 22, or an active metabolite, could bind to either of these receptors. However, it is important to note that H1 antagonists stimulate locomotor activity, casting

173 doubt that compound 22 could be binding to H1 receptors, since no locomotor stimulation was seen in our studies with compound 22 alone.

Opioid Receptors

As mentioned in section 4.7.2, opioid receptors are heavily involved in regulating dopamine signaling.

μ-opioid receptors are expressed in GABAergic interneurons located in the VTA/SNc, tonically inhibiting dopamine neurons. Activation of μ-opioid receptors leads to an increase in dopamine release from the VTA and NAc (Cui et al., 2014). μ-opioid receptor agonists enhance cocaine- mediated locomotor activity (Smith et al., 2003). Interestingly, μ-opioid receptor selective antagonist, naloxonazine, does not affect cocaine-induced locomotor activity (Rademacher and Steinpreis, 2002), while the μ-opioid-KO mice show decreased locomotor activity in response to cocaine (Chefer et al., 2004). Based on these results, the role of μ-opioid receptors on amphetamine- or cocaine-mediated locomotor activity remains unclear and conflicting. Therefore, compound 22 is most likely not mediating its effects via μ-opioid receptors.

The δ-opioid receptor is expressed in post-synaptic neurons in the striatum, specifically in cholinergic interneurons (Le Moine et al., 1994; Olive et al., 1997). δ-opioid antagonists were shown to attenuate amphetamine but not cocaine-induced locomotor activity in rats (Jones et al., 1993). δ-opioid agonists, SNC80, DPDPE and (+)BW373U86, potentiate the effects of amphetamine and cocaine (Waddell and Holtzman, 1998; Jutkiewicz et al., 2008). Unfortunately, unlike the μ- or κ-opioid in vivo studies, there is less research on the effects of δ-opioid ligands in vivo due to a limited selection of selective δ-opioid ligands (Chefer et al., 2004). Based on these results, the role of δ -opioid receptors on amphetamine- or cocaine-mediated locomotor activity remains unclear. Therefore, we cannot conclude whether compound 22 is mediating its effects via δ-opioid receptors.

Glutamate Receptors

Group I receptors are expressed primarily in the striatum, along with brain regions that are innervated by the striatum (i.e. GPe or GPi/SNr). mGluR1 receptors are specifically found in all MSN and interneurons of the striatum (Gubellini et al., 2004), as well as the presynaptic dopamine

174 neurons originating from the SNc (Smith et al., 2000). Activation of mGluR1 receptors on dopaminergic terminals decreases dopamine release (Zhang and Sulzer, 2003). It is speculated that mGluR1 antagonism could lead to enhanced dopamine release (Marino et al., 2001). However, the mGluR1 receptor antagonist, JNJ16259685, does not affect cocaine-mediated locomotor activity in rats, indicating that mGluR1 ligands may not actually regulate dopamine transmission, as originally hypothesized (Yu et al., 2013). Although mGluR1 is expressed in dopaminergic neurons localized in the SNc, mGluR1 antagonists do not affect cocaine-induced locomotor activity, contrary to the result we observed with compound 22. Therefore, it is unlikely that compound 22 is acting as a mGluR1 antagonist.

Group II metabotropic glutamate receptors (mGluR2/3) are primarily expressed in the striatum within the basal ganglia, with the highest expression in the pre-synaptic glutamatergic neurons originating from the cortex (Lovinger, 1991; Lovinger and McCool, 1995; Battaglia et al., 1997; Cozzi et al., 1997). In addition, mGluR2/3 are expressed in the of dopaminergic neurons innervated from the STN (Wigmore and Lacey, 1998). The role of group II metabotropic glutamate receptors on the regulation of dopamine transmission remains unclear. For instance, the activation of group II metabotropic glutamate receptors expressed in dopamine neurons leads to a reduction of dopamine release (Wigmore and Lacey, 1998). However, administration of the mGluR2/3 agonist, LY379268, enhances dopamine release. In accordance with this observation, the mGluR2/3 antagonist, LY341495, inhibits amphetamine response (Kim et al., 2000; David and Abraini, 2003). However, other studies report that systemic administration of this antagonist (LY341495), or localized administration of group II antagonist EGLU, has no effect on amphetamine-mediated locomotor activity (Cartmell et al., 2000; Mao and Wang, 2000). Given the fact that different studies show different results of the effects of mGluR2/3 ligands on cocaine- or amphetamine-mediated locomotor response, it remains unclear whether compound 22 might be mediating the observed in vivo effects through mGluR2/3.

Cannabinoid CB1 and CB2 receptors

Endocannabinoids are membrane derived lipids that stimulate the cannabinoid family of GPCRs (family: CB1 and CB2 receptors) (Ferré et al., 2010). CB1 receptors are expressed throughout the brain, with highest basal ganglia expression in the striatum. Meanwhile, CB2 receptors are primarily expressed in peripheral organs (Xi et al., 2011). CB1 receptors are found in both pre-

175 synaptic and post-synaptic neurons of the striatum. The activation of CB1 receptors increases the firing rate and burst activity of dopamine neurons in the VTA, and to a lesser extent in the SNc (French et al., 1997; Gessa et al., 1998). Mechanistically, CB1 signalling regulates dopamine release indirectly, through the activity of glutamatergic and GABAergic neurons that innervate the dopamine terminals (Marinelli et al., 2007). Specifically, CB1 signalling in the pre-synaptic GABAergic or glutamatergic terminals reduces the release of GABA and glutamate respectively (Szabo et al., 2002; Melis et al., 2004; Marinelli et al., 2007). Indeed, high levels of CB1 mRNA are found in glutamatergic neurons of the PFC and STN, as well as GABAergic neurons in the SNr and striatum (Matsuda et al., 1993; Marsicano and Lutz, 1999).

While it is clear that CB1 signalling can modulate dopamine release, the role of CB1 receptors in the regulation of locomotor activity is controversial. For instance, the CB1-KO mice (C57BL/6 background) have attenuated basal locomotor activity, as well as an attenuated response to cocaine and amphetamine (Corbille et al., 2007; Li et al., 2009). However, pharmacological studies using CB1 selective ligands do not show an effect on cocaine-induced locomotor activity. Specifically, the CB1 inverse agonist, AM251, does not alter cocaine-induced locomotor activity in mice (Corbille et al., 2007). Furthermore, the CB1 antagonist, , also does not alter cocaine- induced locomotor activity in mice (Blanco-Calvo et al., 2014) or rats (Przegaliński et al., 2005). These in vivo results are in accordance with other studies showing that AM251 and rimonabant do not enhance cocaine-induced dopamine release in the NAc (Caillé and Parsons, 2006; Xi et al., 2006). While CB1 modulates dopamine signalling in the striatum, the effects of CB1 antagonists on amphetamine- and cocaine-induced locomotor activity are unclear. Given these published results, it is unlikely that compound 22 mediates its in vivo effects through the CB1 receptor.

While it has been traditionally thought that CB2 is not expressed in the brain, recent studies have reported low levels of CB2 expression in the rodent brain. CB2 is expressed in the striatum, cerebellum, cortex, hippocampus, and brainstem (Van Sickle et al., 2005; Gong et al., 2006; Baek et al., 2008; Onaivi, 2009). Indeed, CB2 selective agonists, JWH133 and GW405833, potentiate cocaine-induced dopamine release in the NAc, along with the subsequent potentiation of cocaine- mediated locomotor activity (Xi et al., 2011). Based on these findings, it has been postulated that the CB2 receptor is involved in the regulation of dopamine transmission in a yet to be determined mechanism.

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It is clear that CB1, and potentially CB2, regulate dopamine signalling; however, there little evidence for cannabinoid ligands potentiating cocaine- or amphetamine-mediated locomotor activity. Nonetheless, it is possible for compound 22 to bind to these two receptors to mediate our observed in vivo effects.

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Licenses and Copyright

Figures 1.1, 1.2, and 1.3

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For the results section, data and figures were previously published in:

Lam VM, Rodríguez D, Zhang T, Koh EJ, Carlsson J, and Salahpour A (2015) Discovery of trace amine-associated receptor 1 ligands by molecular docking screening against a homology model. Med Chem Commun 6:2216–2223.

The journal of Medicinal Chemistry Communications (Royal Society of Chemistry) explicitly provides permission for use of any material in a thesis or dissertation, as outlined in the excerpt from their website below: