Identification of Novel Sites of Interaction for Α1 Adrenoceptors

Identification of novel sites of interaction for

α1 adrenoceptors

Adrian P. Campbell

A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy

School of Medical Sciences Faculty of Medicine

July 2015 PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet

Surname or Family name: Campbell

First name: Adrian Other name/s: Phillip

Abbreviation for degree as given in the University PhD calendar:

School: School of Medical Sciences Faculty: Medicine

Title: Identification of novel sites of interaction for α1 adrenoceptors

Abstract 350 words maximum: (PLEASE TYPE)

α1 adrenoceptors are three of the nine receptors that bind and respond to the hormones adrenaline and noradrenaline. α1 adrenoceptors mediate a number of physiological responses such as smooth muscle contraction as well as modulating cognition. The high homology between the nine adrenoceptors, as well as other biogenic amine receptors, results in a difficulty in finding highly selective drugs for these receptors. A potential target site for highly selective ligands is the extracellular domain, which has low sequence similarity across the receptors This thesis uses in silico homology modelling and molecular docking to identify and characterise potentially exploitable residues in the extracellular domain of the α1 adrenoceptors. Firstly, D191 in the second extracellular loop of the α1B adrenoceptor was identified in a homology model and shown, by mutagenesis, to have an impact on agonist binding to the receptor, with no effect on subsequent receptor activation. It appears that D191 is contributing direct contact with agonists, even though its position on the extracellular surface of the receptor suggests that it does not form a part of the canonical orthosteric binding site. Following this, a series of bisacridines, 9-aminoacridine moieties conjugated with increasing length methylene linkers, was used as a molecular ruler to investigate the optimum size of a drug to engage in critical contacts with the receptor. The 4-carbon linker was found to be ideal for selective binding, but the 9-aminoacridine based ligands displayed cooperative binding that was subsequently attributed to a bitopic mode of binding that engaged an allosteric site on the receptors. Docking was used, taking advantage of the bitopic mode of binding, to identify residues at the extracellular end of TMII that, when mutated, affected [3H]prazosin dissociation rates, and the magnitude of the allosteric effect of the 9-aminoacridines. All of the residues identified were on the extracellular surface of the receptor and are thought to contribute to the binding/debinding pathway for ligands of the α1 adrenoceptors and other closely related biogenic amine receptors. This structure data can be useful for identification and further development of highly selective, allosteric modulators of the α1 adrenoceptors.

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“Who can say if I've been changed for the better… I have been changed for good”

Glinda the Good Witch

Wicked (Stephen Schwartz)

Contents

Contents ...... vi

Figures ...... xi

Tables ...... xiii

Abstract ...... xiv

Acknowledgements ...... xvi

Publications arising from this thesis ...... xvii

List of Abbreviations ...... xix

Amino Acids ...... xxi

Chapter 1 Introduction ...... 1

1.1 G protein-coupled receptors ...... 1

1.1.1 Classification of GPCRs ...... 2

1.1.2 GPCR structure ...... 3

1.1.2.2 Transmembrane Domain ...... 5

1.1.2.3 Extracellular domain ...... 5

1.1.2.4 Intracellular domain ...... 10

1.1.3 GPCR activation and signalling ...... 11

1.1.4 Dimerisation ...... 15

1.2 Adrenoceptors ...... 17

1.2.1 α1 adrenoceptors ...... 17

1.2.1.2 Ligands of the adrenoceptors ...... 20

1.2.1.3 Activation and signalling ...... 22

1.2.1.4 Cardiovascular α1 adrenoceptors ...... 23

1.2.1.5 CNS α1 adrenoceptors ...... 25

1.2.1.5.1 Protective effects of the α1 adrenoceptor ...... 25 vi

1.2.1.6 Prostatic α1 adrenoceptors ...... 26

1.2.1.7 Selectivity between the biogenic amine receptors ...... 27

1.2.1.8 α1 adrenoceptors as therapeutic targets ...... 28

1.3 Allosteric ligands of GPCRs ...... 29

1.3.2 Allosteric binding site ...... 34

1.3.3 Bivalent ligands ...... 34

1.3.4 Allosteric modulators and bitopic ligands of the α1 adrenoceptors ...... 36

1.4 Receptor theory ...... 38

1.4.1 Binding affinity of orthosteric ligands ...... 38

1.4.2 Cooperative binding ...... 39

1.4.3 Non-competitive binding ...... 39

1.4.4 Receptor activation...... 40

1.4.4.1 Operational model of agonism ...... 40

1.4.5 Allosteric modulators ...... 41

1.5 Computer aided techniques ...... 42

1.5.1 Visualisation ...... 42

1.5.2 Docking ...... 42

1.5.3 Homology modelling ...... 44

1.6 Summary and aims ...... 45

Chapter 2 Methods ...... 46

2.1 Reagents ...... 46

2.2 Buffers ...... 46

2.2.1 Phosphate buffered saline (PBS) ...... 47

2.2.2 HEM binding buffer ...... 47

2.2.3 HC binding buffer ...... 47

2.2.4 TE binding buffer ...... 47

2.2.5 E. coli transformation buffer ...... 47 vii

2.2.6 LB bacteria growth medium ...... 47

2.3 Cell culture...... 47

2.4 Mutagenesis ...... 47

2.5 Transfection for radioligand binding ...... 47

2.6 Membrane preparation ...... 48

2.6.1 Membrane preparation method 1 ...... 48

2.6.2 Membrane preparation method 2 ...... 48

2.7 Radioligand binding ...... 48

2.7.1 Saturation binding ...... 49

2.7.2 Competition binding...... 49

2.7.3 Dissociation kinetics ...... 49

2.8 Transfection for IP accumulation assay...... 49

2.9 IP accumulation assay ...... 50

2.10 Whole cell binding ...... 50

2.11 Data analysis ...... 50

2.12 Docking ...... 52

Chapter 3 An aspartate in the second extracellular loop of the α1B adrenoceptor regulates agonist binding ...... 53

3.1 Introduction ...... 53

3.1.1 Hypothesis ...... 53

3.2 Methods ...... 55

3.2.1 Reagents ...... 55

3.2.2 Mutagenesis ...... 55

3.2.3 Cell culture ...... 55

3.2.4 Transfection, membrane harvesting and radioligand binding ...... 55

3.2.5 Transfection and IP accumulation assays ...... 55

3.2.6 Data analysis ...... 55 viii

3.3 Results ...... 56

3.3.1 Characterisation of receptors by radioligand binding...... 56

3.3.2 Characterisation of competition ligand binding...... 56

3.3.3 Characterisation of receptor activity...... 59

3.4 Discussion ...... 64

Chapter 4 Subtype selectivity of 9-aminoacridines ...... 67

4.1 Introduction ...... 67

4.1.2 Hypothesis ...... 69

4.2 Methods ...... 70

4.2.1 Tissue culture ...... 70

4.2.2 Transfection and membrane harvesting ...... 70

4.2.3 Receptor binding ...... 70

4.2.4 Data analysis ...... 70

4.3 Results ...... 71

4.3.1 WT receptor characterisation ...... 71

4.3.2 Competition binding of 9-aminoacridines ...... 72

4.4 Discussion ...... 77

Chapter 5 Non-competitive effects of 9-aminoacridines ...... 82

5.1 Introduction ...... 82

5.1.1 Hypotheses ...... 83

5.2 Methods ...... 84

5.2.1 Dissociation kinetics ...... 84

5.2.2 IP accumulation ...... 84

5.2.3 Data analysis ...... 84

5.3 Results ...... 86

3 5.3.1 Dissociation of [ H]prazosin from the α1 adrenoceptors ...... 86

5.3.2 9-aminoacridines increase the dissociation rate of [3H]prazosin ...... 88 ix

5.3.3 C9 bisacridine is a non-competitive antagonist of α1A adrenoceptor activation ...... 91

5.4 Discussion ...... 99

Chapter 6 Identification of the allosteric site of the α1A adrenoceptor ...... 106

6.1 Introduction ...... 106

6.1.1 Hypotheses ...... 107

6.2 Methods ...... 108

6.2.1 Docking ...... 108

6.2.2 Mutagenesis ...... 108

6.2.3 Transfection and membrane harvesting ...... 109

6.2.4 Radioligand binding assays ...... 109

6.2.5 Data analysis ...... 109

6.3 Results ...... 110

6.3.1 Docking ...... 110

6.3.2 Mutagenesis ...... 122

6.3.3 Ligand affinities at mutant receptors ...... 123

6.3.4 [3H]prazosin dissociation from mutant receptors ...... 125

6.3.5 Allosteric modulation of α1A adrenoceptor binding kinetics by the acridines ...... 129

6.4 Discussion ...... 133

Chapter 7 General discussion and future directions ...... 139

References ...... 145

Figures

Figure 1.1 Phylogenetic relationship of human GPCRs...... 4 Figure 1.2 Comparison of receptor similarity...... 7 Figure 1.3 Structural similarities and differences of GPCR crystal structures...... 8 Figure 1.4 Inactive and active state GPCR crystal structures...... 13 Figure 1.5 Biogenic amines and synthetic agonists ...... 18 Figure 1.6 Binding pocket of the adrenoceptors...... 19 Figure 1.7 Adrenergic antagonists ...... 21 Figure 1.8 Orthosteric binding site conservation ...... 27 Figure 1.9 Similarity of the extracellular loops of aminergic receptors...... 28 Figure 1.10 Effects of allosteric ligands ...... 30 Figure 1.11 Acridines and quinolines ...... 37

Figure 3.1 Homology model of the α1B adrenoceptor...... 54 Figure 3.2 Competition binding curves for adrenergic ligands...... 57 Figure 3.3 Agonist independent receptor signalling...... 60 Figure 3.4 Agonist associated receptor activation...... 60 Figure 4.1 Acridines ...... 67

Figure 4.2 Bisacridine affinities at central and peripheral α1 adrenoceptors ...... 68 Figure 4.3 Saturation binding of biogenic amine receptors...... 71 Figure 4.4 Subtype selective binding of the 9-aminoacridines ...... 73 Figure 4.5 Competition binding curves ...... 76 3 Figure 5.1 [ H]prazosin dissociation from α1A and α1B adrenoceptors ...... 87 3 Figure 5.2 Increase in [ H]prazosin dissociation rate from the α1A and α1B adrenoceptors in the presence of 100 µM acridines ...... 90 3 Figure 5.3 Dissociation of [ H]prazosin from the α1A adrenoceptor ...... 93 3 Figure 5.4 Dissociation of [ H]prazosin from the α1B adrenoceptor ...... 95 Figure 5.5 Noradrenaline induced total soluble inositol phosphate accumulation ...... 96 Figure 6.1 Representative poses of acridines and quinolines docked into aminergic receptor homology models ...... 116

Figure 6.2 Affinities at WT and mutant α1 adrenoceptors ...... 127 3 Figure 6.3 [ H]prazosin dissociation from WT and mutant α1A adrenoceptors ...... 128 3 Figure 6.4 [ H]prazosin association at WT and mutant α1A adrenoceptors ...... 128 3 Figure 6.5 Modulation of [ H]prazosin dissociation from WT and mutant α1A xi

adrenoceptors by 9-aminoacridines ...... 131 Figure 6.6 Increase in [3H]prazosin dissociation rate in the presence of 9-aminoacridines ...... 132

Figure 7.1 Proposed binding mechanism for the α1 adrenoceptors ...... 141

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Tables

Table 3.1 Saturation Binding ...... 56 Table 3.2 Competition binding ...... 58 Table 3.3 Change in energy of agonist binding ...... 62 Table 3.4 Agonist induced receptor activation ...... 62 Table 3.5 Operational analysis of receptor activation ...... 63 Table 4.1 Competition binding affinities at human aminergic receptors ...... 74 Table 4.2 Competition binding slopes ...... 75 3 Table 5.1 Dissociation rates of [ H]prazosin from the α1A and α1B adrenoceptors ...... 89 Table 5.2 Best-fit values of total soluble IP accumulation ...... 98 Table 6.1 Mutagenesis primers ...... 108

Table 6.2 Interaction of docked, known α1 adrenoceptor antagonists ...... 112 Table 6.3 Interactions of docked acridines ...... 114 Table 6.4 GOLDScore and unweighted GOLDScore components of docked ligands . 118 Table 6.5 Interactions of docked quinolines ...... 120 3 Table 6.6 [ H]prazosin binding at α1A adrenoceptors ...... 124

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Abstract

α1 adrenoceptors are three of the nine receptors that bind and respond to the hormones adrenaline and noradrenaline. α1 adrenoceptors mediate a number of physiological responses such as smooth muscle contraction as well as modulating cognition. The homology between the nine adrenoceptors, as well as other biogenic amine receptors, results in a difficulty in finding highly selective drugs for these receptors. Many clinically used drugs have less than 100-fold selectivity for their target receptor. A potential target site for highly selective ligands is the extracellular domain, which has low sequence similarity across the receptors. This thesis uses in silico homology modelling and molecular docking to identify and characterise potentially exploitable residues in the extracellular domain of the α1 adrenoceptors. Firstly, D191 in the second extracellular loop of the α1B adrenoceptor was identified in a homology model and shown, by mutagenesis, to have an impact on agonist binding to the receptor, with no effect on subsequent receptor activation. D191 appears to be making direct contacts with agonists, even though its position on the extracellular surface of the receptor suggests that it does not form a part of the canonical orthosteric binding site. It is proposed then that D191 is a point of first contact for agonists as they bind to the receptor from the extracellular solvent. Following this, a series of bisacridines, 9-aminoacridine moieties conjugated with increasing length methylene linkers, was used as molecular rulers to investigate the optimum size of a drug to engage in critical contacts with the receptor. The bisacridine with a 4-carbon linker was found to be ideal for selective binding, engaging residues that have previously been identified as important for the selectivity of some antagonists of the α1 adrenoceptor subtypes. Further analysis revealed that the 9-aminoacridine based ligands displayed cooperative binding that was subsequently attributed to a bitopic mode of binding that engaged an allosteric site on the α1 adrenoceptors. Docking was then used, taking advantage of the bitopic mode of binding, to identify residues at the extracellular end of TMII as being the second site of interaction. When the residues at the extracellular end of TMII were mutated, [3H]prazosin dissociation rates were altered, as was the magnitude of the allosteric effect of the 9-aminoacridines. Combined with observations for equivalent residues of the D2 dopamine receptor, it is proposed that this region of the receptors constitutes the binding/debinding pathway for ligands of the α1 adrenoceptors and other closely related biogenic amine receptors. xiv

The observations presented here implicate several residues in the extracellular domain of the α1 adrenoceptor in normal receptor function and as a potential drug binding site. This is the most comprehensive description, to date, of allosteric interactions at the α1 adrenoceptors. The structural data determined here can be useful for identification and further development of highly selective allosteric modulators of the α1 adrenoceptors.

Acknowledgements

Firstly, to my supervisor, Dr. Angela Finch. Thank you for guiding me through a journey that I can only describe as arduous. To my co-supervisor, Assoc. Prof. Renate Griffith, thank you too, for your guidance. To my parents, you have, and will always make sure there is a roof over my head. I cannot imagine the sacrifices you have made. I hope that one day I can pay them back, or pay them forward. To my peers, Tom, Gosia, Manju, Vanni, Erica, Hong, Jon, Tony, Viviane and all my other colleagues. Your company and conversations have helped keep me afloat. To quote Neil Gaiman, “Pain shared, my brother, is pain not doubled but halved.” Joey, I have enjoyed getting to know you immensely. Thank you to Assoc. Prof. Larry Wakelin and Prof. Bill Denny at the University of Auckland for supplying the acridine compounds. Thanks also to Ms. Urmi Kaniz for supplying homology models of the α1 adrenoceptors, and Junli Chen and Karmen Xu for generating some data used in this thesis. To everyone at UNSW who has been gracious enough to share with me their equipment, their resources, their time, knowledge or advice, your contributions to my candidature will not be forgotten.

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Publications arising from this thesis

The papers and abstracts below have been published on work reported in this thesis and the papers can be found bound at the end of this volume. Papers Campbell AP, MacDougall IJA, Griffith R, Finch AM (2014). An aspartate in the second extracellular loop of the α1B adrenoceptor regulates agonist binding. Eur. J. Pharmacol. 733: 90-96.

Chen J*, Campbell AP*, Urmi KF, Wakelin LPG, Denny WA, Griffith R, et al. (2014).

Human α1-adrenoceptor subtype selectivity of substituted homobivalent 4- aminoquinolines. Bioorg. Med. Chem. 22(21): 5910-5916. * Contributed equally

Abstracts Finch AM, Campbell AP, Xu K, Chen J, Griffith R (2015) The role of the extracellular vestibule of the α1A adrenoceptor in orthosteric and allosteric ligand interactions. Poster presented at The Molecular Pharmacology Gordon Research Conference, Ventura, USA, February 2015

Campbell AP, Griffith R, Finch AM (2014) Identifying novel sites of ligand interaction on the α1 adrenoceptors. Poster presented at the ASCEPT-MPGPCR Joint Scientific Meeting, Melbourne, Australia, December 2014

Campbell AP (2013) Identifying origins of affinity, selectivity and allosterism on the

α1 adrenoceptors. Australian Society for Clinical and Experimental Pharmacologists and Toxicologists. Oral presentation at the ASCEPT 2013 Annual Scientific Meeting, Melbourne, Australia, December 2013

Campbell AP, Chen J, Wakelin LPG, Griffith R, Finch AM (2012) Reaching for the loops to improve α1 adrenoceptor subtype selectivity. Presented at the 7th International Meeting of Molecular Pharmacology of G Protein-Coupled Receptors, Melbourne,

xvii

Australia, December 2012

Campbell AP, McDougall IJA, Griffith R, Finch AM (2010) Modulation of ligand binding to the α1B adrenergic receptor: A potential role for the second extracellular loop. International Union of Basic and Clinical Pharmacology. Poster presented at WorldPharma2010, Copenhagen, Denmark, July 2010

xviii

List of Abbreviations

5-HT 5-hydroxytryptamine (serotonin) 9-aa 9-aminoacridine BRET Bioluminescence resonance energy transfer BQCA Benzyl quinolone carboxylic acid CAM Constitutively active mutant cAMP Cyclic adenosine monophosphate CNS Central nervous system CRELD1α Cysteine-rich epidermal growth factor-like domain 1α DEAE dextran Diethylaminoethyl-dextran DMEM Dulbecco’s modified eagle medium ECL Extracellular loop EDTA Ethylenediaminetetraacetic acid EGTA Ethylene glycol-bis(2-aminoethylether)-N,N,N',N'-tetraacetic acid ERK Extracellular signal regulated kinase FBS Foetal bovine serum FRET Fluorescence resonance energy transfer GABA γ-amino butyric acid GOLD Genetic optimisation for ligand docking GPCR G protein-coupled receptor HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid H-Bond Hydrogen-bond IP Inositol phosphate

IP3 Inositol triphosphate mGluR Metabotropic glutamate receptor MAPK Mitogen activated protein kinase NA Noradrenaline NMS N-methyl scopolamine PBS Phosphate buffered saline PDB Protein data bank

xix

PKC Protein kinase C PLC Phospholipase C QNB 3-quinuclidinyl benzilate RMSD Root mean square distance RPM Revolutions per minute SEM Standard error of the mean TM Transmembrane WT Wild type

Amino Acids

Amino acid One letter code Three letter code Alanine A Ala Arginine R Arg Asparagine N Asn Aspartic acid D Asp Cysteine C Cys Glutamic acid E Glu Glutamine Q Gln Glycine G Gly Histidine H His Isoleucine I Ile Leucine L Leu Lysine K Lys Methionine M Met Phenylalanine F Phe Proline P Pro Serine S Ser Threonine T Thr Tryptophan W Trp Tyrosine Y Tyr Valine V Val

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Chapter 1 Introduction

The α1 adrenoceptors are three of the nine receptors that bind and respond to the hormones adrenaline and noradrenaline. The adrenoceptors belong to the G protein- coupled receptor (GPCR) superfamily and are implicated in a number of physiological processes and pathological conditions. Like many GPCRs, they are considered “druggable” targets yet most drugs that target these receptors are limited by their side- effect profile. To develop better therapeutics, unexplored regions of these receptors can be studied to find novel therapeutic targets. The α1 adrenoceptors are therefore candidates for more detailed, structural analysis. 1.1 G protein-coupled receptors GPCRs are a superfamily of transmembrane proteins responsible for the transduction of extracellular stimuli into cellular changes. There are a plethora of stimuli that can interact with GPCRs, including photons, ions and small molecules, peptides and proteins, fatty acids, enzymes and even mechanical force (Zou et al., 2004). GPCRs constitute ~2% of the human genome, are abundantly expressed, and are involved in many vital physiological processes. A ligand binding domain that is accessible from outside the cell, and their control over vital physiological functions make GPCRs ideal targets for therapeutic intervention in human disease.

Some of the most extensively studied GPCRs are rhodopsin, the β2 adrenoceptor and muscarinic acetylcholine receptors. These proteins are all among the first to be characterised by various techniques including their pharmacology (Ahlquist, 1948; Boll, 1876 cited in Marmor et al., 1978; Buckley et al., 1989; Dale, 1914; Hammer et al., 1980; Lands et al., 1967), cloning (Bonner et al., 1987; Bonner et al., 1988; Dixon et al., 1986; Kubo et al., 1986; Nathans & Hogness, 1984) and crystallisation (Cherezov et al., 2007; Haga et al., 2012; Kruse et al., 2013; Palczewski et al., 2000; Rasmussen et al., 2007). Consequently they are frequently used as model receptors for other members of the GPCR superfamily, including the α1 adrenoceptors. Rhodopsin, notably, is unique amongst GPCRs as it is active in its unliganded state and inactivated when covalently bound to its endogenous ligand, 11-cis-retinal (Matsuyama et al., 2010). Information 1

Chapter 1 Introduction

gained from these model receptors can be extrapolated to the α1 adrenoceptors where they share common features. 1.1.1 Classification of GPCRs There are an estimated 802 GPCRs in the human genome (Fredriksson et al., 2003). Given the enormity of the GPCR superfamily, identifying receptor similarity is a useful task that allows observations at one receptor to be extrapolated to multiple, similar receptors as well as understanding differences between receptors. Various methods can be used to evaluate GPCR homology and identify families of closely related receptors. The traditional method of classification uses sequence similarity to evaluate homology. Several attempts have been made using this approach (Bockaert & Philippe Pin, 1999; Kolakowski, 1994). One such system is the GRAFS classification (Fredriksson et al., 2003). This analysis identified 5 main groups of receptors named glutamate, rhodopsin, adhesion, frizzled/taste2, and secretin, after prototypical members of each family (Figure 1.1). Members within each family share common structural or sequence motifs. For instance, members of the glutamate family have large N-termini that form a venus fly-trap like binding pocket, receptors in the frizzled family contain IFL, SFLL, and SxKTL sequence motifs, rhodopsin family receptors contain the DRY and NPxxY motifs, and receptors of the adhesion family appear to be fused to other functional domains such as mucin-like regions at their N-terminus (Fredriksson et al., 2003). The rhodopsin family contains the most members with a total of 701 receptors, 241 of which are non-olfactory receptors (Fredriksson et al., 2003). The olfactory receptors are a sub-group of receptors with promiscuous binding and specificity for odorant molecules (Malnic et al., 1999). The α sub-group of the rhodopsin family contains, amongst others, all of the biogenic amine receptors: the dopamine, serotonin and muscarinic receptors, as well as the 9 adrenoceptors (Figure 1.1). In addition to the three α1 adrenoceptors, are the three β and three α2 adrenoceptors (Figure 1.1). A novel approach to GPCR classification uses ligand, rather than sequence, similarity to compare receptors (Keiser et al., 2007). Databases containing molecules with known protein targets are mined and these molecules are ‘fingerprinted’ for chemical similarity and target receptors are compared based on the similarity of binding molecules (Keiser et al., 2007). Sequence-based classification of proteins typically describes divergent evolution well i.e. it describes receptors which have evolved from a

Chapter 1 Introduction common ancestor. This ‘similarity ensemble approach’ is more amenable to understanding convergent evolution i.e. multiple proteins that have evolved around a single, or a limited number of molecules. For example, this method is able to link the adrenoceptors and phenylethanolamine N-methyltransferase, an enzyme that catalyses the metabolism of noradrenaline to adrenaline (Lin et al., 2013). These proteins are structurally and functionally unrelated, yet both bind the same ligands. An interesting consequence of this evaluation of GPCRs is the reorganisation of receptor similarity within the rhodopsin family (Figure 1.2). For example, the α1 adrenoceptors are still in close proximity to other biogenic amine receptors such as the dopamine and serotonin/5-hydroxytryptamine (5-HT) receptors however the β adrenoceptors are now regarded as some of the least similar receptors to the α1 adrenoceptors (Lin et al., 2013). This implies that the β adrenoceptors have evolved without significant evolutionary pressure to conserve the ligand binding domain however it is not clear why this is the case. This is illustrated by the fact that α1 and β adrenoceptors have been easily discriminated, pharmacologically, since at least 1958 (Powell et al., 1958) and the two receptor subclasses have very few shared ligands, beyond their endogenous agonists.

Conversely, selectivity between α1 adrenoceptor subtypes, or between α1 adrenoceptors and other aminergic receptors, such as the 5-HT and dopamine receptors, is still a challenging task (GlaxoSmithKline, 2011; Groß et al., 1987). These two systems allow receptor similarity to be compared by two different measures, each with their own advantages. The application of one system or the other will differ depending on the receptor property being considered, and each may find relevance in differing circumstances. 1.1.2 GPCR structure Knowledge of receptor structure is fundamental in understanding the interactions between receptors and their ligands as well as the function of these proteins. It can also be an important tool in the rational design and development of drugs (Congreve et al.,

2011). Early cloning and sequence analysis of rhodopsin and the β2 adrenoceptor highlighted a common feature between the two receptors; 7 hydrophobic regions separated by connecting hydrophilic domains of varying length (Kobilka et al., 1987; Nathans & Hogness, 1983). This structure appeared to be common, and exclusive to receptors that signalled through G-protein dependent pathways (Kobilka et al., 1987). X-ray crystallography has thus far yielded 128 publically available crystal structures of

Chapter 1 Introduction

This figure has been removed for copyright purposes. The original image can be found in Fredriksson et al. (2003) Mol Pharmacol 63: 1256-72

Figure 1.1 Phylogenetic relationship of human GPCRs. Classification of human GPCRs by sequence similarity (Fredriksson et al., 2003). Coloured branches define the 5 main families and Greek characters define the four sub- branches of the rhodopsin-like family. Olfactory receptors are excluded for clarity.

Image is adapted from (Huang et al., 2007). Highlighted receptors are the α1 adrenoceptors ( ), β2 adrenoceptor ( ), 5-HT1A receptor ( ), D3 receptor ( ) and rhodopsin ( ).

Chapter 1 Introduction

GPCRs in the protein data bank (PDB, www.rcsb.org/pdb) (Berman et al., 2000), with at least one representative structure from four of the 5 human groups; the adhesion family is still unrepresented by a crystal structure. All reported crystal structures possess 7 hydrophobic α-helices, which are considered to constitute the transmembrane domain of all GPCRs, and connecting hydrophilic domains. The current model of GPCR structure is a transmembrane bundle of 7 α-helices connected by a series of intra- and extracellular loops, an extracellular N-terminus and an intracellular C-terminus (Figure 1.3). This general structure of a transmembrane core is expected to be conserved across all GPCRs however more divergent receptors are predicted to share few common features beyond this structure, as they possess sequences and structures more reflective of their specialised function. 1.1.2.2 Transmembrane Domain The transmembrane (TM) domain is the most structurally conserved region of GPCRs (Figure 1.3B). Despite there being little sequence similarity between the five groups of GPCRs (Fredriksson et al., 2003; Fredriksson & Schioth, 2005) all solved crystal structures fold into the predicted 7 α-helical bundle (Figure 1.3). The conserved transmembrane structure has led to the implementation of universal numbering systems for rhodopsin-like GPCRs (Ballesteros & Weinstein, 1995). Transmembrane residues are numbered in the format “#.##”, where the first number designates the helix i.e. 1-7, and the second number gives the relative position of the residue on that helix. The most conserved residue is numbered 50 and all following or preceeding residues are numbered above or below that. For example, the most conserved residue in helix 6 of rhodopsin-like GPCRs is a proline (Ballesteros & Weinstein, 1995). This residue is designated P2876.50, where the absolute position within that receptor is given, followed by Ballesteros-Weinstein number in superscript. The next, C-terminal residue in the α1A adrenoceptor for example, is a phenylalanine and would be numbered F2886.51, while the preceding, N-terminal residue would be L2866.49. 1.1.2.3 Extracellular domain The extracellular domain of GPCRs is comprised of the N-terminus and three extracellular loops. This domain is largely hydrophilic and solvent exposed. It has been observed that some polymorphisms in the extracellular domain, particularly in the N- terminus can have pharmacological and clinical effects (Levin et al., 2002; Rathz et al., 2002; Small et al., 2003), but compared to other domains, mutations are relatively

Chapter 1 Introduction

This figure has been removed for copyright purposes. The original image can be found in Lin et al. (2013) Nat Meth 10: 140 -146

Figure 1.2 Comparison of receptor similarity. A comparison of GPCR homology as compared by sequence similarity (A), and ligand similarity (B) adapted from (Lin et al., 2013). Aminergic receptors are displayed with blue branches. Highlighted receptors are the α1 adrenoceptors ( ), β2 adrenoceptor ( ), 5-HT1A receptor ( ) and D3 receptor ( ). Rhodopsin, with only one known ligand, was not included in the analysis.

Chapter 1 Introduction

Figure 1.3 Structural similarities and differences of GPCR crystal structures. (A) Crystal structure of rhodopsin (PDB: 1U19) coloured blue (N-terminus) to red (C- terminus). (B, D) Structural alignment of rhodopsin (PDB: 1U19), mGluR1 metabotropic glutamate receptor (PBD: 4OR2) from the glutamate-like family, smoothened receptor (PDB: 4JKV) from the frizzled family, and CRF1R corticotropin releasing factor receptor (PDB: 4K5Y) from the secretin family viewed from (B) the side and (D) extracellularly. Intracellular and extracellular loops and termini have been removed for clarity. (C) Structural alignment showing ECL2 of rhodopsin (PDB 1U19) in green, the β2 adrenoceptor (PDB: 2RH1) in blue and the A2A adenosine receptor (PDB: 3EML) in pink. 8

Chapter 1 Introduction

well tolerated in the extracellular domain of small-molecule rhodopsin-like GPCRs with limited perturbation of receptor expression and function (Dixon et al., 1987; Go et al., 2005). This has often led to the extracellular domain being viewed as linkers between helices with limited importance (Peeters et al., 2011; Wheatley et al., 2012). However, evidence is accumulating highlighting the importance of the extracellular domains. The N-terminus is a highly variable region of GPCRs. Glutamate-like receptors have a large N-terminus, typically several hundred residues long, as this forms a large venus fly-trap binding domain for its ligands (Conn & Pin, 1997). Some larger peptide agonists of the rhodopsin-like GPCRs, such as C5a, interact with the N-terminus to determine selective binding (Kolakowski et al., 1995). In general the N-termini of the rhodopsin-like GPCRs are relatively short and is often a site for glycosylation and involved in receptor trafficking (Akinaga et al., 2013; Hague et al., 2004; Schiöth & Fredriksson, 2005). The first extracellular loop (ECL1) shows little variation between the rhodopsin- like receptors. Over 70% of all rhodopsin-like receptors have 52 amino acids between positions 2.50 and 3.50, as fixed points of reference (Peeters et al., 2011). The #.50 positions are used to account for the precise location of the helix-loop boundary not being exactly known for all receptors. As there are so few amino acids between the top of TMII and TMIII, this loop is often quite tightly constrained and shows little structural diversity between similar receptors (Peeters et al., 2011). The second extracellular loop (ECL2) is the most variable in size and structure (Figure 1.3C). ECL2 of rhodopsin-like GPCRs, measured between residues 4.50 and 5.50, varies between 30 and 201 residues in length (Peeters et al., 2011). ECL2 adopts various conformations in X-ray crystal structures although the conformations are typically conserved in all structures of the same receptor. In rhodopsin, ECL2 forms an anti-parallel β-sheet that forms extensive contacts with the extracellular surface of the transmembrane helices and contributes interactions to the ligand binding pocket

(Palczewski et al., 2000). In the β1 and β2 adrenoceptors, ECL2 forms a short α-helix with an internal disulphide bond that is unique to the β adrenoceptors (Cherezov et al.,

2007; Warne et al., 2008). In the A2A adenosine receptor, ECL2 has little secondary structure and extends away from the transmembrane bundle (Jaakola et al., 2008)(Figure 1.3C). In many receptors, including the 5-HT receptors and muscarinic

Chapter 1 Introduction receptor, ECL2 does not adopt any specific secondary structure (Kruse et al., 2012; Wacker et al., 2013; Wang et al., 2013). Flexibility of the loops is now being considered essential for function (Wheatley et al., 2012). Mutations that restrict the movement of the extracellular loops have been demonstrated to reduce receptor function. Tethering

ECL2 to the top of TMVII in the M2 muscarinic acetylcholine receptor slows association and dissociation kinetics of the antagonist, [3H]N-methyl-scopolamine (NMS), and reduces affinity of NMS and acetylcholine (Avlani et al., 2007). Mutation of ECL2 has also been shown to decrease efficacy or potency of agonists at the muscarinic receptors (Avlani et al., 2007; Scarselli et al., 2007). A general consensus is that flexibility is necessary to allow ligand entry and exit (Avlani et al., 2007), thereby defining affinity, and that flexibility is a requisite to allow conformational rearrangements associated with receptor activation, particularly for the muscarinic receptors which show a contraction of the orthosteric binding pocket upon agonist binding (Kruse et al., 2013). The third extracellular loop (ECL3), measured between positions 6.50 and 7.50, is slightly more variable in length than ECL1, but most receptors in the rhodopsin-like family have short loop lengths between 35 and 45 residues long. ECL3 does not appear to adopt secondary structure, and the short nature of the loop in rhodopsin-like GPCRs would restrict available conformations. The extracellular and intracellular loops (ICL) do not maintain the homology seen for the transmembrane helices (Ballesteros & Weinstein, 1995), and as such are notated as either ECL# or ICL# in superscript, specifying their loop number. 1.1.2.4 Intracellular domain The intracellular domain is responsible for GPCR interaction with effector and regulatory molecules. These effector molecules include, but are not limited to various G proteins, β-arrestins and kinases. Cysteine crosslinking studies and crystal structures of active state GPCRs complexed with G proteins, indicate that the G protein interface consists of residues at the extracellular end of TMIII, V, VI, and VII, ICL2 and 3, and the C-terminus (Hu et al., 2010; Mnpotra et al., 2014; Rasmussen et al., 2011b). ICL2 has been implicated in β-arrestin activation in the 5-HT2C serotonin receptor, Y2 neuropeptide Y receptor and β2 and α2A adrenoceptors by mutagenesis studies, an interaction that is expected to be conserved throughout the GPCR superfamily (Marion et al., 2006). Kinases appear to phosphorylate serine and threonine residues on the

Chapter 1 Introduction intracellular face of receptors fairly non-specifically though ICL3 and the C-terminus are common targets for kinases (Tobin et al., 2008). Specific receptor-effector interactions are not of critical importance to this thesis but it should be noted that different effector molecules can usually be associated with distinct sites on the intracellular face of GPCRs. 1.1.3 GPCR activation and signalling GPCRs are signal transducers. GPCRs interact with an extracellular stimulus and intracellular effectors. These two events, though spatially distinct, occur in a concerted manner that is inseparable from receptor structure. Agonist binding at the extracellular face of the receptor is associated with a structural rearrangement of the intracellular side of the receptor. Fluorescence quenching experiments using various donor-acceptor combinations have previously demonstrated a structural rearrangement of the cytoplasmic end of the transmembrane domain in rhodopsin and the β2 adrenoceptor indicating a widening or spreading of the cytoplasmic face of the receptors (Dunham & Farrens, 1999; Farrens et al., 1996; Gether et al., 1997; Gether et al., 1995; Sheikh et al.,

1996). Crystal structures are now available of rhodopsin, the β2 adrenoceptor and the M2 muscarinic receptor, which are all rhodopsin-like GPCRs, in inactive, active and various intermediate states (Cherezov et al., 2007; Haga et al., 2012; Palczewski et al., 2000; Park et al., 2008; Rasmussen et al., 2011a; Rasmussen et al., 2007; Rasmussen et al., 2011b). The most pronounced and seemingly well-conserved change across all available crystal structures appears to be the outward movement of the intracellular end of TMVI away from TMIII (Figure 1.4) (Rasmussen et al., 2011a; Rasmussen et al., 2011b).

Agonist bound structures in complex with either G proteins or G protein- mimicking antibodies show TMVI moving 11 - 14 Å away from TMIII when compared to inactive structures, creating a large solvent-exposed pocket between the intracellular ends of the helices (Kruse et al., 2013; Park et al., 2008; Rasmussen et al., 2011b). Y7.53 moves into the newly created cavity as do interacting regions of the associated G protein (Rasmussen et al., 2011a). This structural rearrangement demonstrates how the G protein-interacting region of the receptor is made accessible following agonist binding. The degree of movement of TMVI is similar across the three receptors suggesting a similar global activation mechanism, at least within the rhodopsin-like family of GPCRs, to which all of these receptors belong. In contrast, movement at the extracellular end of the receptor is far more subtle

Chapter 1 Introduction

Rhodopsin β2 adrenoceptor M2 muscarinic receptor

Extracellular

Side

Intracellular

Figure 1.4 Inactive and active state GPCR crystal structures. Crystal structures of inactive (pink) and active (green) state rhodopsin (left), the β2 adrenoceptor (centre) and M2 muscarinic receptor (right) showing structural rearrangement of the receptor from the extracellular view (top), side view (middle) and cytoplasmic view (bottom). Conserved residues and residues of note are shown as sticks. PDB ID: 1U19, 3CAP, 2RH1, 3P0G, 3UON, 4MQS, respectively.

Chapter 1 Introduction

(Rasmussen et al., 2011a; Rosenbaum et al., 2011). There is a slight contraction of binding sites with only small deviations of side chains facing the ligand binding site, which is most prominent in the structures of the M2 muscarinic receptor (Figure 1.4). Interaction with G proteins was a defining characteristic of these receptors (Kobilka et al., 1987) and G proteins are the canonical intracellular mediators of GPCR activation. The α subunit of the G protein is the subunit responsible for mediating the canonical signalling pathways. There are four broad classes of Gα subunits: Gq, which signals through inositol triphosphate (IP3), Gs and Gi which stimulate or inhibit cyclic adenosine monophosphate (cAMP), and G12/13, which can mediate cytoskeletal rearrangement (Wang et al., 2006; Wong, 2003). GPCR-protein interactions are not specific. The ability to signal through at least two G protein-dependent pathways has been observed for many GPCRs, including the β2 adrenoceptor (Xiao et al., 1995), the

α2A adrenoceptor (Chabre et al., 1994), the M1, M2 and M3 muscarinic receptors (Offermanns et al., 1994), corticotropin releasing factor receptors (Blank et al., 2003), oxytocin receptor (Favre et al., 2005) as well as others (Wong, 2003) and while these interactions may show preference for a single subtype, it is generally accepted that GPCRs can signal through multiple G proteins (Wong, 2003). It has been more recently observed that GPCRs are also capable of signalling through G-protein independent pathways, using alternate effectors such as β-arrestins (Galandrin & Bouvier, 2006; Gurwitz et al., 1994; Ryman-Rasmussen et al., 2005). It has also been observed that a ligand does not necessarily activate all pathways to the same extent and an agonist of one pathway may be an antagonist or inverse agonist of another pathway (Galandrin & Bouvier, 2006; Galandrin et al., 2008). This preferential coupling to different signalling pathways is termed “signalling bias”. Signalling bias is specific to each agonist of the receptor. Biophysical studies using environmentally sensitive fluorescent or NMR probes, such as bimane (Yao et al., 2006), tetramethylrhodamine (Swaminath et al., 2005) and [19F]trifluoroethanthiol (Rahmeh et al., 2012) or fluorescence resonance energy transfer (FRET) or bioluminescence resonance energy transfer (BRET) donor-acceptor pairs (Drake et al., 2008) to monitor intracellular movement have demonstrated that many GPCRs including the β adrenoceptors (Drake et al., 2008; Ghanouni et al., 2001; Swaminath et al., 2005), the α2A adrenoceptors (Zürn et al., 2009), the V2A vasopressin receptor (Rahmeh et al., 2012), and the cannabinoid receptors (Georgieva et al., 2008) produce a

Chapter 1 Introduction distinct fluorescence profile depending on the bound agonist, and that these are associated with distinct conformations and signalling pathways (Adams et al., 1986; Ghanouni et al., 2001; Rahmeh et al., 2012; Swaminath et al., 2005). Further supporting the theory that each signalling pathway is associated with a distinct receptor conformation is the observation that some receptor mutations are able to enhance or inhibit individual signalling pathways of a receptor with different magnitudes, and ICL2 different direction. At the angiotensin AT1 receptor, the P133 A mutation blunts Gq response, but has no impact on extracellular signal-regulated kinase (ERK) signalling (Gaborik et al., 2003) and at the oxytocin receptor, D1363.49N mutation enhances agonist mediated signalling through the Gq pathway, while reducing signalling through the Gi pathway (Favre et al., 2005). A receptor can thus be considered to have multiple active states which are dictated by the bound agonist.

The importance of this phenomenon is demonstrated by β1 adrenoceptor antagonists (i.e. beta blockers). Carvedilol has been noted as the most effective β blocker available in patients with heart failure (Kopecky, 2006; Poole-Wilson et al., 2003), and carvedilol also displays a unique ability to activate a β-arrestin signalling pathway from β1 adrenoceptors (Kim et al., 2008). In vitro and in vivo models also support this observation, noting that bias towards β-arrestin signalling show increased cardioprotective effects in opposition to stimulation of pro-apoptotic, G protein mediated signalling (Noma et al., 2007; Yoo et al., 2009). This suggests that such pleiotropic signalling may find therapeutic relevance in the future design of novel drugs. Signalling pathways are not a focus of this thesis, however these observations raise a number of important points. A high affinity, selective ligand could still show no clinical efficacy or have side effects if it is not signalling through an appropriate pathway. Therefore, when observing receptor activation, or screening chemical libraries, a valid signalling pathway that is appropriate for the clinical/experimental outcome should be chosen (Kenakin & Christopoulos, 2013). 1.1.4 Dimerisation Glutamate-like GPCRs are known to act as obligate dimers, often covalently linked by disulphide bonds between their large, venus-fly-trap ligand binding domains (Bai et al., 1998; Gurevich & Gurevich, 2008; Romano et al., 1996). Monomers of heterodimeric glutamate-like GPCRs, such as the γ-aminobutyric acid (GABA)B receptor do not form functional receptors and are not trafficked to the cell surface.

Chapter 1 Introduction

Expression of both GABABR1 and GABABR2 subunits is required for a fully functional receptor with high affinity for its endogenous ligand, GABA (Margeta-Mitrovic et al., 2001; White et al., 1998). On the other hand, rhodopsin-like GPCRs are capable of signalling as monomeric functional units. Monomeric β2 adrenoceptors and rhodopsin have been isolated in lipid nanodiscs and are capable of activating their associated signalling pathways (Whorton et al., 2007; Whorton et al., 2008). Despite these receptors being able to function as monomers, there is growing evidence that they can also function as physiologically relevant dimers. Despite the demonstration that β2 adrenoceptors can signal as monomeric units, β2 adrenoceptors have been shown, using BRET, to dimerise at the surface of HEK-293 cells, with dimerisation increasing in the presence of the agonist, isoproterenol (Angers et al., 2000) and coexpression of wild type (WT) β2 adrenoceptors with a mutant β2 adrenoceptor shows functional rescue of the mutant receptor trafficking and pharmacology (Hebert et al., 1998). α1B adrenoceptors have been shown by both BRET and coimmunoprecipitation to form homodimers, and coexpression of receptor-G protein fusion constructs, where one GPCR cannot couple and the alternate G protein cannot couple, showed transactivation across the dimer pair by the agonist phenylephrine (Carrillo et al., 2003) demonstrating not only physical proximity, but also a functional consequence of dimerisation. The major sites of dimer- interaction for the α1B adrenoceptor were postulated to involve TMI (Carrillo et al., 2004; Stanasila et al., 2003) and TMIV (Carrillo et al., 2004). Another study was also able to identify α1 adrenoceptor oligomers by coimmunoprecipitation, but photoaffinity labelling with [125I]arylazidoprazosin only identified monomeric receptors from the same preparations (Vicentic et al., 2002). Endogenous dopamine D2 receptor homodimers can be detected in the brain by photoaffinity labelling and coimmunoprecipitation that show receptors at molecular weights representing monomers, dimers, trimers and even higher order oligomers. Azidophenethylspiperone was found to only bind to monomeric D2 receptors, where other ligands identify higher receptor density in native tissue without discriminating between monomers and oligomers (Zawarynski et al., 1998). Dimerisation interfaces for the D2 receptors have also been attributed to TMI and TMIV (Guo et al., 2005; Guo et al., 2003). The pharmacological effects of dimerisation are complex. For example, heterodimers of δ and µ opioid receptors can also be identified by coimmunoprecipitation where the δ and

Chapter 1 Introduction

µ opioid receptor heterodimers had increased potency to µ agonists in the presence of δ antagonists (Gomes et al., 2004). The dimeric interactions of rhodopsin-like GPCRs appear to be transient in nature.

The M1 muscarinic receptor, and β1 and β2 adrenoceptors have all been studied with single molecule imaging studies using either fluorescently tagged receptors, or fluorescently tagged, slowly dissociating ligands and all show interactions that are more stable than random interactions (Calebiro et al., 2013; Hern et al., 2010). Overexpression does indeed promote dimerisation, however, low expression levels can still distinguish dimeric interactions from chance encounters, further supporting the likelihood that dimers are a physiologically relevant occurrence (Calebiro et al., 2013). The evidence for GPCR dimerisation on at least a physical or functional level is extensive and growing (Chabre et al., 2009; Gurevich & Gurevich, 2008; Kasai & Kusumi, 2014), and while the effects are variable and unpredictable, it is highly likely that higher order signalling units of receptors exist and have physiological relevance. The altered pharmacology of dimeric GPCRs and the demonstrated selectivity of at least one known ligand for monomeric receptors (Vicentic et al., 2002; Zawarynski et al., 1998) potentially presents an aspect that could be exploited in the design of a highly selective ligand. 1.2 Adrenoceptors The adrenoceptors are a family of nine GPCRs that bind and respond to the endogenous hormones adrenaline and noradrenaline (Figure 1.5) with similar low micromolar-high nanomolar affinity. They are expressed in many tissues and cell types throughout the body (Price et al., 1994; Weinberg et al., 1994) where they mediate the effects of adrenaline and noradrenaline.

1.2.1 α1 adrenoceptors

The α1 adrenoceptors are three of the nine members of the adrenoceptor family.

The α1 subfamily is comprised of the α1A (Schwinn et al., 1990), α1B (Cotecchia et al.,

1988), and α1D (Lomasney et al., 1991; Perez et al., 1991) adrenoceptors, all of which have been cloned and identified within the human genome (Schwinn et al., 1995). The

α1 adrenoceptors can be defined pharmacologically by selective binding of the agonist phenylephrine (Minneman et al., 1994) and the antagonist prazosin (Bylund et al., 1992;

Shibata et al., 1995; Uhlen et al., 1994) as well as signalling via the Gq/11 pathway. Phylogenetically, the three receptors are clustered in close proximity in the α subgroup

Chapter 1 Introduction of the rhodopsin family of GPCRs (Figure 1.1). These receptors are classically known to mediate smooth muscle constriction, particularly in the blood vessels (Cauvin et al., 1983), a large component of the ‘fight or flight’ response. They are also expressed in the heart, liver, prostate, kidneys and central nervous system (CNS) (Cavalli et al., 1997; Doze et al., 2011; Faure et al., 1994; Forray et al., 1994; Grupp et al., 1998).

The functional pharmacology of the α1 adrenoceptor sub-family is fairly well described however precise delineation of the function of each of the α1 adrenoceptor subtypes is difficult. While mRNA of individual subtypes can be readily measured, the lack of suitably selective ligands, particularly radio- or fluorescently labelled ligands, has made it difficult to properly characterise the pharmacology of individual subtypes, particularly in vivo (Mustafa et al., 2012; Nalepa et al., 2013; Philipp & Hein, 2004; Piascik et al.,

1994). There is also a lack of adequately specific antibodies for the α1 adrenoceptors (Jensen et al., 2009a). The best evidence for receptor function therefore derives from knockout or overexpression mouse models using WT or constitutively activated mutant (CAM) receptors (Hirano et al., 2006; O'Connell et al., 2003; O-Uchi et al., 2008; Wang et al., 2001).

Noradrenaline Adrenaline Phenylephrine

Octopamine Dopamine 8-OH-DPAT

Phenylethanolamine Histamine Serotonin

Figure 1.5 Biogenic amines and synthetic agonists Endogenous and synthetic structures of the adrenoceptors as well as dopamine, 5-HT and histamine receptors. 18

Chapter 1 Introduction

There is also considerable evidence to support the existence of a fourth, pharmacologically defined α1L adrenoceptor. The α1L adrenoceptor is pharmacologically similar to the α1 adrenoceptors, but has reduced affinity for some antagonists such as prazosin (Ford et al., 1996). There is no distinct gene for the α1L adrenoceptor, but it is thought to be a functional isoform of the α1A adrenoceptor as its phenotype disappears in α1A knockout mice (Gray et al., 2008; Muramatsu et al., 2008). The α1L phenotype can be observed, particularly in vascular and male urogenital tissues, such as the prostate (Gray et al., 2008; Gray & Ventura, 2006; Muramatsu et al., 1998; Murata et al., 1999; Ohmura et al., 1992; Oshita et al., 1993; Stam et al., 1999), but disappears in cell culture or membrane preparations of the same tissue (Muramatsu et al., 2008; Su et al., 2008). The α1L subtype does not appear to be a product of dimerisation of the α1A adrenoceptor (Ramsay et al., 2004) or splice variants of the receptor (Ramsay et al.,

2004) but may be a product of an α1A adrenoceptor interacting protein, cysteine-rich epidermal growth factor-like domain 1α (CRELD1α) since a positive correlation is observed between CRELD1α expression, and the presence of α1L–type pharmacology (Nishimune et al., 2010).

This figure has been removed for copyright purposes. The original image can be found in Finch et al. (2005) in Perez DM (ed) The Adrenergic Receptors in the 21st Century, Humana Press, New Jersey, NJ, 25-86

Figure 1.6 Binding pocket of the adrenoceptors. Main features of norepinephrine binding pocket for the α1(B) adrenoceptor highlighting π-π interactions with F6.52, which can vary in a receptor dependent manner (blue), H- bond interactions with TMV serines (red), and an ionic interaction with D3.32(orange).

Chapter 1 Introduction

1.2.1.2 Ligands of the adrenoceptors The endogenous ligands of the adrenoceptors are adrenaline and noradrenaline (Figure 1.5). These are small molecules which bind to a fairly well defined pocket ~11 Å below the extracellular surface of the receptor (Figure 1.6). The binding mode of agonists to the α1 adrenoceptors is mostly described by a combination of mutagenesis data and in silico docking. D3.32 is completely conserved throughout the entire biogenic amine family of receptors, and is considered crucial for ligand binding to the α1 adrenoceptors, interacting with the protonated nitrogen of aminergic ligands via a salt- bridge interaction (Porter et al., 1996). Mutation of this residue causes drastic decreases in affinity of agonists and antagonists at all aminergic receptors (Mansour et al., 1992; O'Dowd et al., 1988; Ohta et al., 1994; Strader et al., 1988; Strader et al., 1987b; Wang et al., 1991). The catechol ring of the endogenous agonists forms π- π interactions with various, receptor specific phenylalanines. Mutagenesis studies have demonstrated F6.51 to be of critical importance for this interaction in the α1B and β2 adrenoceptors (Chen et al., 1999; Strader et al., 1989b), while F4.62 ad F5.41 appear to be more important for this interaction in the α1A adrenoceptor (Waugh et al., 2000). Another major contributor to agonist binding is hydrogen bonding (H-bonding) between the hydroxyl groups of the catechol ring (Figure 1.5) and serines in TMV. Mutagenesis has shown the importance of interaction between the hydroxyls and at least one of the conserved serines at positions 5.42, 5.43 or 5.46 (Cavalli et al., 1996; Hwa & Perez, 1996; Liapakis et al., 2000; Strader et al., 1989a; Wang et al., 1991). These interactions appear to be somewhat non-specific as disruption of one interaction , by mutagenesis or chemical modification, can be well tolerated but disruption of two causes a loss in affinity that is far greater than the sum of two individual mutations (Hwa & Perez, 1996). Many of these effects can be recapitulated with adrenaline or noradrenaline derivatives lacking either or both of the catechol hydroxyls, such as octopamine and phenylethanolamine (Hwa & Perez, 1996; Liapakis et al., 2004; Strader et al., 1989a).

α1 adrenoceptor antagonists (Figure 1.7) are typically larger than agonists (MacDougall & Griffith, 2006) and binding interactions extend outside the orthosteric binding site. Antagonists can make contact with residues in ECL2 (Zhao et al., 1996), TMII (Hamaguchi et al., 1996), and TMVII (Waugh et al., 2001). Many of these residues are responsible for not only high affinity binding of antagonists, but also subtype selectivity.

Chapter 1 Introduction

Phentolamine Niguldipine

5-methylurapidil Prazosin

WB4101 Silodosin

Naftopidil Tamsulosin

[125I]HEAT

Figure 1.7 Adrenergic antagonists Structures of selected adrenergic antagonists phentolamine, niguldipine, 5- methylurapidil, prazosin, WB4101, silodosin, naftopidil, tamsulosin, [125I]-HEAT

Chapter 1 Introduction

Molecular dynamics simulations of the M3 muscarinic receptor and β2 adrenoceptor largely support the widely held view that ligands of most rhodopsin-like GPCRs enter the binding cavity from the extracellular solvent through a binding cavity at the top of the receptor (Dror et al., 2011; Kruse et al., 2012). These simulations did, however, produce an unexpected observation; binding was not a single-step process, but involved at least one major, transient binding site, termed the ‘binding vestibule’ at the extracellular site of the receptor (Dror et al., 2011). 1.2.1.3 Activation and signalling

The α1 adrenoceptors are activated by the binding of the endogenous agonists, adrenaline and noradrenaline. At the α1B adrenoceptor, it has been shown that, when bound, the protonated amine of these ligands (Figure 1.5) interacts with the negatively charged, highly conserved D1253.32. In the ground state, D1253.32 is postulated to interact with K3317.36 via a charge-charge interaction and this interaction stabilises the inactive state of the receptor (Porter et al., 1996; Porter & Perez, 1999). The positively charged amine group of the agonist disrupts this interaction, promoting receptor activation (Porter et al., 1996). A similar mechanism has also been demonstrated in rhodopsin (Longstaff et al., 1986; Robinson et al., 1992) and positively and negatively charged residues are highly conserved at these locations throughout the rhodopsin-like family of GPCRs.

When activated, the α1 adrenoceptors are extensively characterised to signal through the Gq pathway (Clerk & Sugden, 1997; Dorn Ii & Brown, 1999; Macrez-

Leprêtre et al., 1996; Wu et al., 1992). Following receptor activation, Gq activates phospholipase C (PLC), generating the second messenger molecules diacyl glycerol and

IP3, which in turn raises intracellular calcium levels (Macrez-Leprêtre et al., 1996;

Morgan & Morgan, 1984). Smooth muscle contraction, one of the main outcomes of α1 adrenoceptor activation, is stimulated by the presence of calcium (Morgan & Morgan,

1984). In addition to the canonical signalling pathway, the α1 adrenoceptors have also been observed to signal through Gi (Barrett et al., 1993), protein kinase C (PKC) (Chaulet et al., 2006; D’Angelo et al., 1997) mitogen-activated protein kinase (MAPK) and ERK phosphorylation (Chaulet et al., 2006; D’Angelo et al., 1997), as well as modulate the permeability of ion channels (Hillman et al., 2009), likely through actions of the Gβγ subunit (Ma et al., 1997). Endogenous and synthetic agonists show signalling bias at the α1A adrenoceptor (Evans et al., 2011) and the measured pathway should thus

Chapter 1 Introduction

always be considered when measuring functional consequences of α1 adrenoceptors.

Dimerisation has been observed to have complex effects on α1 adrenoceptor signalling. For example, the α1D adrenoceptor is frequently described as constitutively internalised, yet coexpression with the α1B adrenoceptors can rescue cell surface expression of the α1D subtype, though this masks the pharmacology of the α1D adrenoceptor (Hague et al., 2006; Hague et al., 2004), but in most cases, dimer- or oligomerisation of the receptors appears to have little or no effect on their pharmacology (Carrillo et al., 2003; Uberti et al., 2003; Vicentic et al., 2002). It has also been reported that coexpression of the CXCR2 chemokine receptor can stimulate increased signalling of the CXCR2 mediated β–arrestin pathway by α1A adrenoceptor agonist, suggesting a transactivation mechanism (Mustafa et al., 2012).

Evidence for dimerisation in the α1 adrenoceptors is not extensive; however there is growing evidence for prototypical members of the rhodopsin like family of GPCRs. The strongest evidence can be seen for the dopamine receptors, where monomers and oligomers can be differentially labelled in native tissues (Zawarynski et al., 1998), expression systems demonstrate trans-activation (Han et al., 2009), and putative dimer interfaces have been identified (Guo et al., 2003). BRET complementation studies in dopamine receptors indicate that dimerisation is a product of the receptors, and not promoted by fluorophore complementation as titration of complementary fluorophores generate expected 1:1 interaction ratios (Guo et al., 2008). The pharmacological consequences of α1 adrenoceptor dimerisation are yet to be fully elucidated, but selective targeting of monomers or oligomers may be a potential therapeutic option in the future.

1.2.1.4 Cardiovascular α1 adrenoceptors

The α1 adrenoceptors have a well-known cardiovascular role. α1 adrenoceptors were first defined by their ability to constrict smooth muscle in response to adrenal extracts (Barger & Dale, 1910). Mice deficient in α1A or α1D adrenoceptors are hypotensive under resting conditions (Rokosh & Simpson, 2002; Tanoue et al., 2002), indicating a role in basal vascular tone with α1A adrenoceptors having a more prominent role in smaller vessels (Methven et al., 2009a; Rokosh & Simpson, 2002) and α1D adrenoceptors being the main contractile mediators in larger, conducting arteries

(Methven et al., 2009b; Tanoue et al., 2002). α1B adrenoceptor knockout mice have normal resting blood pressure, but decreased responses to noradrenaline and

Chapter 1 Introduction

phenylephrine (Cavalli et al., 1997; Zuscik et al., 2001). Thus the α1B adrenoceptor may be more important for maintaining blood pressure when challenged than maintaining basal tone. Compensatory upregulation of the α1A adrenoceptor has been observed in the hepatocytes of α1B adrenoceptor knockout mice (Deighan et al., 2004). In contrast, there is no evidence that other receptor subtypes are upregulated in response to gene deletion in blood vessels, however some functional compensation without changes in protein level or distribution was observed (Methven et al., 2009a; Methven et al., 2009b), suggesting that in blood vessels at least, the three subtypes each have distinct, non- redundant roles.

α1 adrenoceptors are also expressed in human myocardium (Bohm et al., 1988; Bristow et al., 1988; Limas et al., 1989; Steinfath et al., 1992; Vago et al., 1989) where they can mediate positive inotropy (Curiel et al., 1989; Landzberg et al., 1991) and are thought to be cardioprotective (O’Connell et al., 2014; Perez & Doze, 2011). Numerous studies have observed that α1 adrenoceptor antagonism is associated with increased cardiovascular events such as coronary heart disease, myocardial infarction or stroke (Allhat Officers & Allhat Collaborative Research Group, 2000; Bristow et al., 2004; Cohn et al., 2003; Dhaliwal et al., 2009; Swedberg et al., 2002). Mice overexpressing

WT α1A adrenoceptor or CAM α1A adrenoceptor in the heart display enhanced contractility and short term protection from ischaemic injury, pressure overload and infarction (Du et al., 2004; Du et al., 2006; Lin et al., 2001; Rorabaugh et al., 2005), although these mice do die early with evidence of hypertrophy and fibrosis (Chaulet et al., 2006). In contrast, cardiac expression of CAM α1B adrenoceptor or overexpression of WT α1B adrenoceptor in mice results in hypertrophy, particularly after phenylephrine infusion or pressure overload, and higher rates of heart failure following pressure overload, simulating heart failure (Benoit et al., 2004; Grupp et al., 1998; Iaccarino et al., 2001; Lemire et al., 2001; Milano et al., 1994; Wang et al., 2000; Zuscik et al.,

2001) while α1B adrenoceptor knockout mice are protected against agonist induced hypertrophy (Vecchione et al., 2002). In cultured α1A/B adrenoceptor knockout myocytes, transfection of the α1A adrenoceptor is sufficient to protect myocytes from oxidative and cytotoxic induced cell death (Huang et al., 2007). Gq overexpression in the hearts of mice is sufficient to induce hypertrophy (D’Angelo et al., 1997) similar to

α1 adrenoceptor overexpression or activation, suggesting that the Gq pathway is a relevant signalling pathway for the cardiac effects of α1 adrenoceptors (Curiel et al.,

Chapter 1 Introduction

1989; Dorn Ii & Brown, 1999; Landzberg et al., 1991; Steinfath et al., 1992; Turnbull et al., 2003). Taken together, this evidence suggests that the α1B adrenoceptor promotes pathological hypertrophy while the α1A adrenoceptor is somewhat protective in the heart and improves survival and function in failing hearts.

1.2.1.5 CNS α1 adrenoceptors Animal models have also shown observable effects in the CNS. Systemic overexpression of WT or CAM α1B adrenoceptor produces mice with increased frequency of seizures and epileptiform activity in electrophysiological recordings

(Kunieda et al., 2002; Zuscik et al., 2000) whilst an α1B adrenoceptor knockout mouse is resistant to seizures and neuronal degeneration (Pizzanelli et al., 2009). In hippocampal slices, selective α1A adrenoceptor stimulation reduces epileptic burst activity in an in vitro epilepsy model (Hillman et al., 2009). Systemic expression of a CAM α1A adrenoceptor in mice resulted in enhanced memory and learning as assessed by Barnes,

Morris water, and multi-T mazes, while α1A adrenoceptor knockout mice displayed decreased memory and learning in the Barnes maze (Doze et al., 2011). Thus it appears that the α1A adrenoceptor is largely protective in the CNS, while the α1B adrenoceptor impairs normal function. It is not entirely clear why two similar receptors have such different effects, but it may be attributable to different signalling pathways of the two receptors (Chaulet et al., 2006; Hillman et al., 2009; Ma et al., 1997; Mouradian et al.,

1991). Hillman et al. (2009) attribute the α1A adrenoceptor dependent reduction in epileptiform activity to a Gi/o mediated modulation of sodium channels and not the canonical Gq-PLC second messenger pathway. Whether this function is conserved or not in the other members of the α1 adrenoceptor family has not yet been determined, however the ability to modulate membrane polarisation is a very plausible mechanism whereby these receptor can influence epileptiform activity. A beneficial α1 agonist/antagonist in the brain would therefore need not only selectivity, but bias towards the appropriate intracellular signalling pathways.

1.2.1.5.1 Protective effects of the α1 adrenoceptor

In both brain and heart, the protective scenario seems to be mediated by non-Gq second messenger pathway/s; Gq induces pathological hypertrophy in heart, and the Gq pathway does not protect against epileptiform activity in the brain. Clearly there is a necessity for Gq signalling to be kept under strict control to avoid overstimulating messenger pathways to the point of deleterious consequences. Despite the protective

Chapter 1 Introduction

effects appearing to be more strongly associated with the α1A, it is unlikely that the α1B subtype is intrinsically “damaging”, but it would appear that its expression requires tight control to avoid excessive activation. Similarly, the origin of the α1A adrenoceptor’s “protective” action is unlikely to be an inherent quality, otherwise it would be expected to be far more abundantly expressed. Instead it my may simply be a reflection of more/different signalling pathways capable of coupling the α1A adrenoceptor.

1.2.1.6 Prostatic α1 adrenoceptors

Similar to their role in the vascular system, the α1 adrenoceptors have been shown to be responsible for constriction of the prostate (Forray et al., 1994). The α1A adrenoceptor is the most abundant subtype found in the prostate (Faure et al., 1994; Lepor et al., 1995) and is the major contributor of all three subtypes to prostate smooth muscle tone (Lepor et al., 1993; Taniguchi et al., 1997), although more recently the α1L pharmacological subtype has been demonstrated to be the major mediator of adrenaline and noradrenaline induced contraction (Gray et al., 2008; Gray & Ventura, 2006; Leonardi et al., 1997). Despite the reduced affinity of antagonists in the prostate, due to the α1A/L paradox (Section 1.2.1), α1 adrenoceptor antagonists are a common and efficacious pharmacological treatment for the relief of lower urinary tract symptoms associated with benign prostatic hyperplasia (Beduschi et al., 1998; Dhaliwal et al., 2009; Leonardi et al., 1997; Oelke et al., 2009).The major symptom, and complaint, of benign prostatic hyperplasia is difficulty and frequency of urination, caused by obstruction of the urethra by the hyperplastic prostate. Antagonism of the α1 adrenoceptors inhibits contraction of the prostate, thereby alleviating the obstruction and consequent symptoms. There are many high affinity, α1A adrenoceptor antagonists all with clinical efficacy in the relief of symptoms associated with benign prostatic hyperplasia (Beduschi et al., 1998; Lepor, 2007; Lepor et al., 2012; Yoo & Cho, 2012).

Interestingly, α1A adrenoceptor mRNA is upregulated in both hyperplastic prostate and failing right ventricle (Jensen et al., 2009b; Nasu et al., 1996; Walden et al., 1999).

Given the general ‘protective’ nature demonstrated by the α1A adrenoceptor (Perez & Doze, 2011), this upregulation may be a protective response rather than pathogenic, further justifying the use of the α1 adrenoceptors as a therapeutic target. The use of antagonists in the prostate may then seem counter-intuitive, but the complete signalling bias profile of these drugs is quite poorly defined. Non-canonical signalling pathways may actually be responsible for cytoprotection, as has been postulated for α1

Chapter 1 Introduction

adrenoceptors in heart and brain (Section 1.2.1.5.1). Whether the traditional α1 antagonists used in benign prostatic hyperplasia activate or inhibit these pathways is yet to observed. 1.2.1.7 Selectivity between the biogenic amine receptors The design of highly selective drugs is difficult (Leonardi et al., 1997; Takei et al., 1999), particularly for receptor families with many members such as the adrenoceptors. All nine adrenoceptors bind and respond to the hormones adrenaline and noradrenaline. Furthermore, it can be seen that the structures of adrenaline and noradrenaline are also similar to the other endogenous biogenic amines, dopamine, serotonin and histamine (Figure 1.5). Accordingly, the orthosteric binding sites of these receptors are also highly similar to the adrenoceptors (Figure 1.8)(Lin et al., 2013). This high degree of similarity thus explains the difficulties in designing or identifying highly selective ligands, and the off-target effects seen with currently used α1 adrenoceptor drugs and suggests that there is an inherent limit to the selectivity of a drug. Therefore, higher selectivity may be imbued into drugs by targeting less conserved regions of the receptor, such as the extracellular loops (Figure 1.9).

TMIII TMV TMVI TMVII

ɑ1A adrenoceptor AVDVL--LFSAL--LPFFL--LGYLN

ɑ1B adrenoceptor AVDVL--LFSSL--LPFFI--LGYFN

ɑ1D adrenoceptor AVDVL--VFSSV--FPFFF--LGYFN

β1 adrenoceptor SVDVL--IASSV--LPFFL--LGYAN

β2 adrenoceptor SIDVL--IASSI--LPFFI--IGYVN

D3 dopamine receptor TLDVM--IYSSV--LPFFL--LGYVN

5-HT1A serotonin receptor ALDVL--IYSTF--LPFFI--LGYSN Figure 1.8 Orthosteric binding site conservation Alignment of aminergic receptor sequences showing portions of TM helices III, V, VI, and VII that surround the orthosteric binding pocket. Highlighted residues have been shown by mutagenesis to be major contributors to endogenous agonist binding: D3.32, S5.42, F6.51 and Y7.35 (see section 1.2.1.2). 27

Chapter 1 Introduction

1.2.1.8 α1 adrenoceptors as therapeutic targets Adrenoceptors, like many GPCRs, are considered very ‘druggable’ targets (Salon et al., 2011). Indeed they are already directly targeted in the treatment of benign prostatic hyperplasia, for the relief of nasal congestion, and are the target of early generation antihypertensives (Bohm et al., 1988; Lepor et al., 2012; Meltzer et al.). They are also indirect targets of drugs used in the treatment of psychiatric disorders such as monoamine oxidase and noradrenaline transporter inhibitors. This is despite the difficulty in finding highly selective drugs. Drugs with improved selectivity and toxicology profiles may prove to be efficacious treatments in a number of conditions including heart failure, seizure and cognitive disorders.

α1A adrenoceptor antagonists are a common and effective treatment for the treatment of benign prostatic hyperplasia (Hutchison et al., 2007). The α1A adrenoceptor has been recognised as being the predominant subtype in the prostate, and the α1A/L subtype as being responsible for smooth muscle contraction in the prostate (Forray et al., 1994; Lepor et al., 1993). Like most drugs, these antagonists have associated side- effects and it is interaction with other receptor subtypes that appear to mediate the majority of side effects of these α1A adrenoceptor antagonists. Previous generation prazosin-like drugs are high affinity but non-selective antagonists of the α1 adrenoceptors that produce side effects such as orthostatic hypotension, mainly attributable to off-target α1B adrenoceptor binding (Lepor et al., 2012). It is often

ECL1 ECL2 ECL3

ɑ1A adrenoceptor G-YWAFGRVFC RQPAP-EDETICQINEE FFPD-FKPSET

ɑ1B adrenoceptor G-YWVLGRIFC KEPAP-NDDKECGVTEE LFST-LKPPDA

ɑ1D adrenoceptor G-FWAFGRAFC KEPVP-PDERFCGITEE LFPQ-LKPSEG

D3 dopamine receptor GGVWNFSRICC NTT---GDPTVCSISNP HCQT-CHVSPE

5-HT1A receptor N-KWTLGQVTC RTPEDRSDPDACTISKD FCESSCHMPTL

Figure 1.9 Similarity of the extracellular loops of aminergic receptors. The aligned primary sequence of the extracellular domains of selected aminergic receptors are shown, aligned. 28

Chapter 1 Introduction

observed that compounds are either non-selective for the α1 adrenoceptors with selectivity over other aminergic receptors, or selective for the α1A adrenoceptor over the other α1 adrenoceptor subtypes but with affinity for the other aminergic receptors (Leonardi et al., 1997). More recent drugs, such as tamsulosin, naftopidil and silodosin are more selective for the α1A or α1D adrenoceptors over the α1B adrenoceptor minimising orthostatic hypotension side effects, but show increased rates of sexual dysfunction and/or high rates of intraoperative floppy iris syndrome (Lepor, 2007; Oshika et al., 2007; Yamaguchi et al., 2013). Because these effects are not seen with non-selective α1 adrenoceptor antagonists, it has been proposed that they must arise from off-target binding (Hellstrom & Sikka, 2006). Affinity for dopamine or serotonin receptors has been postulated as a potential cause of ejaculation disorders and floppy iris syndrome (Andersson & Wyllie, 2003; Osman et al., 2012) and tamsulosin and naftopidil both have observed low nanomolar affinity for the D2 or D3 and 5-HT1A receptors (Borbe et al., 1991; GlaxoSmithKline, 2011; Leonardi et al., 1997). Thus the search continues for a more highly selective α1 adrenoceptor antagonist.

α1 adrenoceptor agonists may present a novel therapy for heart failure. Unlike β adrenoceptors which are downregulated during heart failure, α1 adrenoceptor expression remains unchanged, or even increased in the human heart (Bohm et al., 1988; Bristow et al., 1988; Hwang et al., 1996; Jensen et al., 2009b). Consequently, the α1 adrenoceptors are capable of eliciting a noradrenaline induced response equal to that of β adrenoceptors in failing myocardium (Skomedal et al., 1997). Considering the general protective effect of α1A adrenoceptors in mouse models (Perez & Doze, 2011), it is possible that a highly selective α1A adrenoceptor agonist may be of use as a positive inotrope for treatment of heart failure.

In the CNS the α1A adrenoceptor also appears (Perez & Doze, 2011) to be protective. Further supporting this theory is a case study of tamsulosin increasing seizure frequency (Iváñez & Ojeda, 2006) in a patient receiving tamsulosin, an α1A adrenoceptor selective antagonist (Martin et al., 1997) as treatment for benign prostatic hyperplasia. Seizure disorders such as epilepsy or Rett syndrome, a genetic disorder that is characterised by seizures and decreased noradrenaline levels in the CNS (Moretti &

Zoghbi, 2006), may therefore benefit from selective α1 adrenoceptor therapy. 1.3 Allosteric ligands of GPCRs Allosteric ligands are drugs which bind to a site that is topographically distinct to

Chapter 1 Introduction the receptor’s orthosteric binding site (Figure 1.10). There are two main consequences of a drug being able to bind allosterically. Firstly, a receptor can be occupied simultaneously by an orthosteric and allosteric ligand, and secondly, these two ligands can exert influence on each other (Figure 1.10). Allosteric ligands can possess a number of functions. “Allosteric agonists” are ligands which bind allosterically and activate a receptor. There are examples of allosteric for the muscarinic and metabotropic glutamate receptors (Digby et al., 2012; Noetzel et al., 2012; Spalding et al., 2002). Alternatively, “allosteric modulators” are pharmacologically silent when bound on their own, but perturb the regular function of a concomitantly bound, orthosteric ligand. Allosteric modulators can increase or decrease orthosteric ligand affinity and binding kinetics, as well as enhance or inhibit the ability of an orthosteric agonist to activate signalling pathways. Promoting binding affinity, efficacy or potency is deemed a

This figure has been removed for copyright purposes. The original image can be found in Davie et al. (2013) ACS Chem Neurosci 4: 1026-48

Figure 1.10 Effects of allosteric ligands General scheme of the effects of allosteric ligand binding at biogenic amine GPCRs, adapted from Davie et al. (2013). Any allosteric ligand with intrinsic efficacy to activate receptor signalling pathways (τB) is termed an allosteric agonist. Allosteric modulators have the ability to promote or inhibit orthosteric ligand affinity (α) or perturb the efficacy of orthosteric agonists (τA), by a factor of β. 30

Chapter 1 Introduction

“positive” effect, while decreasing these properties is considered a “negative” effect. Within the rhodopsin-like family of GPCRs, allosteric modulators for muscarinic receptors are probably the most comprehensively described, owing largely to the early observation of non-competitive interactions at these receptors (Tucek et al., 1990). Allosteric modulators of the metabotropic glutamate receptors (mGluR) are also well described owing largely to their potential as targets for treatment of many CNS based conditions including pain, anxiety, schizophrenia and Parkinson’s disease (Conn et al., 2014; Gasparini et al., 2002; Marino & Conn, 2006). Allosteric modulators have a number of postulated advantages over orthosteric ligands, including selectivity, preservation of normal signalling patterns, saturability of binding, subtype-specific functional selectivity, probe dependence and signalling bias: Selectivity: As allosteric ligands bind to regions that are not under as stringent evolutionary pressure as orthosteric sites, there is greater opportunity for divergent sequences in allosteric binding regions, creating more selective binding sites.

Replacement of ECL3 in the M3 muscarinic receptor with that of the M2 muscarinic receptor changed the affinity of allosteric modulators gallamine and alcuronium to that of the M2 muscarinic receptor (Krejčı́ & Tuček, 2001). Many of the first subtype selective antagonists of the metabotropic glutamate receptors were identified as allosteric (Conn et al., 2014; Litschig et al., 1999; Varney et al., 1999). Maintenance of physiological signalling patterns: Allosteric modulators, lacking any intrinsic efficacy, only alter signalling in the presence of endogenous orthosteric ligands. Signalling will therefore mimic the physiological release of endogenous hormones or neurotransmitters, instead of continuous receptor blockade/activation seen for competitive ligands. In vivo and in vitro experiments demonstrate that the mGluR5 receptor is a potential target in schizophrenia, as tested by hyperlocomotion models in rats (Marcotte et al., 2001). Direct, orthosteric activation of the receptor results in downregulation of the receptor and dysregulation of long-term depression and potentiation induced by this receptor; functions that are meticulously linked to high or low frequency stimulation of the mGluR5 receptor (Neyman & Manahan-Vaughan,

2008). One of the major side effects of mGluR5 activation, eptileptiform activity observed during in vitro electrophysiology and seizures in whole animals, is also present for allosteric ligands that have intrinsic agonist activity but abolished in “pure” allosteric modulators which lack agonist activity and only potentiate the actions of

Chapter 1 Introduction glutamate (Bridges et al., 2013; Rook et al., 2013). Positive allosteric modulators of this receptor, however, are able to maintain this frequency-dependent regulation in cultured astrocytes and hippocampal slices, while reducing amphetamine induced hyperlocomotion (Noetzel et al., 2012; Rodriguez et al., 2010). Reduced agonist activity of these allosteric ligands correlates with lower incidences of side effects (Bridges et al., 2013) indicating that interruption of endogenous signalling patterns can be of concern, particularly in the CNS. Saturability: Allosteric ligands do not compete for the same binding site as orthosteric ligands. An allosteric modulator with a moderate cooperativity (positive or negative) that does not increase or impede receptor activity such that it becomes toxic, should never produce toxic effects. Once binding is saturated, the effect is thus limited to the maximum efficacy of the modulator and cannot outcompete orthosteric ligands (Conn et al., 2014; Nickols & Conn, 2014) . Functional subtype selectivity: It is emerging that many “selective” allosteric modulators have similar affinity for many receptor subtypes, but are selectively efficacious at only one or a subset of receptor subtypes. It has been demonstrated that the muscarinic compound McN-A-343 binds with similar affinity to the five muscarinic receptor subtypes, but modules the M1 and M4 subtypes to a greater extent than the remaining subtypes (Valant et al., 2008). Similarly, thiochrome has similar affinities for the M1-M4 muscarinic receptors, but enhances acetylcholine affinity only at the M4 subtype (Lazareno et al., 2004). Probe dependence: The effects of an allosteric modulator can be dependent on the orthosteric ligand used. The muscarinic allosteric modulator benzyl quinolone carboxylic acid (BQCA) is able to increase the cAMP response of the M1 muscarinic receptor induced by agonists acetylcholine, carbachol and pilocarpine, but has minimal effect on the xanomeline induced response (Canals et al., 2012). Likewise, at the M4 muscarinic receptor, LY2033298 improves agonist potency of the agonist oxotremorine over acetylcholine and xanomeline, so much so that LY2033298 is only efficacious in in vivo mouse models, when coadministered with oxotremorine (Suratman et al., 2011). Thus, for a receptor with two, or more, endogenous ligands, an ideal allosteric modulator would only possess cooperativity for the most relevant ligand (Valant et al., 2012). Signalling bias: Allosteric ligands, like orthosteric ligands, can possess bias for

Chapter 1 Introduction

certain signalling pathways. A series of allosteric agonists of the M1 muscarinic receptor preferentially activates calcium release and ERK phosphorylation over β–arrestin recruitment in transfected cell lines (Digby et al., 2012). This difference translated into hippocampal specific effects in rats, despite wider distribution of M1 muscarinic receptors in the CNS (Digby et al., 2012). An ideal allosteric modulator would modulate a single, validated pathway, as opposed to all signalling pathways of a given receptor. Probe dependence, signalling bias and functional selectivity all offer additional ‘layers’ of selectivity that can be engendered to an allosteric ligand. While moderate binding selectivity may not be large enough for clinical relevance, summation or compounding selectivity of multiple properties may give rise to an allosteric ligand with superior, combined properties. These effects should also be considered when choosing an assay to test these compounds. Probe ligands and tested pathways should be chosen to match endogenous conditions as closely as possible to increase the likelihood of finding a therapeutically relevant molecule. Notably, it has been demonstrated that allosteric modulators, like orthosteric drugs, are amenable to structural modification to produce drugs with more refined properties (Huynh et al., 2013). Allosteric modulators of GPCRs are somewhat underrepresented as therapeutics. The drug bank database (Wishart et al., 2006) lists at least 437 drugs currently approved by the US Food and Drug Administration (FDA) whose targets are GPCRs (Garland, 2013). There are only 2 approved allosteric modulators of GPCRs; cinacalcet and marivaroc. Cinacalcet is a positive allosteric modulator of the calcium sensing receptor and maraviroc is a negative allosteric modulator of the CCR5 chemokine receptor (Dorr et al., 2005; Jensen & Bräuner-Osborne, 2007; Milligan & Smith, 2007). Given the overrepresentation of GPCRs as drug targets (Garland, 2013), and the numerous advantages of allosteric modulators, it may be surprising that there are so few described allosteric modulators for many GPCRs, including the α1 adrenoceptors. This is largely owing to the difficulty in identifying allosteric modulators, particularly in high throughput screens. Allosteric modulators can be pharmacologically silent on their own, and can be easily missed in binding or functional assays. Allosteric modulators with high negative cooperativity, i.e. the ability to completely inhibit receptor binding or activation via allosteric mechanisms, can be mistaken for competitive antagonists. Identification of allosteric modulators thus represents promising, new avenues for therapeutic treatments directed at GPCRs (Christopoulos, 2002; Conn et al., 2014;

Chapter 1 Introduction

Garland, 2013). 1.3.2 Allosteric binding site Allosteric ligands bind to a site that is topographically distinct from the orthosteric binding site. Mutagenesis studies of muscarinic receptors, and more recently, the crystal structure of an M2 muscarinic receptor with a bound allosteric modulator have proposed that the allosteric binding site for muscarinic receptors is on the extracellular surface of the receptor located between TMII, TMVI, TMVII, ECL2 and ECL3 (Chan et al., 2008; Kruse et al., 2013; Voigtländer et al., 2003). Original mutagenesis studies suggested that the binding site for typical allosteric modulators of the M2 muscarinic receptors involved residuesY177ECL2 and T4237.36 (Tränkle et al., 2005; Voigtländer et al., 2003). The availability of a radiolabelled allosteric ligand of the muscarinic receptors also demonstrated that “atypical” modulators, such as tacrine which modulated receptor function also interacted non-competitively with the radiolabelled, typical allosteric modulator [3H]dimethyl-W84 (Tränkle et al., 2003). The allosteric site of the muscarinic receptors could therefore be considered quite diffuse and permit the simultaneous binding of a second, small allosteric modulator, or be entirely occupied by a single, larger allosteric ligand (Tränkle et al., 2005). The allosteric modulator crystalised with the M2 muscarinic receptor, LY2119620, appears to be large enough to occupy the entire site making noted contacts with Y802.61, E172ECL2, Y177ECL2, N4106.58, N419ECL3, W4227.35 and Y4267.39 (Kruse et al., 2013). Allosteric interactions have also been identified at the D2 dopamine receptor by the use of mutagenesis and an isomer of the ligand SB269652. Mutating the identified residues at the extracellular end of TMII, V912.61 and E952.65 or using an enantiomer of the ligand destroys the interactions at the allosteric site and allosteric properties are lost (Lane et al., 2014). Allosteric sites can vary and are dependent on the location of the orthosteric binding site, but for aminergic, rhodopsin-like GPCRs, it is expected that the allosteric site will, in general, be on the extracellular surface of the receptor (Conn et al., 2009). 1.3.3 Bivalent ligands Bivalent ligands are ligands which are conjugations of two component drugs that would ordinarily bind to two distinct binding sites (Portoghese, 1989). A bivalent ligand can bind to the orthosteric site of two adjacent receptors, or can bind to two spatially distinct sites on a single receptor e.g. the orthosteric site and an allosteric site. Combining two pharamcophores in a single molecule offers a number of

Chapter 1 Introduction pharmacological advantages, including increased affinity, the combined properties of two drugs in a single molecule, and also pharmacokinetic advantages. Increased affinity and potency: Conjugating two drugs for two receptors that exist in close proximity to each other can increase affinity. Simply combining two identical pharmacophores will increase affinity. Binding of the first moiety creates a high micro- concentration by tethering the second moiety to locations near to the second binding site (Portoghese, 1989). Such a method has yielded homobivalent compounds with improved affinity and/or potency for the D2 dopamine receptor (Gogoi et al., 2012;

McRobb et al., 2012), and the cannabinoid CB1 receptor (Zhang et al., 2010) with linkers of sufficient length to suggest the two pharmacophores are binding at two dimerised, or proximal receptors. Incidentally, improved affinity has also been observed at the 5-HT1B receptor (Perez et al., 1998), however the linker was far shorter (>10 atoms) suggesting that the gains in affinity arise by a different mechanism. Heterobivalent ligands for different receptors found either dimerised or in close proximity can also demonstrate such improvements in affinity. This has been demonstrated with a heterobivalent ligand with moieties for the µ and δ opioid receptors (Daniels et al., 2005) again with linkers of sufficient length, >16 atoms, to support the hypothesis of binding at two proximal, but different receptors. Combined properties of two desirable drugs: Combining two drugs, for example, one with high affinity but low efficacy, and one with low affinity but high efficacy can yield an improved drug which now has high affinity and high potency (Portoghese, 1989). Many ligands of the muscarinic receptors, such as McN-A-434, are being described as bitopic, where one moiety interacts with the orthosteric site of the receptor with high affinity, and the other acts allosterically to promote binding and modulate the function of the orthosteric end (Valant et al., 2008). Thus, this single molecule combines an orthosteric partial agonist as well as an allosteric modulator. Pharmacokinetic: Combining two drugs into a single molecule can potentially produce one pharmacokinetic profile providing dual therapy with a single dosing schedule (Hughes et al., 2011; Steinfeld et al., 2011). This was the rationale behind developing the drug “MABA” (Steinfeld et al., 2011). MABA contains muscarinic and

β2 adrenoceptor moieties to provide a dual therapy for chronic obstructive pulmonary disease, in a single molecule.

Chapter 1 Introduction

1.3.4 Allosteric modulators and bitopic ligands of the α1 adrenoceptors The advantages that allosteric modulators present would overcome many of the difficulties of developing α1 adrenoceptor therapies. Side effects such as orthostatic hypotension, sexual dysfunction and floppy iris syndrome could be overcome by a more selective ligand. Continuous receptor blockade/activation in the CNS could also be overcome by maintaining a more physiological pattern of signalling in the CNS. The first stages of developing allosteric modulators of the α1 adrenoceptors would be to identify any compounds that possess these properties. Information gathered from this could then be used to identify potentially important residues of the receptors that could be targeted by potential drug candidates. More recently described modes of interaction with a receptor, such as allosteric and bitopic binding, offer potential new options for therapeutics which target GPCRs. The adrenoceptors are established targets for a number of conditions such as benign prostatic hyperplasia (Lepor et al., 2012) and are proposed targets for the treatment of seizure disorders and heart failure (Perez & Doze, 2011).While there are a number of allosteric and bitopic ligands described for some GPCRs such as the muscarinic and metabotropic glutamate receptors, there is little information on such ligands for the α1 adrenoceptors. Only a handful of molecules have been partially described for their ability to allosterically modulate, or bind bitopically to the α1 adrenoceptors. These include ρ-T1A, a peptide toxin isolated from the cone snail Conus tulipia (Sharpe et al.,

2001). ρ-T1A acts noncompetitively at the α1B adrenoceptor subtype, altering 125 dissociation kinetics of [ I]HEAT, but appears to act competitively at the α1A and α1D adrenoceptor subtypes (Chen et al., 2004). Evidence for the binding site of ρ-T1A is scarce and experiments are incorrectly interpreted (Ragnarsson et al., 2013). Differences in competition binding IC50 values of ρ-T1A are directly correlated with the allosteric site, though no correction is made for changes in radioligand affinity, nor for affinity difference of the two radioligands used, nor is the data modelled to accommodate the assumption that the ligands are binding non-competitively. Several benzodiazepines have been demonstrated to have partial agonist activity and increase the maximum effect of agonists adrenaline, phenylephrine and clonidine at the α1 adrenoceptors (Waugh et al., 1999) though the location of the binding site was not determined. Alcuronium and gallamine known modulators of the muscarinic receptors, have also been shown to modestly increase the dissociation rate of [3H]prazosin from cardiac

Chapter 1 Introduction membranes, as well as incompletely inhibit [3H]prazosin binding in competition binding, suggesting a non-competitive mode of action (Pfaffendorf et al., 2000). The most well described modulators of α1 adrenoceptors appears to be a series of amiloride 3 derivatives, which can substantially increase the dissociation of [ H]prazosin from α1A adrenoceptor expressing membranes (Leppik et al., 2000). There appears to be considerable evidence that there is indeed an allosteric site on the α1 adrenoceptors, however its location remains unspecified. Finally, two series of homobivalent molecules, the bisacridines and bisquinolines

(Figure 1.11), were shown to have greater affinity at the α1 adrenoceptors than their monovalent constituents (Adams et al., 1986; Adams et al., 1985). The series contained a number of molecules where two identical pharmacophores of either 4-aminoquinoline or 9-aminoacridine, were conjugated with methylene linkers of varying lengths (Adams et al., 1985). Furthermore, there were tissue specific differences in affinity of some of these compounds (Adams et al., 1986). The authors suggested that these differences could be attributed to bitopic binding modes at different receptor subtypes which had yet to be identified (Adams et al., 1985; Schwinn et al., 1995). Again, no suggestion of binding site was made. These molecules would thus present an ideal starting point in the search for novel binding modes at the α1 adrenoceptors as the increasing length linkers could be used as a “molecular ruler” to find the location of novel sites of interaction.

9-aminoacridine Bisacridine Bisquinoline 4-aminoquinoline

Tacrine

Figure 1.11 Acridines and quinolines Structures of 9-aminoacridine, tacrine (3,4,5,6-tetrahydro-9-aminoacridine). 4- aminoquinoline and general structures of the bisacridines and bisquinolines.

Chapter 1 Introduction

1.4 Receptor theory Receptor theory is the application of complex models to empirical observations in an attempt to quantify properties of drug-receptor interactions. By using appropriate parameters in these models, receptor theory can explain the behaviour of receptor populations as well as single molecules using relevant, and understandable parameters (Kenakin, 2009). Original theories regarding the behaviour of drugs and “receptive substances” were rather simple. As experimental observations of pharmacological concepts progressed past early notions of ‘receptive substances’ (Langley, 1905), it was observed that properties, such as the rate of association of a drug to its receptor could be quantified. As theories became more complex, so too did the models that described them. Using the developed models allows an unbiased method to compare drug properties. Binding of G proteins is known to change the activation state of the receptor and thus receptor affinity. If a receptor population only exists in either a G protein bound or unbound state, then G protein has no bearing on the observations. Consideration of G protein coupling adds another component to these models and another layer of complexity. There was no evidence of multiple populations observed in the studies of this thesis, therefore this component will not be included in the models described here, or used in analysis of the data presented. Extensive descriptions of the effect of G protein coupling on receptor function can be found in publications by Black and Leff (1983), Weiss et al. (1996) and Christopoulos and Kenakin (2002). 1.4.1 Binding affinity of orthosteric ligands Receptor binding assays have generated considerable data. The most complete model for describing receptor-ligand interaction would be the cubic ternary complex model (Weiss et al., 1996) however when binding follows a single-site model, data can be sufficiently explained using a two-state model. The affinity of any ligand for a receptor can be calculated using Langmuir’s adsorption isotherm:

[�][�] � = (1) � [��] where A is any ligand, R is any receptor, and AR is the bound ligand-receptor complex.

Chapter 1 Introduction

There is generally more than one ligand that can bind a receptor. Rather than label many ligands, it is possible to calculate the affinity of unlabelled ligands by competing them against a high affinity, labelled ligand. Thus, the affinity of an unlabelled ligand can be calculated by:

�� = 50 � [�] (2) 1 + �� where B is the competing, unlabelled ligand, IC50 is the concentration of B which displaces 50% of labelled-ligand binding, [A] is the concentration of labelled ligand, and KA is the affinity of the labelled ligand. This model works under the assumption that the two ligands are competing for the same binding site and have no effect on the binding of the competing ligand. 1.4.2 Cooperative binding Classic pharmacological observations generating Hill slopes of one are indicative of simple, competitive receptor interactions that resulted in the simple theory that receptors and ligands interact without cooperativity i.e. one receptor, one ligand. Growing evidence is suggesting that receptors can possess more than a single binding site, whether they both exist on a single receptor protomer, or are the result of receptor oligomerisation. The existence of multiple sites can result in binding cooperativity, where binding of molecule can either promote or inhibit binding of another, identical molecule. In competition binding assays, a competing ligand that displays cooperativity will produce curves whose steepness deviates from normal (assuming that the labelled ligand displays simple, non-cooperative binding). This data can be fit by incorporation of the term “Hill slope” (Hill, 1910; Lazareno & Birdsall, 1993), as follows :

��50 �� = 1 [�] � � (3) (2 + ( ) ) − 1 �� where H is the Hill slope. A Hill slope greater than 1 indicates positive cooperativity of the competing ligand, while a Hill slope of less than 1 indicates negative cooperativity. 1.4.3 Non-competitive binding It has been shown that the affinity of a non-competitive antagonist can be

Chapter 1 Introduction estimated when the antagonist displays extremely strong negative cooperativity with the orthosteric agonist (Ehlert, 1988). A double reciprocal plot of equi-effective agonist concentrations in the absence and presence of antagonist should produce a straight line. Using the slope of this plot, affinity can be estimated by:

[B] � = (4) � slope − 1 where Kb is the affinity of the non-competitive antagonist, [B] is the concentration of antagonist used, and slope is derived from the double reciprocal plot (Kenakin, 1997). 1.4.4 Receptor activation Agonist induced responses, particularly in animals or tissues, are a relatively easy observation to make i.e. heart rate or blood pressure, or contraction of tissue in organ baths. Consequently, agonism is traditionally expressed as a function of agonist concentration. The most simplistic expression of agonism could be expressed as:

[�]. � � = �� (5) [�] + ��50

where E is the magnitude of the observed effect, [A] is the agonist concentration, Emax is the maximum observed effect. This simply applies a hyperbolic curve to the measured effect as a function of agonist concentration (Reeves, 2012). 1.4.4.1 Operational model of agonism The previous model of receptor activation is a simple one and does not account for more complex observations such as receptor reserves, partial agonism, or ligand affinity. The advent of molecular pharmacology has elucidated properties such as receptor number and ligand affinities. Black and Leff (1983) thus proposed the Operational Model of Pharmacological Agonism which explains observed effects more completely as:

� . [�]. � � = � �� (6) �� + [�](�� + ��)

where KE is the concentration of occupied receptors necessary to elicit half-maximal effect, Rt is the total concentration of receptors, and KA is the affinity of an agonist. The concept of intrinsic efficacy can also be quantified by the operational model of agonism. 40

Chapter 1 Introduction

Intrinsic efficacy or “transduction efficiency” of an agonist can also be derived from this equation and is designated as τA where:

� � = � (7) ��

This largely represents systems where receptor activation saturates signalling pathways (Black & Leff, 1983). 1.4.5 Allosteric modulators The properties of allosteric modulators can also be quantified in a similar manner. Importantly, it needs to be noted that allosteric ligands add cooperativity to other receptor functions. Adding an allosteric modulator to a simple two state model, not only adds the parameters for the ligand’s concentration and its affinity, but also the allosteric modulator’s ability to perturb orthosteric ligand binding by a factor of α and receptor activation by a factor of β (Figure 1.10). These cooperativity factors are also reciprocal; the binding of an orthosteric ligand alters the binding of an allosteric ligand by the same factor α. Thus it can be seen how addition of a single, allosteric component can produce a complex system and changes in one or more parameters can have vast implications. This model can be extended to create the operational model of allosterism (Leach et al., 2007) which parameterises the signalling ability of both the orthosteric and allosteric ligands (τA and τB, respectively) and can be applied to observations of receptor activation in the presence of allosteric modulators.

� (� [�](� + ��[�]) + � [�]� ) � = �� (8) [�]�� + �� + ��[�] + �[�][�] + ��[�](�� + ��[�]) + ��[�]��

where KA and KB are the affinities of the orthosteric ligand, A, and allosteric ligand, B. α is the cooperativity factor between the orthosteric and allosteric ligands, and β is the cooperativity factor between the allosteric ligand and activation of the receptor (Hall, 2000; Leach et al., 2010). An important caveat of this model is that it contains many parameters, and any analysis should be done with great respect to the proportion of which have been experimentally derived and which have been fit by regression. As more parameters are left unconstrained, there is a higher likelihood of dependence between them for proper fitting (Giraldo, 2015; Leach et al., 2007).

Chapter 1 Introduction

1.5 Computer aided techniques Computer based techniques can be used to compliment or even replace many aspects of the drug discovery, design and development process (Congreve et al., 2005; Davis et al., 2003). While empirical observations are still the ultimate validation, methods such as high throughput screening can be resource intensive and time consuming. Instead, in silico techniques can be used at multiple stages of the drug discovery process including target validation, virtual high throughput screening, lead optimisation to enrich test sets with molecules that are more likely to bind to receptors, or to guide further development of a drug with respect to its target binding pocket (Anderson, 2003). There are a number of techniques that can be used to aid drug discovery, including visualisation, molecular docking and homology modelling. 1.5.1 Visualisation Visualisation is a fairly basic, yet fundamental tool in drug discovery. Visualisation software is fairly ubiquitous but underscores most, if not all other in silico techniques. Visualisation gives shape to 3D protein structures and their ligands, and can highlight the interactions that occur between them. 1.5.2 Docking Docking is a process to predict the binding mode of a ligand within a protein binding site (Kitchen et al., 2004). Docking therefore predicts the location and conformation of a ligand binding site in a protein, as well as the chemical interactions between the ligand and target protein. One such docking method is the Genetic Optimisation for Ligand Docking (GOLD) (Jones et al., 1995; Jones et al., 1997) which is a “genetic algorithm” for identifying the orientation of a ligand within a protein binding site. To generate poses, random solutions, each considered as a “chromosome” are generated (Jones et al., 1995). Each chromosome contains all of the information necessary to describe the ligand pose; atom types, bond angles, H-bond donors/acceptors etc. Poses are then quantified using a scoring function. GOLD uses GOLDScore, which is the weighted sum of four individual component scores; external H-bonds and external van der Waals which are H-bond and hydrophobic interactions between the ligand and protein, internal van der Waals which are intramolecular interactions of the ligand, and internal torsion which measures torsional strain within the ligand. Each component is scored so that favourable interactions add points, while unfavourable interactions deduct points. Once

Chapter 1 Introduction scored, parent chromosomes are then “selected” and subjected to either “crossover” or “mutation”, generating newer, daughter chromosomes that represent an alternative pose. Crossover combines elements from previous poses, while mutation modifies a single, previous pose. New poses are assessed for fitness and less fit members of the population are replaced by more fit members (Jones et al., 1997). Thus, the docking process “evolves” towards poses of better fitness. Once the specified number of poses has been generated by the algorithm, they are ranked based on score and clustered based on root mean square distance (RMSD) of the ligand atoms. Scoring is by no means a reflection of affinity, as it simply identifies potential interactions with no regard for the strength of each interaction. Consequently, high scores are more likely to be generated by larger molecules as they have more potential to find more interactions. Thus, scoring is relative, and where possible should always be interpreted with respect for any available empirical data for a known ligand. The largest cluster is considered to be the most likely binding pose. Scoring functions appear to be the major limiting factor in docking accuracy (Kitchen et al., 2004; Li et al., 2010). For example, larger molecules tend to score more highly as they have the potential to make more interactions with the receptor (Kitchen et al., 2004). Similarly hydrophobic molecules tend to score more poorly as they do not make H-bond interactions with the receptor, a large component of the final score (Jones et al., 1997). In general, there is no good correlation between docking scores and affinity (Olsen et al., 2004). Ultimately, GOLD appears to perform well (Jones et al., 1997) and, while it can be more computationally demanding that other docking algorithms, has been demonstrated to more reliably predict correct poses than other algorithms such as CHEMscore (Verdonk et al., 2003), PMF (Pérez & Ortiz, 2001), Glide, LigandFit, Surflex (Li et al., 2010), AutoDock and FlexX (Olsen et al., 2004). A limitation to the GOLD algorithm is that the target protein is typically held rigid, while the ligand is allowed flexibility. Current understanding of protein-ligand interactions recognises that binding pockets are preformed and stabilised by a bound ligand (Boehr et al., 2009; Koshland, 1958). Simulating gross protein movement, or even sidechain movement in a binding pocket drastically increases computational requirements, sometimes to the point of impracticality (Carlson & McCammon, 2000). The most economical use of docking therefore is to use a target structure with a binding pocket predicted to be most similar to the ligands being docked.

Chapter 1 Introduction

Docking therefore finds major use in either identifying ligands which are likely to fit within the identified binding pocket, or assessing a ligand’s binding mode within a binding pocket. Identifying ligands which will be accommodated within a known binding pocket can be used as a virtual screen of large chemical libraries to filter and enrich test sets with a higher proportion of potential binders (Jenkins et al., 2003; Kitchen et al., 2004). Alternatively, assessing a docked ligands binding mode within the binding pocket can be used to identify where advantageous modifications can be made to improve a ligand’s properties, a process that yielded the influenza treatment, zanamivir (Congreve et al., 2005). 1.5.3 Homology modelling Docking methods, including GOLD, are frequently assessed for their accuracy, and it has been observed that the likelihood of generating a good, or correct pose in known structures is correlated with the quality of the starting structure; structures of higher resolution and quality are more likely to generate a correct pose (Jones et al., 1997). Crystal structures do not exist for the vast majority of GPCRs, and there are none available for any of the α1 adrenoceptors. A commonly used alternative is a homology model of the target protein. Homology models are 3D structures that are made using the known structure of a related, homologous protein, termed the “template” structure (Martí-Renom et al., 2000). Homology models rely on conserved structure between the target and template proteins to shape the primary, amino acid sequence of the target protein, guided by the known structure of the template. When using homology models for docking, it is of utmost importance to generate high quality models (Cavasotto & Phatak, 2009), choosing an appropriate, well resolved template (Davis et al., 2003) and generating valid sequence alignments (Davis et al., 2008; Kolb et al., 2012; Yoshikawa et al., 2013). Sequence alignments can be a major determinant of the final homology model, and expert, human intervention is still a vital step in generating appropriate alignments for modelling (Eswar et al., 2001). The method used to generate homology models used in this thesis is the algorithm, MODELLER (Eswar et al., 2001; Sali & Blundell, 1993). MODELLER retains the protein backbone of the template structure, specifically secondary structures such as α-helices and β-sheets, then builds the model using side chains of the target structure, while attempting to satisfy torsional restrictions of the side chains (Sali & Blundell, 1993). MODELLER will return as many models as specified, each with slight

Chapter 1 Introduction variations, where expert analysis can be used to identify the best model. Homology models can be assessed and validated by comparing docked poses of well described ligands, or by assessing side-chain deviations e.g. side chain deviations are not desirable in critical areas such as ligand binding pockets. 1.6 Summary and aims

Whilst the field for α1 adrenoceptor therapeutics is already populated, there still exists room for drugs with improved selectivity, or an improved mechanism of action. Regions of the receptors, such as the extracellular domains are not as comprehensively described as the transmembrane domains, yet studies continue to demonstrate important roles for the extracellular domain in normal function of the receptors. It is possible that these extracellular domains represent allosteric binding sites, which would offer a number of advantages over orthosterically-targeted drugs, yet there is little information on allosteric modulators of the α1 adrenoceptors, or where an allosteric site may exist on these receptors. Therefore, the aim of this thesis is to identify and describe any novel sites on the α1 adrenoceptors that are potentially druggable, allosteric sites.

Chapter 2 Methods

2.1 Reagents COS-1 cells were purchased from ATCC (Virginia, USA). [3H]prazosin, [3H]myo-inositol, and Ultima Gold and Ultima Flo scintillation cocktails were purchased from Perkin Elmer (Waltham, MA, USA). [3H]8-OH-DPAT was purchased from GE Healthcare (Uppsala, Sweden). GF/C and GF/B glass fibre filters was purchased from Whatman (Maidstone, UK). Dulbecco’s Modified Eagle Medium (DMEM) without inositol was purchased from MP Biomedicals (Santa Ana, CA, USA). Foetal bovine serum (FBS) was purchased from Invitrogen (Carlsbad, CA, USA). (R)- adrenaline hydrochloride, (R)-noradrenaline hydrochloride, phentolamine hydrochloride , 5-methylurapidil, lithium chloride, (S)-propranolol hydrochloride, tacrine hydrochloride, diethylaminoethyl-dextran (DEAE dextran), ammonium formate, chloroquine diphosphate, 2-amino-2-hydroxymethyl-propane-1,3-diol (Tris) and 2-[4- (2-hydroxyethyl)piperazin-1-yl]ethanesulfonic acid (HEPES) were purchased from Sigma Aldrich (St. Louis, MO, USA). Bisacridines were synthesised as previously described (Deshpande & Singh, 1972). Ethylene glycol-bis(2-aminoethylether)-

N,N,N’,N’-tetraacetic acid (EGTA), MgCl2, NaCl, KCl, Na2HPO4, KH2PO4 and glycerol were purchased from Ajax Finechem (Taren Point, NSW, Australia). Phusion High- fidelity DNA Polymerase was from Finnzymes (Keilaranta, Espoo, Finland). DpnI was purchased from NEB (Ipswich, MA, USA). Mini- and Maxi-prep kits were from either Qiagen (Venlo, Netherlands) or RBC (Banqiao City, Taiwan). jetPEI was purchased from PolyPlus-transfection SA (Illkirch, France). AG 1-X8 formate resin was from Bio-

Rad (Hercules, CA, USA). Human α1A adrenoceptor, α1B adrenoceptor and 5-HT1A receptor in pcDNA were purchased from Missouri S&T cDNA Resource Centre

(www.cdna.org). Human α1D adrenoceptor in pMV6-XL5 vector was obtained from Origene (Rockville, MO, USA). 2.2 Buffers Standard buffers were as follows:

Chapter 2 Methods

2.2.1 Phosphate buffered saline (PBS)

137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4, KH2PO4, pH 7.4 2.2.2 HEM binding buffer

20 mM HEPES, 1.4 mM EGTA, 12.5 mM MgCl2, pH 7.4 2.2.3 HC binding buffer

20 mM HEPES, 4 mM CaCl2, pH 7.4 2.2.4 TE binding buffer 50 mM tris, 500 mM EDTA, pH 7.4 2.2.5 E. coli transformation buffer

10 mM PIPES, 15 mM CaCl2, 250 mM KCl, 55 mM MnCl2 2.2.6 LB bacteria growth medium 10 g.L-1 tryptone, 5 g.L-1 yeast-extract, 5 g.L-1 NaCl, pH 7 2.3 Cell culture COS-1 cells were maintained in DMEM supplemented with 10% (v/v) heat -1 treated FBS and 100 μg.mL glutamine. Cultures were kept at 37°C and 5% CO2 and passaged as they approached confluence by standard tissue culture techniques. 2.4 Mutagenesis Mutations were generated by site directed mutagenesis using Phusion polymerase mediated PCR using primers >35 bp containing the desired mutation in the middle of the sequence, followed by DpnI digestion of methylated wild-type constructs. PCR- digestion products were transformed into competent DH5-α e. coli as per the protocol of Inoue et al. (1990) and incubated overnight on LB agar containing 50 μg.mL-1 ampicillin at 37°C. Single colonies were picked and grown overnight in LB containing 50 μg.mL-1 ampicillin at 37°C and shaking at 200 revolutions per minute (RPM). Mutant receptor vectors were retrieved from overnight cultures by mini prep and mutations were confirmed by sequencing the entire length of the gene in both directions. Confirmed mutations were amplified in DH5-α e. coli, retrieved by maxiprep and stored in milliQ water at -20°C. Maxiprep columns were reused by regeneration as per the method of (Siddappa et al., 2007) 2.5 Transfection for radioligand binding 24 hours before transfection, cells were plated at a density of 2.5-2.8 x 104 cells per cm2 in fully supplemented DMEM. Cells were transfected using a transfection cocktail of 0.5 mg.mL-1 DEAE dextran and 125 nM chloroquine in serum-free DMEM 47

Chapter 2 Methods and 85 ng construct per cm2. Cells were incubated in the transfection cocktail for 3 hours at 37°C and 5% CO2. Following incubation, transfection cocktail was aspirated, cells were washed in 10% DMSO in PBS for 2-3 minutes, then returned to 37°C and 5%

CO2 in fully supplemented DMEM. 24 hours following transfection, cells were lifted using trypsin and replated in DMEM supplemented with 10% FBS and 100 μg.mL-1 glutamine. 2.6 Membrane preparation 2.6.1 Membrane preparation method 1 72 hours after transfection, cells were harvested by scraping into cold PBS. Harvested cells were pelleted by centrifugation at 1000 xg for 5 mins at 4°C. The pellet was resuspended in 0.25 M sucrose with protease inhibitors and homogenised in a Dounce homogeniser with a tight fitting pestle. Homogenates were centrifuged at 1260 xg for 5 mins at 4°C. The supernatant was added to 25 mL membrane precipitation buffer (50 mM tris, 12.5 mM MgCl2, 5 mM EGTA) and centrifuged at 37 000 xg for 15 mins at 4°C. Supernatant was discarded and the pellet was resuspended in 25 mL membrane precipitation buffer and centrifuged again. Supernatant was discarded and the pellet was resuspended in membrane precipitation buffer +10% glycerol. The suspension was passed through an insulin syringe 10-15 times then stored at -80°C in 50 μL aliquots. Protein concentration was determined using the Bradford protein assay (Sigma Aldrich, St. Louis, MO, USA). 2.6.2 Membrane preparation method 2 A second, more efficient membrane preparation, adapted from Leach et al. (2010), was implemented to coincide with the switch to human receptors. Briefly, cells were scraped from the surface of dishes into cold PBS and centrifuged at 500 x g for 5 mins at 4°C. The pellet was resuspended in 10 mL cold HE buffer (20 mM HEPES, 10 mM EDTA, pH 7.4) per scraped plate. Suspensions were homogenised, on ice, with three 10 sec bursts at 20 000 RPM. Lysate was centrifuged at 600 x g for 10 min at 4°C. Supernatant was then centrifuged at 40 000 x g for 1 hour at 4°C. The final pellet was resuspended in cold 20 mM HEPES + 10% glycerol (v/v), 200 μL per 175 cm2 flask and homogenised using an insulin syringe, then stored at -80°C. Protein concentration was measured using Bradford reagent (Sigma, St. Louis, MO, USA). 2.7 Radioligand binding All radioligand binding assays were performed at room temperature in duplicate

Chapter 2 Methods or triplicate, as specified. Reactions were terminated by the addition of 4°C PBS and vacuum filtration through Whatman GF/C glass fibre filters. 2.7.1 Saturation binding Saturation binding assays were performed in a final volume of 200 μL and allowed to incubate for 1 hour. Adrenoceptors were incubated in HEM buffer (20 mM 3 HEPES, 1.4 mM EGTA, 12.5 mM MgCl2, pH 7.4) with 0.03 – 8 nM [ H]prazosin using

1-2 μg protein per reaction for α1A and α1B adrenoceptors and 10-15 μg protein per reaction for the α1D adrenoceptor. Non-specific binding was determined using 100 μM phentolamine. 5-HT receptors were incubated in HC buffer (20 mM HEPES, 4 mM 3 CaCl2, pH 7.4) with 0.1 – 12 nM [ H]8-OH-DPAT using 10 μg protein per reaction. Non-specific binding was determined using 10 μM serotonin. 2.7.2 Competition binding. Competition binding assays were performed in a final volume of 200 μL and allowed to incubate for 1 hour. Ligand binding affinity for adrenoceptors was determined in HEM buffer in competition with [3H]prazosin using 1-2 μg protein per reaction for α1A and α1B adrenoceptors and 10-15 μg protein per reaction for α1D adrenoceptor. Ligand binding affinity for 5-HT1A receptors was determined in HC buffer in competition with [3H]8-OH-DPAT using 10 μg protein per reaction 2.7.3 Dissociation kinetics Dissociation kinetics assays were performed in HEM buffer over 80 minutes for the α1A adrenoceptor and TE buffer (50 mM Tris, 500 mM EDTA, pH 7.4) over 160 minutes for the α1B adrenoceptor. Receptors were pre-equilibrated with 250 pM [3H]prazosin for 1 hour at room temperature in a volume of 400 μL. [3H]prazosin reassociation was then inhibited by the addition of 100 μL phentolamine for a final concentration of 100 μM in the absence or presence of acridine. 2.8 Transfection for IP accumulation assay Resuspended COS-1 cells were diluted to a concentration of 1x105 cells/mL DMEM. Cells were transfected with 1 μg construct and 2 μL jetPEI transfection reagent per 1 x 105 cells as per the manufacturer’s instructions. Cells were plated into 96 well plates (200 μL per well) for inositol phosphate (IP) accumulation assays and 6 well plates (6 mL per well) for whole cell binding analysis. Plates were left at room temperature for 1 hour following transfection, then transferred to a 37°C, 5% CO2 incubator.

Chapter 2 Methods

2.9 IP accumulation assay 16-24 hours post-transfection, media was aspirated and replaced with DMEM supplemented with 10% FBS, 100 μg.mL-1 glutamine, and 100 μg.mL-1penicillin- streptomycin plus [3H]myo-inositol to a final concentration of ~85 nM (10 μCi/mL).

Labelled cells were returned to 37°C and 5% CO2. 24 hours post labelling, media was aspirated and replaced with inositol free DMEM and the cells returned to 37°C for 2 hours. Media was then supplemented to a final concentration of 10 mM LiCl and 10 μM propranolol to inhibit signalling from endogenous β2 adrenoceptors present in COS-1 cells and incubated for 20 mins at 37°C. Reactions were started with the addition of adrenaline or noradrenaline to a final volume of 150 μL and incubated for 30 mins at 37°C. Reactions were stopped by the addition of 50 μL 400 mM formic acid. Cells were lysed by freeze-thawing at -80°C and 45°C. Total soluble inositol phosphates were collected by 30 minute incubation and vacuum filtration through activation AG 1-X8 formate resin in a 96 well MultiScreen filter plate (Millipore) then eluted with 1 M ammonium formate in 100 mM formic acid. 200 µL eluate was diluted with 1 mL reverse osmosis (RO) water and emulsified in 3 mL Ultima Flo liquid scintillation cocktail and quantified by counting for 5 mins in a liquid scintillation counter. 2.10 Whole cell binding Cells in 6-well plates were lifted with trypsin and diluted to 4 x 105 cells per mL. Binding was performed in a total volume of 200 μL HEM buffer with 4 x 104 cells for 1 hour with 4 nM [3H]prazosin. Non-specific binding was determined using 100 μM phentolamine. Bound radioligand was extracted from dried filters in Ultima Gold liquid scintillation cocktail and quantified in a liquid scintillation counter. 2.11 Data analysis Saturation binding data were analysed by non-linear regression in GraphPad Prism v.5 or later. Pre-programmed models were used for saturation binding, one-site competition binding, and one-site association and dissociation kinetics. Where evidence of cooperative competitive binding was observed, non-linear regression curves were fit using a variable slope model (equation 3), entered into Prism as:

(�� − ��) � = �� + (9) 1 + 10(�−��C50)×��

Chapter 2 Methods

Initial values were set as follows: ��: 1 × � �� , [�]: 1 × ��,

��: 1 × � �� , ��: 1 × ��, ��: 1 × ��, ��: 1 × �� , �� .

KE values were determined using the operational model of pharmacological agonism of Black and Leff (1983):

� ∗ �� ∗ (�� − ��) � = �� + ( ) (10) (�� ∗ ��) + (� ∗ (�� + ��))

Initial values were set as follows: ��: 1 × ��, ��: 1 × ��, ��: 1. Energy of binding (ΔG) was calculated as:

1 ΔG = −RTlog ( ) (11) ��

-1 -1 where R is the gas constant in J.K .mol , T is temperature in Kelvin, and Ki is the binding affinity as determined by competition binding. Mutant cycle analysis of binding was performed with mean ΔG values. Mutant cycle analysis of function was performed as per Gleitsman et al. (2009):

�� (��) × �� (�1�2) Ω = 50 50 (12) ��50(�1) × ��50(�2) where M1 and M2 represent individual mutations and M1M2 represents the combined mutation. The coupling parameter, Ω, was calculated using mean EC50 values ± standard error of the mean (SEM) from all available experiments and errors propagated as:

�. �. �. �. �. �. 2 �. �. �. 2 � = √( �) + ( �) (13) � � � where c is the product and a and b are any two variables. Statistical analysis of binding kinetic data was performed on log10 51

Chapter 2 Methods transformations of fold-increase values to normalise fold-changes. All data are presented as mean ± SEM, and were compared by one-way ANOVA with Newman-Keuls post-test In GraphPad Prism v5, or Tukey post-test in GraphPad Prism v6. 2.12 Docking Homology models were prepared by Ms. Urmi Kaniz. Briefly, ClustalW

(www.uniprot.org) was used to align the related GPCR sequences of human α1A-, α1B-,

α1D-, and β2 adrenoceptors, human D2 and D3 receptors, human 5-HT1A receptor, human histamine H1 receptor, turkey β1-adrenoceptor and bovine rhodopsin. The resulting alignment was then hand edited to ensure maximum overlap of conserved sequences and minimise gaps. Chain A of the D3 receptor-eticlopride complex crystal structure (PDB ID: 3PBL) was selected as the template. The T4 lysozyme of the template structure and corresponding residues of target structures were removed. Homology models were generated using the MODELER package as implemented in DS 4.0 (www.accelrys.com), generating 100 models and ranked by PDF energy, which indicates favourable modelled properties. The top model, by PDF energy was used without further refinement. Ligands were sketched in Discovery Studio 4.0 and protonated at designated location and minimised using the CHARMm forcefield using a maximum of 20 000 steps. Phentolamine was not protonated. Minimised ligands were docked into supplied homology models using GOLD v5.1 as implemented in Discovery Studio 4.0 setting “Identify Cavity” to false, “Early Termination” to false, “Flip Amide Bonds” to true and “Internal Hydrogen Bonds” to false. All other settings were left as default. Clustering distances were chosen by expert selection to produce clusters appropriate to the size and flexibility of the ligands, and ligand-receptor interactions were assessed in Discovery Studio 4.0 using default settings.

Chapter 3 An aspartate in the second extracellular loop of the α1B adrenoceptor regulates agonist binding

3.1 Introduction

Adrenaline and noradrenaline, the two endogenous agonists of the α1 adrenoceptors, bind within the transmembrane bundle to a well-defined site ~11 Å below the extracellular surface, which is conserved amongst the nine adrenoceptor subtypes. Antagonists for the adrenoceptors are typically larger than agonists and have interaction sites that extend outside the agonist binding site, towards the extracellular domain (Ahmed et al., 2008; Nagaoka et al., 2008; Waugh et al., 2001; Zhao et al., 1996). The less-conserved nature of the extracellular loops creates an ideal target for ligand selectivity. Indeed it has been demonstrated that a triplet of residues at the beginning of ECL2 in the α1A and α1B adrenoceptors is responsible for the selective binding of a series of adrenergic antagonists (Zhao et al., 1996). There is currently no demonstrated role of the extracellular domains in agonist binding for the adrenoceptor family.

There are no available crystal structures of the α1 adrenoceptors. Homology modelling was used to construct a model of the α1 adrenoceptors based on a rhodopsin template (PDB ID: 1GZM)(Li et al., 2004; MacDougall & Griffith, 2006). The model predicted an interaction between K3317.36 in the seventh transmembrane helix and D191ECL2 in ECL2. This lysine has a well-characterised role in an interhelical salt- bridge, where a charge interaction with D1253.32 is postulated to constrain the receptor in an inactive state. Upon agonist binding, the charge interaction is disrupted by competition from the positively ionised nitrogen of adrenergic agonists (Porter et al., 1996) which allows the receptor to assume an active conformation. 3.1.1 Hypothesis D191ELC2 is a counter-ion for K3317.36 following agonist binding and receptor

activation and promotes agonist binding to the α1B adrenoceptor.

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding

Figure 3.1 Homology model of the α1B adrenoceptor. Model was based on rhodopsin (PDB ID: 1GZM) template (Li et al., 2004). Shown, right, with transmembrane helices I and IV labelled for orientation. Enlarged, left, with helices I, II, and III removed for clarity, and helices VI and VII labelled for orientation. The proposed salt-bridge between the D191ECL2 and K3317.36 sidechains can be observed clearly (MacDougall & Griffith, 2006).

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding

3.2 Methods 3.2.1 Reagents Regents were supplied as specified in section 2.1. Mini- and Maxi-prep kits were from Qiagen (Venlo, Netherlands). 3.2.2 Mutagenesis

Mutations were generated by site directed mutagenesis of hamster α1B adrenoceptor in pMT3’ vector as per section 2.4 and sequenced at the Ramaciotti Centre for Gene Function Analysis (University of New South Wales, Sydney, Australia). 3.2.3 Cell culture Cell culture was performed as per section 2.3. 3.2.4 Transfection, membrane harvesting and radioligand binding Transfections for membrane preparations were performed as per section 2.5, and membranes were harvested as per section 2.6.1. Receptor binding assay were performed as per sections 2.7.1 and 2.7.2. 3.2.5 Transfection and IP accumulation assays Transfections were performed as per section 2.8. IP accumulation assays were performed as per section 2.9 and normalised to expression data as determined by whole cell binding, described in section 2.10. 3.2.6 Data analysis All saturation and competition binding were fit to a one-site model.

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding

3.3 Results 3.3.1 Characterisation of receptors by radioligand binding. 3 [ H]prazosin affinity for the WT α1B adrenoceptor (220 ± 80 pM) is similar to previously published results, as is affinity for the K3317.36A mutation (198 ± 66 pM) (Porter et al., 1996). There was no significant difference between [3H]prazosin affinity for the WT and K3317.36A receptors (Table 3.1). The K3317.36A mutant expresses at only 40% of WT (p<0.01), again similar to previous experiments (Table 3.1) (Porter et al., 1996). The D191ECL2A mutant is expressed at similar levels to WT, and there is no significant difference in affinity for [3H]prazosin (374.1±76.5 pM). The double D191ECL2A.K3317.36A mutant has a [3H]prazosin affinity similar to WT, but expresses at 29% of WT levels, similar to the K3317.36A mutant (Table 3.1). 3.3.2 Characterisation of competition ligand binding. Phentolamine and 5-methylurapidil, described as competitive inverse agonists of the α1B adrenoceptor (Rossier et al., 1999), show 32 nM and 80 nM affinities for the WT receptor, respectively, in agreement with other studies (Porter et al., 1996; Zhao et al., 1996). Alanine, with an obvious lack of side chain substituents, was chosen for the mutagenesis studies with the intention of generating exaggerated, easily detectable changes. None of the mutants show significantly different affinities for either of the competing antagonists (Figure 3.2, Table 3.2) indicating no gross distortion of the ligand binding pocket. The endogenous agonist adrenaline has 1.3 µM affinity at the WT receptor, consistent with previously reported values (Porter et al., 1996). In contrast to a previous

Table 3.1 Saturation Binding

KD (pM) n Bmax (pmol/mg) n WT 220 ± 80 7 14.6 ± 1.0 4 K3317.36A 198 ± 66 6 5.9 ± 0.2*** 4 D191A ECL2 374 ± 77 10 15.3 ± 1.0 5 D191 ECL2A.K3317.36A 252 ± 56 9 4.3 ± 0.7*** 5 3 KD: Dissociation constant, equivalent to the concentration of [ H]prazosin required to occupy 50% of expressed receptors. Bmax: Maximal receptor concentration as calculated by non-linear regression of saturation binding. All data are expressed as the mean ± S.E.M for ‘n’ repeats, performed in triplicate. ***, P < 0.001 compared to WT. 56

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding study, we observe no significant difference in affinity for adrenaline at the K3317.36A mutant receptor, where an increased affinity has previously been observed (Porter et al., 1996). The study by Porter et al. (1996) used the radioligand [125I]HEAT. A recent analysis of binding kinetics for radioligands of the α1A adrenoceptor revealed differential binding kinetics of [3H]prazosin and [125I]HEAT (Maïga et al., 2014). [125I]HEAT had a slower dissociation rate and incubation times up to 2 hours were not sufficient to reach equilibrium at WT and at least one mutant of the α1A adrenoceptor and incubation times used by (Porter et al., 1996) were unlikely to be sufficient to reach equilibrium. [3H]prazosin therefore most likely represents a more accurate observation. Both the D191ECL2A and D191 ECL2A.K3317.36A mutants display a significant decrease in affinity for adrenaline compared to WT and K3317.36A receptors (Table 3.2).

Figure 3.2 Competition binding curves for adrenergic ligands. Competition binding curves for phentolamine (A), 5-methylurapidil (B), adrenaline (C), and noradrenaline (D) at WT (●), K3317.36A (▼), D191 ECL2A (▲), and D191 ECL2A/K3317.36A (♦) receptors. Binding assays was performed against 250 pM [3H]prazosin with 1-5 µg protein, as determined by Bradford assay, in a final volume of 200 µL HEM buffer. Reactions were allowed to equilibrate for 1 hour at room temperature. Points and bars represent the mean ± SEM of 3-5 experiments performed in triplicate. Affinity values and statistical analysis are given in Table 3.2.

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding

Table 3.2 Competition binding WT K3317.36A D191 ECL2A D191 ECL2A.K3317.36A

pKi n Ki (nM) pKi Ki (nM) pKi n Ki (nM) pKi n Ki (nM) Phentolamine 7.5 ± 0.2 4 32 7.8 ± 0.1 4 16 7.2 ± 0.2 4 63 7.8 ± 0.2 4 16 5-methylurapidil 7.1 ± 0.1 4 79 7.3 ± 0.1 4 50 6.8 ± 0.1 4 160 7.0 ± 0.1 4 100 Adrenaline 5.9 ± 0.1 5 1300 6.0 ± 0.1 6 1000 5.1 ± 0.1** 6 7900 5.3 ± 0.1** 6 5000 Noradrenaline 5.4 ± 0.1 4 4000 5.9 ± 0.1** 4 1300 4.8 ± 0.1** 4 16000 5.2 ± 0.1 4 6300 pKi: Negative log of the inhibition constant, equivalent to the concentration of ligand required to bind to 50% of unoccupied receptor. Calculated from observed IC50 values according to the Cheng-Prusoff equation (Cheng & Prusoff, 1973). Ki: Calculated inhibition constant, equivalent to the concentration of ligand required to occupy 50% of unoccupied receptors. Derived from pKi. All data are presented as mean ± SEM for ‘n’ repeats, performed in triplicate. **, P < 0.01 compared to WT.

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding

Noradrenaline displays 4.0 μM affinity at the WT receptor, consistent with previously reported values (Porter et al., 1996). We observed a small but significant increase in affinity for noradrenaline at the K3317.36A mutant (3-fold, p<0.01). A previous study observed a more dramatic 7-fold increase in affinity for this mutant (Porter et al., 1996). With the D191 ECL2A mutant, we observe a modest, but significant 4-fold decrease in affinity for noradrenaline (p<0.01). In contrast to adrenaline, noradrenaline affinity at the double D191ECL2A.K3317.36A receptor is similar to, and not significantly different from, WT (Table 3.2, Figure 3.2). To assess any residue interactions, the change in binding energies was calculated and analysed by mutant cycle analysis (Table 3.3). The sum of binding energies from individual mutants was not significantly different from the change in binding energy of the double mutant for either agonist. 3.3.3 Characterisation of receptor activity. Given the change in affinity for agonists, the ability of the receptors to become activated was studied using a radiolabelled precursor of the second messenger inositol 7.36 triphosphate (IP3). The K331 A mutant shows a 4.1-fold increase in basal signalling over the WT receptor (p<0.01). Neither of the D191ECL2A mutants demonstrate significantly increased basal signalling over WT receptor. Addition of the D191ECL2A mutation to the K3317.36A receptor returns basal signalling to WT levels (Figure 3.3) The mutant receptors showed altered and differing responses to the endogenous agonists adrenaline and noradrenaline. Adrenaline possesses 74 nM potency at the WT

α1B adrenoceptor (Table 3.4, Figure 3.4). We observe small, but significant 2.1 fold (p<0.05) and 3.6 fold (p<0.01) decreases in potency at the K3317.36A and D191ECL2A mutants (Table 3.4, Figure 3.4). At the double mutant, adrenaline has an 8.5 fold decrease in potency compared to WT (Table 3.4, Figure 3.4), which is significantly different from WT (p<0.001), as well as the K3317.36A (p<0.01) and D191ECL2A (p<0.05) single mutants. Noradrenaline displays 347 nM potency at the WT receptor. The K331A mutation has no significant effect on noradrenaline potency. We observe a 3.3 fold decrease in potency at the D191ECL2A mutant (p<0.01 compared to WT), and a 3.9 fold decrease in potency at the double mutant (p<0.01 compared to WT and K3317.36A) (Table 3.4, Figure 3.4). Mutant cycle analysis (Ambrosio et al., 2000) was used to examine residue interaction for receptor activation (Table 3.4). Ω values did not deviate significantly from unity, providing no evidence for interaction between the

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding

Figure 3.3 Agonist independent receptor signalling. Fold-WT basal signalling of K3317.36A (4.0 ± 0.7), D191 ECL2A (0.9 ± 0.5), and D191 ECL2A.K3317.36A (2.0 ± 1.0), corrected for vector only signalling. All data were normalized to receptor expression levels as determined by whole cell binding with 4 nM [3H]prazosin. All data were analysed by one-way ANOVA with Newman-Keuls post- test. ** p<0.01, n=3-8.

Figure 3.4 Agonist associated receptor activation. Adrenaline (A) and noradrenaline (B) induced production of soluble inositol phosphates by WT (●), K3317.36A (▼), D191 ECL2A (▲), and D191 ECL2A/K3317.36A (♦) receptors. Points and bars represent mean ± S.E.M of 3-5 experiments performed in triplicate.

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding mutated residues. Functional data was then analysed in the presence and absence of the D191ECL2A mutation using the Operational Model of Agonism (Black & Leff, 1983) (Table 3.5) with respect to experimentally derived binding data to attempt to reconcile the divergent observations for agonist affinity and potency. Mg2+ has been shown to be a major contributor to agonist binding at the α1 adrenoceptors (Colucci et al., 1984) so affinity values determined in HEM buffer are easily applicable to observations made for receptor activation. Operational analysis yielded values of the percent of receptors occupied to cause half-maximal activation (KE). WT receptors reached half-maximal activation with only 8.5 and 10.3% receptor occupation for the endogenous agonists, 7.36 adrenaline and noradrenaline, respectively. At the K331 A mutation, KE values were 22.4% and 38.1% for adrenaline and noradrenaline. Addition of the D191ECL2A 7.36 mutation to WT or K331 A mutant receptors did not significantly change KE. The effect of the K3317.36A mutation on receptor activation could not be reliably quantified as comparison to a receptor lacking this mutation is difficult due to differences in receptor reserve (Table 3.1).

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding

Table 3.3 Change in energy of agonist binding K3317.36A D191 ECL2A D191 ECL2A.K3317.36A -1 -1 -1 ΔΔG (kj.mol ) n ΔΔG (kj.mol ) n ΔΔG (kj.mol ) n ΔΔGK331A + ΔΔGD191A Adrenaline -0.9 ± 0.4*** 5 4.3 ± 0.2 5 3.3 ± 0.5 5 3.4 ± 0.4 Noradrenaline -2.9 ± 0.3*** 4 3.4 ± 0.6* 4 1.2 ± 0.5 4 0.5 ± 0.7

ΔΔG , Change in energy of binding, expressed as ΔGmutant-ΔGWT, where ΔG=-RTlog(1/Ki). All data are presented as mean ± SEM for ‘n’ repeats. All analyses were performed on each repeat, and the resulting values averaged. *, **, ***, P < 0.05, 0.01, 0.001 compared to D191A.K331A double mutant.

Table 3.4 Agonist induced receptor activation WT K3317.36A D191 ECL2A D191 ECL2A.K3317.36A

EC50 EC50 EC50 EC50 Ω pEC50 n (nM) pEC50 n (nM) pEC50 n (nM) pEC50 n (nM) Adrenaline 7.1 ± 0.1 5 74 6.8 ± 0.1* 4 160 6.6 ± 0.1** 5 260 6.2 ± 0.1*** 4 630 1.07 Noradrenaline 6.5 ± 0.1 5 350 6.5 ± 0.1 3 320 5.9 ± 0.1** 3 1100 5.9 ± 0.1** 3 1300 1.14 pEC50, Negative log of the concentration of agonist required to activate the receptor to 50% of observed maximum. EC50, Calculated concentration of agonist needed to activate the receptor to 50% of observed maximum. Derived from pEC50. Ω, Coupling parameter of a mutant cycle analysis, where Ω is equal to the ratio of the product of the EC50 values of WT and double mutant receptors to the product of the EC50 values of the single mutation receptors, as described in section 2.9. All data are presented as mean ± SEM for ‘n’ repeats, performed in triplicate. *, **, ***, P < 0.05, 0.01, or 0.001 compared to WT.

Table 3.5 Operational analysis of receptor activation WT K3317.36A D191 ECL2A D191 ECL2A.K3317.36A

KE n KE n KE n KE n Adrenaline 8.5 ± 2.0 5 22.4 ± 1.9 4 4.5 ± 1.5 5 16.2 ± 1.8 4 Noradrenaline 10.3 ± 1.8 5 38.1 ± 10.9 3 9.7 ± 1.9 3 27.2 ± 4.0 3

KE, Percent of receptors required to be occupied to cause half-maximal activation. Calculated according to the Operational Model of Agonism as described in section 2.9. All data are expressed as mean ± SEM for ‘n’ repeats. *, **, ***, P < 0.05, 0.01, or 0.001 compared to WT.

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding

3.4 Discussion The D191ECL2A mutation caused a decreased affinity for both agonists. This was surprising, as no extracellular residues have previously been shown to be involved in binding of the endogenous agonists for this receptor. There is increasing evidence that the extracellular regions of aminergic receptors form binding ‘vestibules’ where ligands briefly reside before proceeding on, to the orthosteric binding site (Dror et al., 2011; Kruse et al., 2012). The ligands investigated in these simulation studies contain positively charged amines, and both simulations identified acidic residues in ECL2 as important for vestibule binding. It is possible that an aspartic acid in the extracellular region of the α1B adrenoceptor could interact with positively charged aminergic agonists in a similar manner to the conserved acidic residue at position 3.32, which is considered critical for ligand binding, to create this binding vestibule in the extracellular region of the receptor. The flexible nature of ECL2 has been shown to be an important factor in regulating ligand access to the orthosteric binding pocket of the muscarinic acetylcholine receptors (Avlani et al., 2007). D191ECL2 is located in a fairly unstructured and unconstrained loop, and would thus be ideally placed to sample the surrounding environment for suitable ligands and provide an initial point of contact before the ligand advances to the orthosteric binding pocket within the transmembrane helix bundle. 7.36 The K331 A α1B adrenoceptor mutation has been described previously (Porter et al., 1996; Porter & Perez, 1999). This study extends these observations by comparing binding and function of both endogenous agonists. In agreement with the previous study (Porter et al., 1996), we find the K3317.36A mutation results in a constitutively active receptor. The increased agonist independent signalling indicates that this receptor has a reduced capacity to maintain its inactive, ground state. This is consistent with a previous conclusion that this residue is involved in a salt-bridge interaction that prevents receptor transition to a signalling conformation. This active state conformation would normally be expected to favour agonist binding. This is indeed the case for noradrenaline however adrenaline binding is unchanged for this mutant. While mutation of K3317.36 produces a constitutively active receptor, this residue may also have a positive role in promoting adrenaline binding. Thus, K3317.36A may create a constitutively active mutant with a higher affinity for agonists in general but also remove a feature of adrenaline binding, resulting in an apparently unchanged affinity. Previous study of this mutation showed increased

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding affinity for both ligands at the K3317.36A mutation when in competition with the radioligand [125I]HEAT, however [125I]HEAT and prazosin have previously been shown to produce different results at mutant adrenoceptors (Chen, 2001), likely as a result of different binding kinetics for each radioligand (Maïga et al., 2014). Accurate determination of this feature would require the analysis or a greater number of agonists with chemical modifications. The unchanged affinity of the three inverse agonists, [3H]prazosin, phentolamine and 5-methylurapidil at the K3317.36A mutant suggests no gross distortions of the ligand binding pocket and that the observed increase in affinity for noradrenaline is not a product of a global folding disorder. The combination of both mutations yielded agonist binding profiles which appear to be a combination of both individual mutations. We originally hypothesised that the two residues, K337.361 and D191ECL2 were engaged in a stepwise redirection of charge. This observation was quantified using mutant cycle analysis. Theoretically, if both residues are acting independently, then the change in binding energy of the double mutation should be the same as the sum of the change in binding energies of the individual mutations. The similarity of the observed double mutation, and summed individual mutations for both agonists does not provide evidence for an interaction between these two residues. It would appear that K3317.36 and D191ECL2 are able to exert independent effects on the binding of agonists to the α1B adrenoceptor. The extracellular regions of this receptor have been shown to be a source of selectivity for antagonists (Porter et al., 1996) and this data suggests that they are also able to contribute to the binding of agonists. Following the change in agonist affinities, the role of these residues in receptor function was examined. In contrast to noradrenaline’s increased affinity for the mutant receptor, its potency was similar at both WT and K3317.36A receptors. Also, while adrenaline had an unchanged affinity for the K3317.36A mutation, it displayed decreased potency. Due to the suggested role of K3317.36 in agonist binding as well as receptor activation, it is difficult to delineate the precise influences this residue has on binding as well as receptor activation. Unlike residues such as R3.50, K3317.36 has influence over not only receptor activation, but ligand binding. This dual role will produce complex effects on the affinity of, and activation by agonists. Such mixed results could be explained if K3317.36 were considered a micro-switch that is involved in both the

Chapter 3

An ECL2 aspartate in the α1B adrenoceptor regulates agonist binding inactive and active states of the receptor. Following the decrease in agonist affinity at the D191ECL2A mutant, both agonists showed decreased potency. Neither receptor generated significantly different levels of basal or Emax signalling, so it would appear that this residue’s sole role is in agonist binding. Application of an operational model of agonism (Black & Leff, 1983) further confirms this as the fraction of occupied receptors necessary to elicit half-maximal activation was not significantly different between WT and the D191ECL2A mutant, or between K3317.36A and D191ECL2A.K3317.36A mutants for either agonist. The non- conserved and unrestrained nature of the ECL2 would ideally place this residue in extracellular space that would allow it to interact with nearby, solvated ligand. The positively charged amine group of the aminergic ligands interacts with a highly conserved aspartate in TMIII: D1253.32. An identical residue in the extracellular space could possibly be a point of first contact, interacting with ligands in a similar manner to the conserved D1253.32. Furthermore, while addition of the D191ECL2A mutation to the K3317.36A receptor appeared to decrease potency, it should be considered that addition of this mutation would alter agonist affinity. Indeed, operational analysis reveals that the fraction of occupied receptors necessary to activate the double mutant receptors is not significantly different from the K3317.36A single mutation for either agonist. Again, D191ECL2 appears to be involved solely in agonist binding.

Chapter 4 Subtype selectivity of 9-aminoacridines

4.1 Introduction Bivalent ligands are an interesting approach to studying multiple binding sites and have been employed to study GPCRs (Shonberg et al., 2011), including aminergic receptors, usually within the context of GPCR dimerisation (Berque-Bestel et al., 2008; Hiller et al., 2013). Linkers greater than ~16 atoms allow the bivalent ligand to act across a dimer pair (or higher order oligomer) (Kühhorn et al., 2011; McRobb et al., 2012; Russo et al., 2007) while shorter chains restrict interactions to within a single receptor (Birnkammer et al., 2012). Bivalent ligands can be heterobivalent, with two different pharmacophores linked to either end of the specified spacer, or homobivalent, where two identical pharmacophores are linked.

9-aminoacridine C4 bisacridine C9 bisacridine

Tacrine

Figure 4.1 Acridines Structures of 9-aminoacridine, C4 bisacridine, C9 bisacridine, and tacrine in their protonated form. 67

Chapter 4 Subtype selectivity of the 9-aminoacridines

The bisacridines are a series of homobivalent molecules with two 9-aminoacridine chromophores linked by methylene linkers of increasing length (Figure 4.1). These compounds had previously been shown to display high affinity for adrenoceptors with the bivalent molecules displaying higher affinity than the monovalent 9-aminoacridine

(Adams et al., 1985). The highest affinity was seen at the α1 adrenoceptors with tissue specific differences in α1 adrenoceptor binding affinity between rat cerebral cortex and kidney membranes (Figure 4.2)(Adams et al., 1986). The tissue specific differences were postulated to be a consequence of the linked pharmacophores binding concomitantly to non-conserved regions of the receptor outside the traditional, orthosteric binding site (Adams et al., 1986). Subtypes of the α1 adrenoceptor were yet to be identified or characterised at the time of the study.

This figure has been removed for copyright purposes. The original image can be found in Adams et al. (1986) Euro J Pharmacol 127: 27-35

Figure 4.2 Bisacridine affinities at central and peripheral α1 adrenoceptors Competition binding affinities of C2-C12 bisacridines and 9-aminoacridine (linker length = 0) at rat cerebral cortex (●) and rat kidney (○) membranes (Adams et al., 1986). Points represent the mean of 3 experiments performed in competition with 150 pM [3H]prazosin. The solid line (-) shows the affinity of bisacridines at cerebral cortex membranes as measured by competition binding with [125I]HEAT. Reproduced from (Adams et al., 1985). 68

Chapter 4 Subtype selectivity of the 9-aminoacridines

These acridines were of interest as they presented a promising approach to further probe the extracellular regions of the α1 adrenoceptors. If they were indeed binding to non-orthosteric regions of the receptor, elucidating their binding profiles may provide a novel mode of high affinity or selective binding at each of the α1 adrenoceptor subtypes. Optimally sized molecules would display high affinity or subtype selective binding and the known linker length could be used as a ‘molecular ruler’ to predict the proximity of different binding sites. However, 9-aminoacridine’s planar structure makes it an ideal DNA intercalator and would limit its use as a potential adrenoceptor therapeutic (Wakelin et al., 1978). Tacrine (tetrahydro-9-aminoacridine) has a structure that is similar to 9-aminoacridine however one ring is saturated. The saturated ring in tacrine would overcome this limitation by disrupting the planarity of the molecule, and indeed, tacrine has previously received FDA approval for the treatment of Alzheimer’s disease, acting as an acetylcholinesterase inhibitor (Drukarch et al., 1987; Qizilbash et al., 1998). Tacrine was thus included as a means of testing whether planarity was essential for the effects of 9-aminoacridine as well as assessing the therapeutic potential of using acridines or a derivative as a highly selective ligand of the α1 adrenoceptors. 4.1.2 Hypothesis The tissue specific differences in acridine binding affinities can be explained by

subtype selectivity for different α1 adrenoceptor subtypes.

Chapter 4 Subtype selectivity of the 9-aminoacridines

4.2 Methods 4.2.1 Tissue culture COS-1 cells were maintained in DMEM supplemented with 10% (v/v) heat -1 treated FBS and 100 μg.mL glutamine. Cultures were kept at 37°C and 5% CO2 and passaged as they approached confluence by standard tissue culture techniques. 4.2.2 Transfection and membrane harvesting

COS-1 cells were transfected with human α1A or α1B adrenoceptor in pcDNA3.1(+), human α1D adrenoceptor in pMV6 or human 5-HT1A receptor in pcDNA3.1(+) as per section 2.5 using 20 µg DNA per 175 cm2 plate and harvested as per section 2.6.2 and stored in 20 mM HEPES, 1 mM EDTA, 10% glycerol in 50 µL aliquots at -80ºC. 4.2.3 Receptor binding All saturation and competition binding was performed as per sections 2.7.1and 2.7.2. Competition binding was performed using 250 pM [3H]prazosin. 4.2.4 Data analysis Competition binding data were all fit by non-linear regression in GraphPad Prism v6 using a variable slope competitive binding model as defined in section 2.11, equation (2). All values were compared using two-way ANOVA and Tukey post-test.

Chapter 4 Subtype selectivity of the 9-aminoacridines

4.3 Results 4.3.1 WT receptor characterisation 3 [ H]prazosin binding to human α1 adrenoceptors was similar, albeit slightly lower than reported values (Zhao et al., 1996), and data were best fit by a one-site saturation binding model with no significant selectivity between any of the receptor subtypes (KD: 3 α1A: 1060 ± 41 pM, α1B: 707 ± 12 pM, α1D: 932 ± 166 pM). [ H]8-OH-DPAT displayed

2.2 nM affinity for the 5-HT1A receptor similar to reported values (Newman-Tancredi et al., 1998b)

Phentolamine displayed 4.0, 14.8, and 19.3 nM affinity for the α1A, α1B, and α1D adrenoceptors, respectively, similar to previously reported values (Zhao et al., 1996) and displaying slight α1A adrenoceptor selectivity (P < 0.01Table 4.1, Figure 4.3).

Figure 4.3 Saturation binding of biogenic amine receptors. 3 3 Saturation binding curves for [ H]prazosin binding at α1 adrenoceptors and [ H]OH- DPAT binding at the 5-HT1A receptor. Receptor expressing membranes were incubated at room temprature for 1 hour. Non-specific binding was determined using 100 µM phentolamine for the α1 adrenoceptors and 10 µM 5-HT for the 5-HT1A receptor. Points and bars represent the mean ± S.E.M for 3 repeats performed in duplicate 71

Chapter 4 Subtype selectivity of the 9-aminoacridines

Serotonin displayed 1 nM affinity for the 5-HT1A receptor, similar to previously reported values (Newman-Tancredi et al., 1998b). 4.3.2 Competition binding of 9-aminoacridines To address whether the tissue specific differences in binding affinity originally observed for the acridines are attributable to subtype selectivity, the affinity of all available acridine compounds was determined via competition against radioligand binding at all three α1 adrenoceptor subtypes, as well as the 5-HT1A receptor to assess for “off target” binding. In general, all acridine compounds showed low to sub-micromolar affinity for all three α1 adrenoceptor subtypes (Table 4.1). 9-aminoacridine had 247 nM affinity for the

α1A adrenoceptor, 10-fold selective over the α1B adrenoceptor (Ki: 2.6 µM, P<0.01), 8- fold selective over the α1D adrenoceptor (Ki: 1.9 µM, P<0.001), and greater than 400- fold selective over the 5-HT1A receptor (Ki: >100 µM, Table 4.1). A long-term outcome of this research would be the design of a highly selective, clinically useful α1 adrenoceptor antagonist. The planar nature of the acridines makes them efficient DNA intercalators, which would give rise to limiting side effects. To test whether the high affinity of 9-aminoacridine was dependent upon a flat structure, tacrine was also included in the test as set for comparison with 9-aminoacridine. Tacrine displayed 1.8, 19.4, and 6.4 μM affinity at the α1A, α1B, and α1D adrenoceptors, respectively (Table 4.1). This was consistently lower than 9-aminoacridine at the α1A and α1B adrenoceptors (P < 0.01), but still maintaining α1A over α1B subtype selective binding (P < 0.05)(Figure 4.4). At the α1B and α1D adrenoceptors conjugation of two acridines pharmacophores, i.e. the bisacridines, had similar or greater affinity than the monovalent 9-aminoacridine for all linker lengths tested. In contrast, the bisacridine series showed large variation in affinities at the α1A adrenoceptor, particularly for bisacridines with linkers between 2 and 7 carbons. Where the bisacridines possessed only 5- and 7-fold differences between the highest and lowest affinity compounds at the

α1B and α1D adrenoceptors, respectively, there was 91-fold difference between the highest and lowest affinity bivalent compounds (C2 and C4) at the α1A adrenoceptor (Table 4.1)(Figure 4.4). C2 had 1.9 μM affinity, significantly lower than 9- aminoacridine (P < 0.01, Table 4.1) while C3 had similar affinity to 9-aminoacridine at the α1A adrenoceptor. C4 has 21 nM affinity, significantly higher than 9-aminoacridine,

C2, C3 and all other bisacridines with linkers longer than 6 carbons at the α1A

Chapter 4 Subtype selectivity of the 9-aminoacridines adrenoceptor (P < 0.05) (Table 4.1.) C4 bisacridine was also 10-fold selective over the

α1B adrenoceptor (P < 0.001), 30-fold selective over the α1D adrenoceptor (P < 0.001), and 145-fold selective over the 5-HT1A receptor (P < 0.001)(Figure 4.4). C4 binding at the α1A adrenoceptor was the highest observed for any of the acridines at all of the tested receptors (Figure 4.3, Table 4.1). All bisacridines with a linker length of 5 carbons or fewer had significantly higher affinity for all of the α1 adrenoceptor subtypes than the 5-HT1A receptor (Figure 4.3). Affinities of the smaller bisacridines, C2 and C3, as well as the monovalent 9-aminoacridines for the 5-HT1A receptor were some of the lowest observed in the test set, resulting in substantial selectivity for the α1 adrenoceptor subtypes (Figure 4.3, Table 4.1). It was noted that the competitive binding curve slopes for the some of the bisacridines appeared steeper than that for the competitive antagonist phentolamine (Figure 4.5). All competition binding curves were fit with a variable slope function.

Phentolamine binding curves did not differ significantly from unity for any α1 adrenoceptor nor did serotonin binding at the 5-HT1A receptor (Table 4.2). C10 generated a competition binding curve with a Hill slope significantly steeper than 1 at

Figure 4.4 Subtype selective binding of the 9-aminoacridines Binding affinities of the acridines at all three α1 adrenoceptors and 5-HT1A serotonin receptor. All binding curves were fit by a variable-slope competitive binding model. Affinities were compared by one-way ANOVA with Tukey post-test. a, b, d, s: P < 0.05 compared to α1A, α1B, α1D adrenoceptors, and 5-HT1A serotonin receptor, respectively.

Affinity is not shown where logKi is greater than -4.. 73

Chapter 4 Subtype selectivity of the 9-aminoacridines

Table 4.1 Competition binding affinities at human aminergic receptors

α1A adrenoceptor α1B adrenoceptor α1D adrenoceptor 5-HT1A receptor

pKi n Ki (nM) pKi n Ki (nM) pKi n Ki (nM) pKi n Ki (nM) Phentolamine 8.40 ± 0.06 6 4 7.83 ± 0.15 6 14 7.72 ± 0.06 6 19 nd Serotonin nd nd nd 9.01 ± 0.06 6 1 9-aminoacridine 6.61 ± 0.03 3 247 5.59 ± 0.05 3 2562 5.73 ± 0.11 3 1873 >4 C2 bisacridine 5.72 ± 0.12 3 1906 6.61 ± 0.16 3 245 5.85 ± 0.09 3 1401 >4 C3 bisacridine 6.15 ± 0.09 3 702 6.37 ± 0.15 3 430 5.92 ± 0.06 3 1202 4.75 ± 0.17 3 17783 C4 bisacridine 7.67 ± 0.15 3 21 6.68 ± 0.14 3 208 6.19 ± 0.03 3 651 5.51 ± 0.12 3 3073 C5 bisacridine 7.48 ± 0.12 3 33 7.02 ± 0.16 3 94 6.44 ± 0.05 3 362 5.75 ± 0.07 3 1783 C6 bisacridine 7.23 ± 0.08 3 58 6.95 ± 0.12 3 112 6.66 ± 0.07 3 219 6.47 ± 0.05 3 340 C7 bisacridine 6.93 ± 0.06 3 117 6.96 ± 0.19 3 108 6.65 ± 0.09 3 225 6.21 ± 0.09 3 619 C9 bisacridine 6.57 ± 0.08 3 266 6.88 ± 0.18 3 131 6.48 ± 0.11 3 334 5.74 ± 0.21 3 1828 C10 bisacridine 6.53 ± 0.07 3 292 6.84 ± 0.11 3 146 6.44 ± 0.11 3 367 6.03 ± 0.05 3 929 C12 bisacridine 6.39 ± 0.18 3 404 6.90 ± 0.09 3 124 5.81 ± 0.06 3 1554 6.02 ± 0.09 3 950 Tacrine 5.73 ± 0.06 3 1857 4.71 ± 0.24 3 19379 5.19 ± 0.16 3 6402 nd pKi: Negative log of apparent affinity calculated according to the Cheng-Prusoff equation (Cheng & Prusoff, 1973) using IC50 values obtained from a variable-slope competitive binding model as per section 2.11, equation (2). Ki: Calculated concentration of ligand required to occupy 50% of unoccupied receptors, derived from pKi All data are presented as mean ± SEM for ‘n’ repeats, performed in duplicate. nd: not determined.

Table 4.2 Competition binding slopes

α1A adrenoceptor α1B adrenoceptor α1D adrenoceptor 5-HT1A receptor Slope n Slope n Slope n Slope n Phentolamine 1.03 ± 0.43 6 1.05 ± 0.06 5 1.04 ± 0.06 4 nd Serotonin nd nd nd 0.84 ± 0.10 6 9-aminoacridine 0.96 ± 0.08 3 1.02 ± 0.07 3 1.22 ± 0.13 3 nd 4 C2 bisacridine 1.24 ± 0.18 3 1.19 ± 0.060.089 3 1.42 ± 0.37 3 nd 3 C3 bisacridine 1.12 ± 0.10 3 1.27 ± 0.04* 3 0.98 ± 0.08 3 0.71 ± 0.090.08 3 C4 bisacridine 1.37 ± 0.28 3 1.25 ± 0.03* 3 1.34 ± 0.080.06 3 1.08 ± 0.07 3 C5 bisacridine 1.58 ± 0.25 3 1.33 ± 0.100.09 3 1.25 ± 0.03* 3 1.00 ± 0.18 3 C6 bisacridine 1.87 ± 0.57 3 1.99 ± 0.250.06 3 1.37 ± 0.06* 3 1.11 ± 0.17 3 C7 bisacridine 1.50 ± 0.120.05 3 1.81 ± 0.200.06 3 1.53 ± 0.03** 3 0.83 ± 0.23 3 C9 bisacridine 2.50 ± 0.380.06 3 2.28 ± 0.370.07 3 4.01 ± 1.57 3 1.04 ± 0.45 3 C10 bisacridine 2.00 ± 0.06** 3 2.00 ± 0.13* 3 2.71 ± 0.82 3 1.38 ± 0.21 3 C12 bisacridine 1.97 ± 1.06 3 1.01 ± 0.11 3 2.49 ± 0.420.07 3 1.72 ± 0.10* 3 Tacrine 1.08 ± 0.20 3 0.77 ± 0.08 3 0.91 ± 0.030.09 3 nd Hill Slope coefficient of competitive binding data fit by a variable-slope competitive binding model as per section 2.11, equation (2). *, ** P < 0.05, 0.01 respectively compared to 1 by one sample t-test. P values between 0.05 and 0.1 are reported in superscript. All data are expressed as mean ± SEM for ‘n’ repeats.

Chapter 4 Subtype selectivity of the 9-aminoacridines

the α1A and α1B adrenoceptors (P<0.01, P<0.05, respectively). C3 and C4 had binding curves with Hill slopes significantly steeper than 1 at the α1B adrenoceptor (P<0.05). C7 and C9 also generated Hill slopes greater than 1 at both the α1A and α1B adrenoceptors (P=0.05-0.07)(Table 4.2) indicative of cooperative binding. Neither of the monovalent compounds, 9-aminoacridine and tacrine, produced binding curves significantly steeper than 1 (Table 4.2). Competition binding slopes, in general, appeared to increase in steepness as linkers increase in length until linker length reached 9 carbons with 2 significant correlation between linker length and Hill slope (P < 0.05) seen at the α1A (r 2 2 = 0.8) and α1D (r = 0.7) adrenoceptors, and the 5-HT1A receptor (r = 0.8).

Figure 4.5 Competition binding curves Displacement binding curves for 9-aminoacridine, C4 bisacridine and C9 bisacridine. Compounds were competed against 250 pM [3H]prazosin binding in HEM buffer at the 3 α1 adrenoceptors and 2.5 nM [ H]OH-DPAT in HC buffer at the 5-HT1A receptor. Reactions were incubated for 1 hour at room temperature. Points and bars represent the mean ± S.E.M. of 3 repeats performed in duplicate. All data were fit by a variable slope competition binding curves.

Chapter 4 Subtype selectivity of the 9-aminoacridines

4.4 Discussion Subtype selectivity of currently available ligands is frequently cited as a major limitation in the study of α1 adrenoceptor subtypes, with few drugs possessing high selectivity for a single receptor subtype (Hillman et al., 2009; Methven et al., 2009a; Methven et al., 2009b; Nalepa et al., 2013). Even clinically relevant drugs, such as prazosin, tamsulosin, and naftopidil possess less than 100-fold selectivity for their target receptor subtype over other α1 adrenoceptor subtypes (Shibata et al., 1995; Takei et al.,

1999) and even other aminergic receptors such as the serotonin 5-HT1A and dopamine

D3 receptors (GlaxoSmithKline, 2011; Kuo et al., 2000), particularly in the prostate where the target receptor shows reduced affinity for antagonists (Ford et al., 1996; Gray & Ventura, 2006). Tissue specific differences in the binding affinity of the bisacridines were observed between rat brain and kidney (Adams et al., 1986). It was hypothesised that subtype selective binding of the bisacridines would explain the tissue specific differences observed. The bisacridines were chosen for use in this study in the hope that any correlation between selectivity and linker length could be exploited to find an optimally sized molecule for highly selective binding. The bisacridines with shorter linker lengths were commonly seen to possess selectivity between adrenoceptor subtypes, as well as the 5-HT1A serotonin receptor. There is considerable similarity between the endogenous ligands, and therefore orthosteric biding pocket of the 5-HT1A and α1 adrenoceptors (Figure 1.5, Figure 1.8) and many ligands of aminergic receptors are very non-specific (Yoshio et al., 2001).

The α1 adrenoceptors and 5-HT1A receptors seem to be particularly susceptible to off- target binding of high affinity ligands (Newman-Tancredi et al., 1998a; Yoshio et al.,

2001) and the side effects of current generation α1A adrenoceptor antagonists have been attributed to off-target binding at the 5-HT1A receptor (Borbe et al., 1991). 9- aminoacridine and C4 bisacridine therefore emerged as particularly interesting as they possessed selectivity for the α1A adrenoceptor over not only the other adrenoceptor subtypes, but also the 5-HT1A receptor, a receptor which often has affinity for adrenergic ligands and may be responsible for side effects exhibited by α1A adrenoceptor antagonists (Borbe et al., 1991). The α1A adrenoceptor subtype has been identified as potential target for a highly selective agonist as a treatment of seizure disorders as well as heart failure (Perez & Doze, 2011). The acridines are structurally distinct from traditional α1A adrenoceptor antagonists (Figure 1.7, Figure 4.1) providing

Chapter 4 Subtype selectivity of the 9-aminoacridines a novel scaffold for future drug design. The tissue specific differences observed by Adams et al. (1986) follow a pattern that reflects the binding affinities seen in cloned human subtypes; subtype selectivity is seen as tissue specific differences for 9-aminoacridine and bisacridines with linkers up to 5 carbons, affinities then converge for bisacridines with moderate length, and then diverge slightly for bisacridines with a linker of 12 carbons. Unfortunately C11 bisacridine was not available for testing in this study. Protein levels of α1 adrenoceptors, like many GPCRs, are difficult to quantify by traditional methods such as Western blot (Jensen et al., 2009a). Instead, mRNA transcript levels in the rat suggest that the predominant α1 adrenoceptors found in the kidney are the α1A and α1B subtypes (Rokosh et al., 1994). The mixed expression makes exact delineation of binding difficult in the kidney tissue, but affinities seen at kidney membranes seems to reflect the receptor with the highest affinity that is present in that tissue. 9-aminocridine and all bisacridines with linker lengths up to 5 carbons displayed higher affinity for kidney tissues than cortex.

The same acridines all displayed highest binding affinity at either the α1A or α1B subtypes. i.e. affinity at kidney membranes reflects α1B subtype affinity when that receptor has the highest affinity, or the α1A subtype when it has the highest affinity. In the rat brain, mRNA would suggest that the predominant subtype is the α1D adrenoceptor (Rokosh et al., 1994). Similar to the binding profile seen for the α1D adrenoceptor, binding affinities in the rat cortex are consistently lower than kidney for all linker lengths less than 6 carbons. Affinities in the two tissues converge for linkers of 9 and 10 carbons and kidney again displays higher affinity for C12 bisacridine. There is no subtype selectivity observed between any of the three human α1 adrenoceptors for linker lengths of 9 and 10, while there is α1B subtype selectivity observed for C12 (Figure 4.2, Table 4.1).While C11 bisacridine was not available for testing, it would be predicted to show some selectivity toward the α1A or α1B adrenoceptor subtypes, as a higher affinity is observed in kidney membranes (Figure 4.2). High affinity, selective binding peaks around the moderate length bisacridines, suggesting that their length is ideal to make critical interactions for selective binding, and while affinities between the subtypes are significant, they are not substantial, reiterating the frequent observation that the binding sites are highly similar (Lin et al., 2013), and intrinsically difficult to discriminate between. Conversely, the bisacridines with linkers of 10 or 12 carbons could not effectively discriminate between the α1 adrenoceptor subtypes, nor the 5-HT1A

Chapter 4 Subtype selectivity of the 9-aminoacridines receptor.

Tacrine was also selective for the α1A adrenoceptor subtype but with a significantly reduced affinity for all three subtypes. This suggests that the planar structure of 9-aminoacridine contributes to affinity, but is not absolutely necessary for binding to the α1 adrenoceptors and that the three-ring structure could be a potential scaffold for novel selective α1 adrenergic drugs. Tacrine, though now discontinued, was approved by the FDA as an inhibitor of the enzyme acetylcholinesterase for the treatment of Alzheimer’s disease symptoms. Side effects of tacrine included nausea, headache, dizziness, confusion, rhinitis, insomnia and fatigue. α1 adrenoceptors are known to be involved in sleep and arousal (Berridge, 2008), rhinitis (Shahar et al., 2014), dizziness and headache (Carruthers, 1994) suggesting that these side effects may have been mediated by tacrine binding to the α1 adrenoceptors. While tacrine displayed relatively poor affinity for the α1 adrenoceptors, it has been noted in rats that tacrine preferentially accumulates in the CNS over plasma, and at therapeutic levels it reaches low micromolar concentrations in the CNS (Nielsen et al., 1989). It is possible that these effects are attributable to actions at the α1 adrenoceptors. Incidentally, drug partitioning into the CNS would be ideal for a centrally acting drug treating seizure disorders. This would minimise any side effects arising from peripheral blockade or activation of α1 adrenoceptors. The other major linker-length dependent observation was that as linker length increased, so too did the Hill slopes generated by competition binding curves at the α1 adrenoceptors. The steepest curves were observed for C9 bisacridine at all three of the tested α1 adrenoceptors, but the 5-HT1A receptor appeared less susceptible to this effect. Such increase in Hill slope are indicative of binding cooperativity (Prinz, 2010), which by definition, requires a second binding site. This second site can potentially be the orthosteric site on an oligomeric partner to promote positive cooperativity within the oligomeric complex. The monovalent tacrine and 9-aminoacridine generated curves indistinguishable from 1, as did phentolamine, at all three α1 adrenoceptors, with binding cooperativity only emerging for the longer bisacridines. 9-aminoacridine and

C9 bisacridine have similar affinities at the α1A adrenoceptor yet produce dramatically different Hill slopes suggesting that the observed cooperativity is not arising from binding at multiple orthosteric sites, but is a phenomenon resulting from the presence of the two pharmacophores in a single molecule. The bivalent nature of the bisacridines

Chapter 4 Subtype selectivity of the 9-aminoacridines suggests that they are able to interact with a second site to positively promote their own orthosteric binding. The linkers used in this study would not be predicted to be long enough to permit interaction with orthosteric sites of two adjacent receptors, thus indicating that the second site likely exists on the same receptor protomer. The increase in Hill slope may only be observable for the bivalent ligands if this second site is low- affinity and therefore unoccupied under low to moderate concentrations of acridines as were used in this study. By conjugating two 9-aminoacridine moieties, the linker is effectively tethering the second moiety to the one bound in the orthosteric pocket. Such an approach has been demonstrated to promote binding by reducing entropic losses associated with two individual binding events, but also by creating a high micro- concentration in the immediate vicinity of a low affinity pocket (Portoghese, 1989). Another alternative explanation is that the bivalent molecules are binding to two allosteric sites across the extracellular surface of two dimeric receptors. The competitive-like behaviour of the monovalent ligands, however, suggests that these molecules are likely to be interacting with the orthosteric site of a receptor. Taken together, it would therefore seem that a low affinity pocket capable of promoting orthosteric binding is present on the α1 adrenoceptors, and is separated from the orthosteric pocket by a distance corresponding to a 9-carbon linker. The bisacridines were therefore rather successful in demonstrating that increasing the length between pharmacological moieties could give rise to different properties for different length molecules. It was previously demonstrated that addition of the methylene linker or aminomethylene linker alone was not sufficient to cause substantial increases in affinity in a series of similar compounds, the bisquinolines (Chen et al., 2013; Nguyen, 2013) and that it is indeed the presence of the second pharmacophore that is responsible for these observations. A clue to the nature of the second binding site also arose from the inclusion of tacrine in the test set. In addition to its activity at acetylcholinesterase, tacrine also has low micromolar affinity at the muscarinic receptors (Kiefer-Day et al., 1991; Nielsen et al., 1989; Potter et al., 1989). Monovalent tacrine binds with positive cooperativity at the muscarinic receptors (Kiefer-Day et al., 1991). Tacrine is also able to slow the dissociation of [3H]NMS and [3H]QNB from the muscarinic receptors (Kiefer-Day et al., 1991; Potter et al., 1989). Importantly, tacrine was described to bind to an allosteric site on the muscarinic receptors (Tränkle et al., 2005). While selectivity is often touted

Chapter 4 Subtype selectivity of the 9-aminoacridines as a potential advantage of allosteric ligands, studies on the muscarinic receptors regularly demonstrate that allosteric ligands are binding at common sites across different muscarinic receptor subtypes (Valant et al., 2012). If this common site extends to the adrenoceptors it is possible that tacrine, and the other acridines, can also act allosterically at the α1 adrenoceptors in a similar manner as the muscarinic receptors.

There are few modulators described for the α1 adrenoceptors and little to no information on the allosteric binding site (Ragnarsson et al., 2015; Ragnarsson et al., 2013; Waugh et al., 1999), however they may make effective treatments for seizure disorders, or even provide improvements over orthosterically acting treatments for peripherally based disorders such as BPH, hypertension, and heart failure.

Chapter 5 Non-competitive effects of 9-aminoacridines

5.1 Introduction The vast majority of drugs that target GPCRs do so via the orthosteric binding site of a receptor’s endogenous ligand (Christopoulos, 2002; Conn et al., 2009). This is typically associated with side effects mediated by off-target binding of the drug to similar receptors. This is often unavoidable as the endogenous binding sites are typically very highly conserved between closely related receptors (Christopoulos, 2002). One approach to overcoming this is to target allosteric sites, regions of the receptor distinct from the orthosteric site. Binding at an allosteric site confers a number of potential advantages to these ligands. The lack of sequence conservation can create greater binding selectivity, the non-competitive nature of binding results in an insurmountable interaction that creates a ceiling effect, and the ability to modulate receptor-orthosteric ligand interactions results in ligands which better mimic physiological receptor function rather than continuous blockade or activation as is the case with traditional orthosteric drugs (Christopoulos, 2002; Conn et al., 2009; Nickols & Conn, 2014). Emerging properties of allosteric modulators that are also of significance include probe dependence and functional selectivity (Valant et al., 2012) which give rise to additional layers of selectivity that can be engendered into allosteric ligands.

A suitably selective allosteric modulator of the α1A adrenoceptor may provide a novel, centrally-acting treatment for conditions such as seizure disorders or learning deficits (Conn et al., 2009; Perez & Doze, 2011). An α1A selective positive allosteric modulator may also find use in the treatment of heart failure as a positive inotrope, or a negative allosteric modulator would be beneficial for treating benign prostatic hyperplasia to relax smooth muscle constriction (Christopoulos, 2002; Perez & Doze, 2011). The 9-aminoacridines may present drug-like leads in the development of such a therapy. Allosterically acting ligands are well described for the muscarinic, metabotropic 82

Chapter 5 Non-competitive effects of the 9-aminoacridines glutamate, and dopamine receptors (Haga et al., 2012; Lane et al., 2014; Lazareno et al., 2004; Lazareno et al., 1998; Lazareno et al., 2000; Lazareno et al., 2002; Leppik et al., 1994; O'Brien et al., 2003; Rodriguez et al., 2010; Silvano et al., 2010; Tränkle et al., 2003; Valant et al., 2008). However, there is very little information regarding allosteric modulators of the α1 adrenoceptors. There is evidence that benzodiazepines modulate phenylephrine induced signalling at the α1 adrenoceptors (Waugh et al., 1999) and ρ- T1A, a peptide toxin isolated from cone snails, has been shown to interact allosterically with only the α1B adrenoceptor, binding competitively at the other two subtypes (Sharpe et al., 2003). In chapter 4 it was postulated that bitopic binding of the bisacridines to the orthosteric and an allosteric site on the α1 adrenoceptors was the cause of the observed binding cooperativity. If cooperativity exists between these two binding sites then acridines bound at the allosteric site may possess the ability to modulate the receptor’s interaction with other orthosteric ligands. There are multiple methods which can detect non-competitive interactions of a ligand. Non-equilibrium binding assays, such as dissociation kinetics, can highlight changes in binding kinetics of orthosteric ligands and functional studies can detect changes in receptor activation and have the added advantage of using an unlabelled, endogenous agonist. If the acridines are binding to the α1 adrenoceptors in a similar manner as tacrine does to the muscarinic receptors (Tränkle et al., 2005), then they may be likely to slow the dissociation kinetics of [3H]prazosin. The bisacridines should not cause any greater effect than the monovalent 9-aminoacridine as the orthosteric site of the receptors would be pre-bound to the probe ligand, [3H]prazosin, leaving only the allosteric site available. Thus only one 9-aminoacridine moiety should be bound at any one time and the dimer cannot be tethered to the orthosteric site. To investigate the ability of 9-aminoacridine, the bisacridines and tacrine to modulate the α1 adrenoceptors, these compounds were all tested in dissociation kinetics and functional assays. 5.1.1 Hypotheses The acridines will slow the dissociation rate of the radioligand [3H]prazosin. Bivalent molecules will be no more potent or efficacious modulators of [3H]prazosin dissociation than the monovalent 9-aminoacridine.

Chapter 5 Non-competitive effects of the 9-aminoacridines

5.2 Methods 5.2.1 Dissociation kinetics Receptors were preincubated at room temperature (~23°C) for 1 hour with [3H]prazosin in a final volume of 400 µL using 1-2 µg protein per tube. [3H]prazosin reassociation was prevented by the addition of 100 µL phentolamine for a final concentration of 100 μM in the absence or presence of test compounds. Assays were terminated by the addition of cold PBS and vacuum filtration through Whatman GF/C glass fibre filters. Filters were air dried overnight and bound radioligand quantified by liquid scintillation. Dissociation kinetics for the α1A adrenoceptor was performed in

HEM (20 mM HEPES, 1.4 mM EGTA, 12.5 mM MgCl2, pH 7.4) buffer. Assays for the

α1B adrenoceptor were performed in TE (50 mM tris, 500 mM EDTA, pH 7.4) buffer. 5.2.2 IP accumulation COS-1 cells were transiently transfected as per section 2.8 and plated in 96 well plates in the presence of [3H]myo-inositol as per section 2.9. Briefly, 48 hours post- transfection, cells were pre-treated with C9 bisacridine or vehicle for 20 mins. Cells were stimulated with noradrenaline for 30 mins and the reaction terminated by addition of 50 µL 400 mM formic acid and stored at -80°C before extraction with AG 1-X8 formate resin, and quantification by liquid scintillation counting. 5.2.3 Data analysis Dissociation curves were best fit by a one-site exponential decay curve in

GraphPad Prism v6. Kobs/Koff ratios were transformed to –log10(Kobs./Koff) to generate values used for statistical analysis. log(Kobs/Koff) ratios were compared between receptors using two-way ANOVA and Tukey post-test. EC50(diss) estimates were obtained from concentration-response curves for acridines by fitting a sigmoidal dose- response curve in GraphPad Prism v6. IP accumulation curves were fit with a variable slope sigmoidal dose-response curve in GraphPad Prism v6. All values were compared by one-way ANOVA with Tukey post-test. An estimate of C9 affinity was made using the method of Ehlert (1988). Where a non-competitive antagonist causes a decrease in maximal receptor activation, a double reciprocal plot of equi-effective doses of agonist in the absence and presence of antagonist should generate a straight line. The slope of the line can be used in the equation:

Chapter 5 Non-competitive effects of the 9-aminoacridines

[�] � = � �� − 1 where B is the insurmountable antagonist.

Chapter 5 Non-competitive effects of the 9-aminoacridines

5.3 Results 3 5.3.1 Dissociation of [ H]prazosin from the α1 adrenoceptors Preliminary experiments were performed to identify the most suitable conditions for dissociation kinetics experiments. It was observed that [3H]prazosin dissociates from the 3 α1A adrenoceptor in HEM buffer with a half-life of 14 minutes while [ H]prazosin dissociates from the α1B adrenoceptor over 8-fold slower with an estimated half-life of 118 minutes and dissociation was not complete after 5 hours (Figure 5.1A). While dissociation from the α1A adrenoceptor occurs within a time period that would allow pharmacological modulation to be easily observed, it was estimated that complete dissociation from the α1B adrenoceptor would take in excess of 8 hours. Therefore,

HEM buffer was deemed unsuitable to use with the α1B adrenoceptor as identification of a positive modulator of binding, i.e. one that would slow the dissociation of radioligand, may be difficult to identify. Dissociation of [3H]prazosin was repeated in TE binding buffer for both receptors as per the method used by Sato et al. (2012) for the α1B 3 adrenoceptor. Dissociation of [ H]prazosin from the α1A adrenoceptor is increased compared to HEM buffer with a half-life of 6 minutes. This is relatively rapid and may make the identification of an α1A adrenoceptor negative modulator i.e. one that increases 3 radioligand dissociation, difficult to identify. Dissociation of [ H]prazosin from the α1B adrenoceptor also increased in TE buffer with a half-life of 33 minutes (Figure 5.1B). This increased dissociation rate in TE buffer would allow for identification of both positive and negative allosteric modulators of the α1B adrenoceptor. The absence of Mg2+ changes the ionic strength of the two buffers, but neither was ideal for both receptors. Thus, HEM buffer was deemed most appropriate for observing [3H]prazosin dissociation from the α1A adrenoceptor while TE buffer was considered most 3 appropriate for observing [ H]prazosin dissociation from the α1B adrenoceptor. All subsequent binding kinetics assays were performed in these buffers. As the α1A subtype represents the most validated therapeutic target (Perez & Doze, 2011) and the α1B subtype represents a common source of off-target activity (Carruthers, 1994; Cavalli et al., 1997), the modulatory effects of the bisacridines on these two receptors were characterised. The most obvious candidate for the difference in [3H]prazosin between the HEM and TE buffers is the presence of divalent magnesium cations. Mg2+ has previously been shown to increase the affinity of agonists at the α1 adrenoceptors

Chapter 5 Non-competitive effects of the 9-aminoacridines

A: HEM buffer

B: TE buffer

3 Figure 5.1 [ H]prazosin dissociation from α1A and α1B adrenoceptors 3 [ H]prazosin dissociation from α1 adrenoceptors in (A) HEM buffer and (B) TE buffer. Receptor expressing membranes were preincubated with 250 pM [3H]prazosin for 1 hour before reassociation was inhibited by 100 µM phentolamine. Non-specific binding was determined using 100 µM phentolamine. Points and bars represent the mean ± SEM for a representative experiment performed in duplicate.

Chapter 5 Non-competitive effects of the 9-aminoacridines

(Glossmann et al., 1980), mostly through promotion of G protein coupling (Colucci et al., 1984) i.e. G protein coupling stabilises an agonist preferring state of the receptor. Prazosin affinity was shown to be unaffected by the presence of Mg2+ (Glossmann et al., 1980) so it is possible that both association and dissociation rates are changed proportionally and the effect is hidden from simple equilibrium binding assays. 5.3.2 9-aminoacridines increase the dissociation rate of [3H]prazosin The observed changes in competition binding slopes of some of the bisacridines (Table

4.2) suggested a degree of cooperativity between two binding sites on the α1 adrenoceptors. The dissociation rate of [3H]prazosin was observed in the absence and presence of all available acridine compounds at 100 μM to test whether this effect was being mediated by an allosteric mechanism. This concentration was chosen as solubility of the bisacridines, particularly those with longer methylene linker chains, limited their use to a maximum final concentration of 100 µM. At 100 µM, 9-aminoacridine, tacrine, and all bisacridines except C2 and C3 significantly increased the dissociation rate of 3 [ H]prazosin from the α1A adrenoceptor (P < 0.05)(Table 5.1) in a linker-length dependent manner (r2=0.86, P<0.001)(Figure 5.2) and all compounds increase the 3 dissociation rate of [ H]prazosin from the α1B adrenoceptor (P < 0.001)(Table 5.1) in a linker-length dependent manner (r2=0.74, P<0.001)(Figure 5.2). C2-C9 bisacridines all produced a greater proportional increase in dissociation rate at the α1B adrenoceptor (P <

0.01)(Table 5.1, Figure 5.2), while C12 produced the greater observed effect at the α1A adrenoceptor (Table 5.1, Figure 5.2). To investigate whether the potency of the acridines to modulate the dissociation rate of [3H]prazosin from the adrenoceptors was correlated with the observed binding selectivity, as observed in section Error! Reference source not found., the α1A selective C4 bisacridine, the non-selective C9 bisacridine, as well as the monovalent 9- aminoacridine were chosen for a more complete characterisation. Tacrine was also included to investigate whether planarity of the molecule was a necessary feature for modulation.

9-aminoacridine causes a maximal 3.2 fold increase in dissociation rate at the α1A adrenoceptor and a 5.5 fold increase in dissociation rate at the α1B adrenoceptor at 100 μM (Table 5.1). Tacrine shows a similar, albeit slightly less efficacious profile resulting in a 2.1 fold increase in dissociation rate from the α1A adrenoceptor and a 4.2 fold increase from the α1B adrenoceptor at 100 µM. It was not clear whether this effect was

3 Table 5.1 Dissociation rates of [ H]prazosin from the α1A and α1B adrenoceptors

α1A adrenoceptor α1B adrenoceptor

Koff t1/2 Kobs/Koff log(Kobs/Koff) Koff t1/2 Kobs/Koff log(Kobs/Koff) Control 0.05 ± 0.01 13.3 1.00 0.00 0.02 ± 0.00 32.2 1.00 0.00 9-aminoacridine 0.17 ± 0.02 4.1 3.16 0.48** 0.14 ± 0.01 4.8 5.47 0.74*** C2 bisacridine 0.08 ± 0.02 8.7 1.49 0.14 0.11 ± 0.01 6.1 4.43 0.63*** C3 bisacridine 0.11 ± 0.03 6.2 2.08 0.28 0.13 ± 0.00 5.3 5.01 0.70*** C4 bisacridine 0.18 ± 0.05 3.8 3.46 0.49** 0.23 ± 0.00 3.0 9.02 0.95*** C5 bisacridine 0.17 ± 0.03 4.0 3.22 0.48** 0.36 ± 0.01 1.9 13.86 1.13*** C6 bisacridine 0.40 ± 0.01 1.7 7.31 0.86*** 0.49 ± 0.07 1.4 19.43 1.26*** C7 bisacridine 0.37 ± 0.07 1.9 6.69 0.81*** 0.76 ± 0.04 0.9 29.47 1.46*** C9 bisacridine 0.96 ± 0.09 0.7 17.64 1.24*** 1.72 ± 0.65 0.4 62.32 1.78*** C10 bisacridine 1.24 ± 0.14 0.6 22.66 1.35*** 1.48 ± 0.66 0.5 62.95 1.67*** C12 bisacridine 4.38 ± 1.39 0.2 82.85 1.84*** 0.72 ± 0.05 1.0 27.56 1.43*** Tacrine 0.10 ± 0.01 6.6 2.08 0.31* 0.07 ± 0.01 10.5 4.18 0.61*** 3 -1 Koff: Dissociation rate of [ H]prazosin (min ). Kobs/Koff: Ratio of the observed dissociation rates in the presence and absence of 100 µM modulator. 3 t1/2: Half-life of [ H]prazosin dissociation (mins). *, **, *** P < 0.05, 0.01, 0.001 compared to control. Values are given as mean ± SEM n=3-6

Chapter 5 Non-competitive effects of the 9-aminoacridines

A: α1A adrenoceptor

B: α1B adrenoceptor

3 Figure 5.2 Increase in [ H]prazosin dissociation rate from the α1A and α1B adrenoceptors in the presence of 100 µM acridines 3 α1A(A) and α1B(B) adrenoceptors were preincubated with 250 pM [ H]prazosin for 1 hour at room temperature. Reassociation was inhibited by the addition of 100 µM phentolamine with or without 100 µM of each compound. Results are expressed as the log of the ratio of the observed [3H]prazosin dissociation rate in the presence of tested acridine to the dissociation rate in the presence of phentolamine alone. Bars and error bars represent the mean ± SEM of 3 individual experiments performed in duplicate. Blue lines (▬)indicate the linear trend of bisacridines C2-C12.

Chapter 5 Non-competitive effects of the 9-aminoacridines saturating for the monovalent ligands, but the allosteric effects appear to be at concentrations higher than their binding data would suggest. 9-aminoacridine has 247 nM affinity at the α1A adrenoceptor yet allosteric properties were only observable at a minimum concentration of 30 µM (Figure 5.3A, Table 4.1). C4 bisacridine caused a maximum 3.5 fold increase in dissociation at the α1A adrenoceptor which did not appear to saturate at its solubility limits. C4 bisacridine did not cause an observable increase in dissociation rate at 10 μM, well above C4’s apparent affinity of 21 nM for the α1A adrenoceptor (Table 4.1, Figure 5.3). C4 bisacridine caused a maximum 9.0 fold increase in dissociation at the α1B adrenoceptor that appears to be close to saturating, producing an estimated EC50(diss) of 22 µM, a concentration ~100-fold higher than its apparent affinity (Table 4.1). C4 bisacridine consistently produces a greater increase in dissociation rate from the α1B adrenoceptor at 10, 30, and 100 μM compared to the α1A adrenoceptor, (Figure 5.3, Figure 5.4) despite demonstrating greater than 10-fold selective binding for the α1A adrenoceptor in competition binding assays (Table 4.1). Unfortunately, the use of different buffers in dissociation kinetics assays for each of the subtypes makes it difficult to compare potency between the receptor subtypes and will need to further optimised for valid comparisons in the future.

C9 bisacridine caused a 17.6 fold increase in dissociation rate from the α1A adrenoceptor at 100 μM (P<0.001)(Table 5.1) and a 62.3 fold increase in dissociation rate from the α1B adrenoceptor (P<0.001)(Table 5.1). This produced EC50(diss) estimates of 32 and 6 µM for the α1A and α1B adrenoceptors, respectively. Despite C4 having higher affinity than C9 at the α1A adrenoceptor, this was not translated into increased modulation potency with C4 displaying decreased modulating potency (Figure 5.3) and efficacy (Figure 5.2) compared to C9 at the α1A adrenoceptors despite having higher apparent affinity.

5.3.3 C9 bisacridine is a non-competitive antagonist of α1A adrenoceptor activation To test whether the acridines were interacting non-competitively with the endogenous agonist noradrenaline, activation of the α1A adrenoceptor was tested in the absence and presence of C9 bisacridine, one of the most potent and efficacious modulators of [3H]prazosin dissociation. C9 bisacridine caused a significant reduction in the potency of noradrenaline at the α1A adrenoceptor at concentrations of 10 μM and above (P<0.05)(Table 5.2, Figure 5.5) as well as a decrease in the maximum observed

Chapter 5 Non-competitive effects of the 9-aminoacridines

A B

C D

E F

G H

Chapter 5 Non-competitive effects of the 9-aminoacridines

3 Figure 5.3 Dissociation of [ H]prazosin from the α1A adrenoceptor 3 [ H]prazosin dissociation from α1A adrenoceptor membranes in the absence and presence of 9-aminoacridine, C4 bisacridine, C9 bisacridine, and tacrine. Membranes were preincubated with 250 pM [3H]prazosin for 1 hour at room temperature in 400 µL HEM buffer. [3H]prazosin reassociation was inhibited by the addition of 100 µL phentolamine with or without test compound at concentrations shown. A, C, E and G show time-dependent dissociation curves. B, D, F and H show concentration response curves. Dashed line represents Kobs/Koff = 1. Points and error bars are the mean ± SEM of 3 individual experiments performed in duplicate.

Chapter 5 Non-competitive effects of the 9-aminoacridines

A B

C D

E F

G H

A B

C D

Chapter 5 Non-competitive effects of the 9-aminoacridines

3 Figure 5.4 Dissociation of [ H]prazosin from the α1B adrenoceptor 3 [ H]prazosin dissociation from α1B adrenoceptor membranes in the absence and presence of 9-aminoacridine, C4 bisacridine, C9 bisacridine, and tacrine. Membranes were preincubated with 250 pM [3H]prazosin for 1 hour at room temperature in 400 µL HEM buffer. [3H]prazosin reassociation was inhibited by the addition of 100 µL phentolamine with or without test compound at concentrations shown. A, C, E and G show time-dependent dissociation curves. B, D, F and H show concentration response curves. Dashed line represents Kobs/Koff = 1. Points and error bars are the mean ± SEM of 3 individual experiments performed in duplicate.

Chapter 5 Non-competitive effects of the 9-aminoacridines response at concentrations of 30 μM and above (P<0.001)(Table 5.2, Figure 5.5). 100

µM C9 also caused a small but significant increase in receptor signalling via the IP3 pathway in absence of noradrenaline (Table 5.2). Given the observations that the 9-aminoacridines were displaying allosteric effects at the α1A adrenoceptor, the IP accumulation data was fit to an operational model of allosterism (equation 6)(Leach et al., 2007), however it did not fit well, generating unrealistic or poor fit values e.g. R2 < 0.5, β < 0, or α > 1012. This is possibly due to the bitopic, rather than purely allosteric binding mode of the bisacridines. Instead, the method of Ehlert (1988) was applied to the IP accumulation data to estimate affinity of C9. 30 μM C9 produces an approximate 50% decrease in the maximum signal, making it the most ideal concentration for use with this method (Kenakin, 1997) and generates an affinity estimate of 19.0 ± 4.9 μM (n=4), 71-fold higher than the apparent affinity observed for C9 at the α1A adrenoceptor in section Error! Reference source not found.. Substituting this value for KB in the operational model still did not improve the fit.

Figure 5.5 Noradrenaline induced total soluble inositol phosphate accumulation COS-1 cells were transiently transfected with α1A adrenoceptor then incubated overnight in the presence of [3H]myo-inositol. After 24 hours of incubation, media was exchanged for serum-free DMEM in the presence or absence of C9 bisacridine for 20 minutes followed by stimulation with noradrenaline for 30 minutes. Unstimulated points are shown in the left segment of the X-axis. All values were normalised between unstimulated response and maximum noradrenaline induced response and fit by non- linear regression to a variable-slope dose-response curve using GraphPad Prism 6. 96

Chapter 5 Non-competitive effects of the 9-aminoacridines

Points and bars represent the mean ± SEM of n=3-5 experiments performed in triplicate. There are some limitations on the extent to which the allosteric effects of the acridines can be characterised. The symmetrical nature makes it impossible to separate the two pharmacophores to study the orthosteric and allosteric effectors individually, as has been done with heterobivalent molecules identified for other GPCRs (Keov et al., 2013; Lane et al., 2014; Valant et al., 2008). The acridines also appear to have higher affinity for the orthosteric site than the allosteric site. Consequently, any allosteric effect of the monovalent ligands will not be observable until the orthosteric site is predominantly saturated, diminishing the ability to observe allosteric effect on other orthosteric ligands. It is thus not practical to observe alterations in many radioligand properties, such as affinity and association rate, let alone the properties of competing, unlabelled ligands in affinity ratio experiments, which would create an enormously complex system.

Chapter 5 Non-competitive effects of the 9-aminoacridines

Table 5.2 Best-fit values of total soluble IP accumulation Noradrenaline (NA) NA + C9 10 μM NA + C9 30 μM NA + C9 100 μM mean ± S.E.M n mean ± S.E.M n mean ± S.E.M n mean ± S.E.M n pEC50 6.2± 0.1 5 5.6 ± 0.2* 4 5.4 ± 0.1** 4 5.0 ± 0.2*** 4 Slope 1.6 ± 0.2 5 1.4 ± 0.2 4 1.8 ± 0.3 4 1.8 ± 1.0 3

Emax (%) 100.8 ± 2.1 5 75.3 ± 11.3 4 45.8 ± 11.0*** 4 38.7 ± 5.0*** 4 Basal (%) 0.3 ± 0.3 5 5.4 ± 2.8 4 2.1 ± 1.4 4 17.1 ± 5.1** 5 pEC50: negative log of the concentration required to cause 50% maximal effect. Slope: slope factor Emax: % maximum noradrenaline response. Basal: agonist independent receptor activity, expressed as % specific noradrenaline effect. *, **, *** P < 0.05, 0.01, 0.001 compared to noradrenaline alone by one-way ANOVA with Tukey post-test.

Chapter 5 Non-competitive effects of the 9-aminoacridines

5.4 Discussion The acridines demonstrated a cooperative mode of binding in addition to subtype selectivity at the α1 adrenoceptors, which prompted the testing of the acridines for allosteric interactions with the α1 adrenoceptors. Allosteric modulators of the α1 adrenoceptors are of great interest as they represent a novel strategy in the pursuit of an efficacious drug with an improved side effect profile (Conn et al., 2009; Melancon et al., 2012; Nickols & Conn, 2014). The hypothesis that the acridines are able to bind to an allosteric site on these receptors is supported by the observed increases in [3H]prazosin dissociation from the

α1A and α1B adrenoceptors combined with the reduction in maximum signalling at the

α1A adrenoceptor. Based on previous studies of tacrine at the muscarinic receptors (Kiefer-Day et al., 1991; Pearce & Potter, 1988; Tränkle et al., 2005; Tränkle et al., 2003), it was hypothesised that tacrine, and the other acridines, would act as positive modulators of antagonist binding by slowing dissociation of [3H]prazosin. However, in contrast to tacrine’s actions at the muscarinic receptors, the acridines behaved as negative modulators of [3H]prazosin binding, increasing the dissociation rate of 3 [ H]prazosin at the tested α1 adrenoceptors. The difference in effect could be attributable to probe dependence i.e. [3H] prazosin exhibits differing cooperativity with tacrine than [3H]NMS or [3H]3-quinuclidinyl benzilate (QNB), or the difference could arise if the allosteric binding site on the α1 adrenoceptors is different to that described for the muscarinic receptors. Allosteric modulators of the muscarinic receptors are some the most comprehensively described of rhodopsin-like GPCRs. The allosteric binding site of the muscarinic receptors has been fairly well defined by mutagenesis studies to the extracellular regions of the receptor with major contributions from tyrosines W3.28 and W7.35 (Matsui et al., 1995) that are conserved across all muscarinic receptors. The ECL2 EDGE motif, which is unique to the M2 muscarinic receptor, has also been demonstrated to be involved in the binding cooperativity of allosteric modulators at this receptor subtype (Leppik et al., 1994). Recent efforts to crystalise GPCRs have yielded a structure of the M2 muscarinic receptor with a bound positive allosteric modulator, LY2119620 (Kruse et al., 2013). This structure showed the allosteric modulator bound to an allosteric pocket comprised of residues from TMV, TMVI, TMVII, ECL2 and ECL3 including the predicted W4227.35 and E172ECL2. This site identified in the crystal

Chapter 5 Non-competitive effects of the 9-aminoacridines

structure of the M2 muscarinic receptor corresponds to an extracellular vestibule that was previously observed in molecular dynamics simulations of the β2 adrenoceptor (Dror et al., 2011). The extracellular vestibule is a low affinity pocket where orthosteric ligands are proposed to bind transiently before progressing to their final pose in the orthosteric pocket (Dror et al., 2011). As a low affinity site, the vestibule will have a high off-rate and acts as a capture-and-release system that creates a high micro- concentration of ligand around the entrance to deep binding clefts, as are often found for the rhodopsin-like GPCRs that may not be easily accessible for a ligand from the bulk solvent. Such a mechanism is well described for other proteins where binding sites are often buried deep within the protein (Pang et al., 1996). The predicted affinity of alprenolol for the binding vestibule is 5 µM (Dror et al., 2011) compared to 0.9 nM affinity for the receptor (Baker, 2005), and the predicted affinity of C9 bisacridine from the IP accumulation assay was 19 µM. These values are similar, and both are well above their observed affinities in competition binding assays, possibly indicating that the non- competitive effects of C9 bisacridine, in the functional assays at least, are representative of its affinity at the allosteric pocket. Changes in [3H]prazosin dissociation rate caused by C9, and all of the tested acridines, are only observed in the mid-micromolar range further supporting the idea that the non-competitive effects are attributable to a low- affinity interaction that does not correspond to competitive, orthosteric binding.

The observation that the allosteric modulator of the M2 muscarinic receptor is bound to the binding vestibule suggests that an allosteric ligand is simply a drug which has high affinity for the binding vestibule i.e. it is “stuck” in the binding vestibule and does not readily dissociate but can still perturb the orthosteric site. Allosteric modulation arises because there a mechanistic link between the binding vestibule and orthosteric binding site; binding of ligands to the vestibule in simulations of the β2 adrenoceptor is associated with a pre-emptive ‘de-wetting’ of the orthosteric site to accommodate the incoming ligand (Dror et al., 2011). Thus binding vestibules can be seen to promote binding to the orthosteric binding site by altering the orthosteric binding site to a state amenable to ligand binding but an allosteric modulator remains bound the vestibule/allosteric site and continues to perturb the normal state of the orthosteric site. At the M2 muscarinic receptor, it has been observed that orthosteric ligands NMS and oxotremorine-M can slow the dissociation rate of the radioligand [3H]NMS, but only at millimolar concentrations, well above their apparent affinity

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(Redka et al., 2008) and even higher than the estimated affinity for alprenolol at the binding vestibule of the β2 adrenoceptor further strengthening the intrinsic link between endogenous ligands and the allosteric site/binding vestibule. An unfavourable implication for the development of allosteric modulators is that if allosteric sites are inherently low-affinity, then it may be difficult to find a drug to target these sites within a reasonable therapeutic concentration/dose. A potential complication is that if the orthosteric site and allosteric site/binding vestibule are recognising the same molecules, then any allosterically acting ligand may also have affinity for the orthosteric site. A successful allosteric ligand will therefore require substantial selectivity for the allosteric over the orthosteric site. If the vestibule is recognising the same ligands as the orthosteric site (Dror et al., 2011) then is stands to reason that the allosteric and orthosteric sites are, to some degree, similar. The suggestion that the orthosteric and allosteric sites of the α1 adrenoceptors are similar is further supported by the observation that both the competitive and non-competitive effects of the monovalent tacrine and 9-aminoacridine are still being mediated by the same molecule, just at different concentrations. This model suggests that the molecules are competing with the radioligand [3H]prazosin for the orthosteric binding site at lower concentrations, but are also able to occupy the allosteric site/binding vestibule at higher concentrations where they can influence the dissociation rate of [3H]prazosin. Tacrine and 9-aminoacridine, while demonstrating that these sites can recognise the same ligand, would not be ideal as allosteric modulators as their orthosteric affinity is higher and would saturate the orthosteric site before exerting any appreciable allosteric effect, which is likely the reason that these ligands demonstrate no cooperativity in binding. A similar result is also observable for the binding of amiloride analogs at the α1A adrenoceptor where simple, competitive-like binding is observed in competition binding assays at moderate concentrations between 100 nM and 10 µM, but non-competitive interactions with [3H]prazosin are observed at concentrations above 30 µM (Leppik et al., 2000). An unexpected observation was that the bivalent C4 and C9 bisacridine molecules caused greater increases in [3H]prazosin dissociation than the monovalent 9- aminoacridine, and at lower concentrations, at odds with the original hypothesis. While conjugation of two ligand pharmacophores into a single, bivalent molecule can increase affinity and/or efficacy (Portoghese, 1989), the bivalent molecules should offer no

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Chapter 5 Non-competitive effects of the 9-aminoacridines additional effect over the monovalent equivalent in this experimental paradigm as the orthosteric site of the receptor would already be occupied by the radioligand, [3H]prazosin, and be competing with the higher affinity orthosteric ligand phentolamine, which is in a vast comparative excess. The only other available site on a monomeric receptor should be the allosteric site, thus the higher-affinity orthosteric site would not be available to tether the bivalent molecules to the receptor and cause such an increased modulation effect. While it has been suggested that there are two allosteric binding sites for tacrine on the muscarinic receptors (Kiefer-Day et al., 1991; Tränkle et al., 2005), monovalent tacrine binding shows cooperativity at these receptors whereas it does not at the α1 adrenoceptors indicating that the allosteric site of the α1 adrenoceptors cannot accommodate two tacrine molecules. Alternatively, this observation could be explained if the adrenoceptors are forming dimers (or higher order oligomers). One possibility is that the bisacridines are able to bind bitopically at the allosteric sites of two dimerised or adjacent receptors. This could again provide a ‘tether’ and create a high micro-concentration that promotes binding at a second, proximal allosteric site, thus explaining the advantage of bisacridines over monovalent 9-aminoacridine. Alternatively, the bisacridines may be binding bitopically at one protomer and modulating ligand binding at a second. Modulation of one protomer by a dimer partner is possible as only a KD concentration of radioligand was used, meaning only 50% of orthosteric sites are occupied by the radioligand, and 50% remain unoccupied. A bivalent D2 receptor ligand, SB269652, has been demonstrated to bind and modulate across a dimer pair (Lane et al., 2014), so this concept is not unprecedented. The super- saturating concentration of phentolamine used, however, would likely occupy any other available orthosteric sites unless phentolamine binding is restricted to only one dimer partner. It has, however, been reported that D2 dopamine receptor dimers form a single signalling unit that is activated non-symmetrically; agonist binding at one protomer is sufficient to activate a single G protein, but requires to the presence of (at least) two receptors (Han et al., 2009). Orthosteric binding of the radioligand, [3H]prazosin, and competing ligand, phentolamine, may therefore be restricted to a single protomer while the bisacridines are capable of binding bitopically to the dimer partner, thereby exerting its effects. A state-specific dimer interface has also been identified at the D2 receptor, involving TMIV (Guo et al., 2005) thereby explaining how ligand binding at one protomer can influence a dimer partner.

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Ligands of the D2 dopamine receptor have also been identified that will selectively only bind to monomers. If a ligand can preferentially bind to monomers, dimers, or higher order oligomers, then it could be targeted toward target tissue where receptors exist as monomers or oligomers if non-target tissues also express the target receptor, but in a different oligomeric state. “Oligomer specificity” potentially presents another layer of selectivity that could be engendered into novel ligands. Oligomer specific interactions are undoubtedly complex behaviours. The allosteric effects of 5 out of the 6 amiloride anologs tested at the α1 adrenoceptor were in better agreement with a two site allosteric model compared to a one-site model (Leppik et al., 2000). Not all parameters could be derived from the data, but the possibility of binding across dimer pairs was also postulated. The major drawback is the difficulty in applying a model to such a system; the number of parameters is unfeasibly large. The most immediate indicator of whether this is a dimer-dependent effect would be to test these compounds on receptor monomers, in a system such as nanodiscs. Nevertheless, both the data presented in this thesis as well as that for the amiloride analogs demonstrates that these interactions are complex, and not adequately explained by single allosteric site models. It was furthermore observed that C9 bisacridine was a more potent and efficacious 3 modulator of [ H]prazosin dissociation than C4 bisacridine at both the α1A and α1B adrenoceptors despite C9 having significantly lower apparent affinity at the α1A adrenoceptors and little difference in affinity at the α1B adrenoceptor. Thus, the ability to allosterically modulate the receptor is not dictated by the same determinants that govern selective, high affinity binding and allosteric effects are likely to originate from a different region of the receptor. It appears that a linker length of around 9 carbons is ideal for maximum interaction with the allosteric site as the allosteric effect appears to plateau around the 9 carbon mark at the α1B adrenoceptor, and binding cooperativity peaks at the 9-carbon linker for the α1 adrenoceptors (Table 4.2). A linker of 9 carbons has been shown to be optimal for bivalent ligands of other biogenic amine receptors. THRX-198321 is a reciprocally bivalent ligand that is comprised of linked muscarinic and β2 adrenoceptor binding moieties in a single molecule and binds to both muscarinic receptors and the β2 adrenoceptor. The binding of the orthosteric moieties to their corresponding receptor is positively promoted by the presence of the alternate moiety, thus ‘reciprocally bivalent’ (Steinfeld et al., 2011).The

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ideal linker length at both the muscarinic receptors and β2 adrenoceptor was also found to be 9 carbons suggesting similar spacing between the orthosteric and allosteric sites at the muscarinic receptor, β2 and α1 adrenoceptors. This similarity provides evidence that the bisacridines possess their greater effects over the monovalent 9-aminoacridine due to bitopic binding at a single receptor, rather than two allosteric sites across a receptor dimer. This ligand also implies a conserved nature of orthosteric and allosteric sites across related receptors; orthosteric muscarinic receptor ligands are exerting allosteric effects at the β2 adrenoceptor and vice-versa. There is clearly some similarity between the orthosteric muscarinic site and the β2 adrenoceptor allosteric site, which is likely binding β2 adrenoceptor orthosteric ligands with low affinity. A therapeutic advantage of allosteric ligands is the ceiling effect that arises from the insurmountable nature of ternary complexes formed between receptors and non- competitive drugs (Christopoulos, 2002; Conn et al., 2009; May & Christopoulos, 2003). The linker-length dependent changes in efficacy and potency of the allosteric effects of bitopic compounds raise the possibility of being able to customise this ceiling height. The orthosteric and allosteric sites are effectively “competing” for occupancy by a single molecule and shorter linkers would restrict interaction with allosteric residues when tethered to the orthosteric site. Such a mechanism was demonstrated at the M2 muscarinic receptor where the allosteric site is reasonably well mapped. Heterobivalent ligands were synthesised according to the predicted distance between the orthosteric and known allosteric site (Bock et al., 2012). A linker length of 6 carbons was predicted to optimally place the allosteric moiety in the allosteric pocket, and this was confirmed experimentally. Extending the linker or mutating the pocket reduced the effect of the allosteric moiety. Thus, bitopic ligands may offer an additional advantage over purely allosteric ligands; by promoting or restricting the degree to which the allosteric moiety can interact with the allosteric site, the magnitude of the therapeutic effect can be more finely regulated. When the bitopic compound, McN-A-343, and allosteric truncations were tested on the M2 muscarinic receptor, they displayed similar potency for decreasing association and dissociation rate, but the bitopic compound was much more potent than the allosteric truncation at inhibiting association (Valant et al., 2008). An interpretation of this data might be that McN-A-343 is more potent at inhibiting association rate than the truncated compound because McN-A-343 is able to tether the molecule to the high affinity, orthosteric site creating a high micro-concentration and

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Chapter 5 Non-competitive effects of the 9-aminoacridines promoting interaction with the allosteric site while the allosteric truncation does not possess this ability. This study also appears to show that the partial agonist activity of McN-A-343 occurs at a lower concentration than the effects on dissociation kinetics suggesting this may be originating from high affinity interaction with the orthosteric site rather than “allosteric agonism”. McN-A-343 is a relatively small ligand compared to the bisacridines, so it is possible, based on the observations made here, that increasing the distance between the orthosteric and allosteric pharmacophores of the molecule would increase the allosteric effect at the muscarinic receptors. These predictions are, of course, speculative and would need to be verified experimentally. While the acridines seem to have low affinity for the allosteric site, and the binding of tacrine at least, has been demonstrated at other aminergic GPCRs, further refinement may generate more potent and selective drugs, as has been done to improve allosteric modulators of the muscarinic and metabotropic glutamate receptors (Bridges et al., 2013; Huynh et al., 2013). Importantly, the linker lengths have provided an approximation of the location of the allosteric site that can be used with in silico techniques to help identify the exact location of the allosteric pocket, which will in turn be useful for further design and development of allosteric ligands.

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Identification of the allosteric site of the α1A adrenoceptor

6.1 Introduction It has been demonstrated that the acridines have the ability to allosterically modulate the α1 adrenoceptors, likely through a bitopic interaction with the orthosteric and allosteric sites of the receptor (Chapter 5). Mutagenesis and crystallography studies have demonstrated that the binding site of allosteric modulators for the muscarinic receptors, archetypal members of small molecule, rhodopsin-like GPCRs, is comprised of residues in ECL3 and TMVII on the extracellular face of the receptors (Gregory et al., 2010; Haga et al., 2012; Kruse et al., 2013; Voigtländer et al., 2003). Tacrine had also previously demonstrated the ability to allosterically modulate the muscarinic receptors (Pearce & Potter, 1988; Tränkle et al., 2005) albeit with somewhat different pharmacology (Kiefer-Day et al., 1991) to that observed at the α1 adrenoceptors (Chapter 5) indicating that its binding maybe different between the two classes of receptors.

Identification and description of the allosteric binding pocket for the α1 adrenoceptors would facilitate a more informed drug design and development process.

Any allosteric therapeutic of the α1 adrenoceptors would need a number of improvements over the acridines which possess a number of features that are not ideal for therapeutic use. The bisacridines are neither “drug-like” nor “lead-like” molecules; the bisacridines are too hydrophobic, and too large and are unlikely to represent orally bioactive molecules (Congreve et al., 2003; Lipinski et al., 2001). Additionally, the planar nature of the acridines makes them ideal DNA intercalators, a property not suitable for a therapeutic. The inclusion of tacrine in the test sets so far has partially demonstrated that modification for improvement of these molecules is possible. Indeed, the simple saturation of one ring within the 9-aminoacridine structure was sufficient to remove the intercalating property of these molecules. The increasing length of the bisacridines presents a unique advantage in that these

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Identification of the allosteric site of the α1A adrenoceptor ligands can be used as a “molecular ruler” to determine the relative location of the allosteric site, if they are indeed binding bitopically as has been hypothesised in this thesis. The 9 carbon linker has emerged as a likely candidate to be of appropriate length to span the distance between the orthosteric and allosteric sites in both competition binding and dissociation kinetics assays (Table 4.2, Figure 5.2). To identify potential allosteric binding site, in silico methods will be used to dock the acridines into homology models of the α1 adrenoceptors, as no crystal structure is currently publically available. 6.1.1 Hypotheses

The allosteric binding site of the α1 adrenoceptors exists at the extracellular surface of the receptor.

C9 bisacridine will dock into α1 adrenoceptor homology models and make simultaneous contact with both the canonical orthosteric binding pocket, as well as the allosteric site of the receptors.

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6.2 Methods 6.2.1 Docking Docking was performed using the GOLD algorithm as implemented in Discovery Studio v4. Homology models were provided by Mrs. Kaniz Urmi and based on the dopamine D3 receptor crystal structure (PDB ID: 3PBL). All ligands were protonated at the location shown in Figure 1.7 and Figure 4.1 except phentolamine which was docked in its unprotonated state, as this is predicted to be physiologically relevant (Matijssen et al., 2012). All ligands were docked as a single, biologically active isomer except HEAT, which was docked separately as (S) and (R) isomers which show little biological difference. All ligands were minimised in Discovery Studio using the CHARMM forcefield prior to docking. Binding pockets were defined manually. 100 poses were generated for each ligand. Early termination was set to “False”, Flip Pyramidal Nitrogens was set to “True”. All other settings were left as default including the GOLD scoring function. Clustering distances were determined manually by expert selection. 6.2.2 Mutagenesis Mutagenesis for the Q177G and QIN177-179ECL2GVT mutants was performed by site-directed mutagenesis using Phusion polymerase and primers given in Table 6.1. WT DNA was degraded using DpnI restriction enzyme and PCR products were transformed into competent DH5-α E.coli and plated onto LB-agar plates with 100 µg.µl-1 ampicillin. Colonies were picked and vectors isolated by mini-prep. Mutants were sequenced at the Australian Cancer Research Foundation Facility at the Garvan Institute for Medical Research, Darlinghurst, Australia. S832.61A, F862.64A, and E872.65A mutants were produced by Dr Junli Chen and Ms Karmen Xu using the same protocol.

Table 6.1 Mutagenesis primers Receptor mutation Primer

ECL2 α1A Q177 G F 5’-AGACCATCTGCGGTATCAACGAGGAGCC-3’ ECL2 α1A Q177 G R 5’-CTCCTCGTTGATACCGCAGATGGTCTCGTC-3’ ECL2 α1A QIN177-179 GVT F 5’-CATCTGCGGTGTAACTGAGGAGCCGGGCTAC-3’ ECL2 α1A QIN177-179 GVT R 5’-CCGGCTCCTCAGTTACACCGCAGATGGTCTC-3’ F, sense primer, R, antisense primer

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6.2.3 Transfection and membrane harvesting Transfections were performed as per section 2.5 using 20 μg DNA per 175 cm2 plate. Membranes were harvested 72 hours after transfection as per section 2.6.2 and stored in 20 mM HEPES, 1 mM EDTA + 10% glycerol at -80°C. 6.2.4 Radioligand binding assays Saturation binding assays were performed as per section 2.7.1 using 1-10 μg protein per point as determined by Bradford assay. All mutants were allowed to equilibrate for 2 hours before termination with cold PBS. Non-specific binding was determined using 100 μM phentolamine. All competition binding assays were performed as per section 2.7.2 at room temperature in HEM buffer up to a final volume of 200 μL against 250 pM [3H]prazosin. Dissociation kinetics were performed as per section 2.7.3 using HEM buffer for 3 all mutants of the α1A adrenoceptor. [ H]prazosin reassociation was prevented by the addition of 100 μM phentolamine. 6.2.5 Data analysis All saturation binding data was best fit by a one-site saturation binding curve in GraphPad Prism v6. Competition data was fit by a variable-slope competition binding curve and Ki values calculated as per the method of Cheng and Prusoff (1973).

Dissociation kinetics were fit by a one-site exponential dissociation curve. log(Kobs/Koff) ratios were calculated compared to matched, phentolamine-alone curves. All data was analysed by one-way ANOVA with Tukey post-test and included values for all receptors/mutants and ligands tested unless otherwise stated.

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6.3 Results 6.3.1 Docking The acridine compounds were docked into homology models of the three human

α1 adrenoceptors and the human 5-HT1A receptor to identify any binding sites that may account for the observed non-competitive effects. The homology models used for docking were based on the eticlopride bound, dopamine D3 receptor (PDB ID: 3PBL)(Chien et al., 2010). Models were validated by docking the aminergic antagonists phentolamine, prazosin, HEAT, and 5-methylurapidil which all made expected contacts (Table 6.2) as predicted by mutagenesis studies (Maïga et al., 2014; Porter et al., 1996; Zhao et al., 1996) confirming the integrity of the orthosteric binding site. While no such confirmation can be made for sites distinct from the orthosteric site, the dopamine D3 receptor template was chosen as it was predicted to have the most functionally similar orthosteric binding site (Figure 1.2)(Lin et al., 2013) and structurally similar extracellular domains to the α1 adrenoceptors compared to other available crystal structures such as the β1 and β2 adrenoceptors based on sequence alignments. It was anticipated that the protonated ring nitrogen of the acridines would engage in a charge interaction with the conserved D3.32, which is a common interaction for aminergic ligands, often considered critical for adrenoceptor ligand binding (Porter et al., 1996; Strader et al., 1987a; Strader et al., 1991; Strader et al., 1988; Waugh et al.,

2001). 9-aminoacridine docked into all four receptors (Table 6.3, Figure 6.1). In the α1A adrenoceptor, the representative pose (pose 3) made no interactions with D3.32, however the next highest scoring pose of the same cluster, (pose 4) did predict a H-bond 3.32 interaction between the amine group and D . At the α1B and α1D adrenoceptors, as well as the 5-HT1A receptor, docked 9-aminoacridine made the expected charge-charge interaction with D3.32. 9-aminoacridine also formed π-π interactions with the conserved 6.51 aromatic residue F at both the α1A and α1B adrenoceptors. 9-aminoacridine also made ECL2 ECL2 hydrophobic interactions with I178 in the α1A adrenoceptor and V197 in the α1B adrenoceptors. These are equivalent residues in each receptor known to be critical for selective antagonist binding to these two receptor subtypes (Zhao et al., 1996). Tacrine adopted similar poses to 9-aminoacridine in all four receptors (Figure 6.1). While the monovalent ligands, 9-aminoacridine and tacrine, docked successfully into the models, GOLD did not produce good docking poses for the bisacridines. C9 bisacridine, for example, generated a GOLDScore of -57.7 at the α1A adrenoceptor

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(Table 6.3), with similar results also seen at the remaining receptors. GOLDScores were negative for all of the bivalent ligands in contrast to what was observed for docked prazosin (Table 6.2) or the monovalent 9-aminoacridine and tacrine (Table 6.3). The most negative component was the internal van der Waals score which was far more negative than that seen for docked prazosin (Table 6.3) i.e. the ligands were not accommodated within the predicted binding pocket without significant intramolecular steric clashes within the ligand. Some poses of the bisacridines also returned negative external van der Waals scores (Table 6.4). One of the most extreme examples was pose

1 of C9 bisacridine at the α1D adrenoceptor, generating an external van der Waals score of -1500. While 5-methylurapidil also generated low GOLDScores, with a negative internal van der Waals component, these were never as negative as the bisacridines, nor did the docked poses generate any intra- or intermolecular steric clashes. As the bisacridines did not generate acceptable docking results, a series of closely related molecules, the quinolines (Figure 1.11), were docked into the homology models as a representative model system for the bivalent ligands, instead. The bisquinolines are predicted to bind to the α1 adrenoceptors in a similar, bitopic manner (Chen et al., 2013) and are negative allosteric modulators of the α1 adrenoceptors (Chen, 2015) although they show a slightly different selectivity profile. C9 bisquinoline when docked into the

α1A adrenoceptor produced similar external van der Waals score as prazosin indicative of a more acceptable docking pose (Table 6.4). 4-aminoquinoline was also docked into the four homology models (Figure 6.1, Table 6.5). The major clusters observed for 4-aminoquinoline were outside the 2.61 orthosteric pocket at the α1A and α1B adrenoceptors and showed interactions with S , F/L2.64, and E2.65 (Table 6.5). This “allosteric” pose of 4-aminoquinoline adopted an almost identical position as the allosteric cluster of 9-aminoacridine at the α1A adrenoceptor (Figure 6.1). Orthosteric clusters were observed for 4-aminoquinoline at 5.46 6.52 the α1A and α1B adrenoceptors, making interactions with S and F but lacking any interaction with D3.32 (Table 6.5). The orthosteric poses for 9-aminoacridine and 4- aminoquinoline did not superimpose at the α1A and α1B adrenoceptors (Figure 6.1) reflecting the observation that 4-aminoquinoline has at least 10 fold lower affinity than

9-aminoacridine at all α1 adrenoceptors (Chen et al., 2013). The bisquinolines generally docked with one quinoline moiety adopting the same/similar pose as the orthosterically located 4-aminoquinoline and the second quinoline group extending towards the r

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Table 6.2 Interaction of docked, known α1 adrenoceptor antagonists

Compound Interactions 1A-AR 1B-AR 1D-AR 5-HT1A-R phentolamine Pose, Score: 3b, 45.24 17b, 46.82 1c, 45.64 15b, 44.53 H-bond/Charge: D1063.32 D1253.32 D1763.32, Y3927.43 R176ECL2 π-π: F2886.51 F3106.51 π-charge: D1253.32 Hydrophobic: V1073.33, I178ECL2, V1263.33, C1293.36, D1763.32, V1773.33, I189ECL2, A3656.55, A1895.43, F2896.52, V197ECL2, F3116.52, I248ECL2, F3656.52 L3666.65 M2926.55 L3146.55 prazosin Pose, Score: 27b, 31.75 1a, 30.85 10b, 44.59 1a, 29.40 H-bond/Charge: D1063.32, I178ECL2 D1253.32 D1763.32, S2585.42 D1163.32 π-π: F2886.51, F3087.35, F3106.51 W1723.28, F3646.51, π-charge: F3127.39 F3656.52 F1123.28, F3626.52 Hydrophobic: W1023.28, I178ECL2, V1263.33, V197ECL2, W1723.28, V1773.33, I1133.29, V1173.33, M2926.55, F3087.35 F3106.51, L3146.55, I248ECL2, F3646.51, I189ECL2, A3656.55 P3156.56 L3686.55 (R)-HEAT Pose, Score: 15b, 52.09 10b, 53.15 2b, 50.07 14b, 53.05 H-bond/Charge: D1063.32 D1253.32, E194ECL2 S1532.61 I1133.29, D1163.32 π-π: F862.64 W1213.28 F1522.60, F3646.51 F1123.28 π-charge: Hydrophobic: W1023.28, V1073.33, L1052.64, C1293.36, M1562.64, I248ECL2, A932.61, F1123.28, C1103.36, W2856.48 V197ECL2, W3076.48, F3646.51, L3686.55 V1173.33, C1203.36, F3106.51 A2035.46, W3586.48

(S)-HEAT Pose, Score: 40b, 50.90 36a, 48.40 1a, 52.93 1a, 58.28 H-bond/Charge: D1063.32, I178ECL2 C1293.36 I1133.29, D1163.32 π-π: F862.64 F3106.51 W1723.28 F1123.28 π-charge: Hydrophobic: W1023.28, V1073.33, W1213.28, A122, W1723.28, V1773.33, F1123.28, V1173.33, C1103.36, I178ECL2, V1263.33, C1293.36, I248ECL2, A2555.39, C1203.36, A186ECL2, W2856.48, F2886.51, L3146.55 F3646.51, L3686.55, I189ECL2, Y3907.52 F2896.52 P3696.56 5-methylurapidil Pose, Score: 1a, 6.04 2b, -1.60 1a, 1.92 1a, 5.39 H-bond/Charge: D1063.32 D1253.32 D1763.32 D1163.32 π-π: F862.64, F2886.51 F3347.39 Y962.64 π-charge: Hydrophobic: F862.64, V1073.33, L1052.64, V1263.33, F1522.60, M1562.64, A932.61, Y962.64, C1103.36, F3087.35, C1293.36, F3347.39 V1773.33, C1803.36, F1123.28, V1173.33, F3127.39 F3887.39 A186ECL2, A2035.46, Y3907.52 a highest scoring pose of the largest cluster, which is pose 1 b highest scoring pose of the largest cluster, which is not pose 1 c pose 1, which is not in the largest cluster

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Table 6.3 Interactions of docked acridines

Compound Interactions 1A-AR 1B-AR 1D-AR 5-HT1A-R 9-aminoacridine Pose, Score: 3b, 40.65 1a, 40.56 1a, 42.29 5b, 45.81 3.29 ECL2 (Orthosteric) H-bond: A122 C187 Charge: W2856.48, F2886.51 D1253.32 D1763.32 D1163.32 π-π: F3106.51 F1123.28 π-charge: V1073.33, C1103.36, D1253.32 Hydrophobic: I178ECL2, V1855.39, A1223.29, V1263.33, V1773.33, C1803.36, A932.61, I1133.29, M2926.55 C1293.36, V197ECL2 I248ECL2, Y2545.38, I189ECL2 A2555.39, L3686.55 9-aminoacridine Pose, Score: 46e, 40.23 1e, 52.15 ECL2 3.26 (Allosteric) H-bond: D180 , D110 Charge: D1103.26 π-π: F862.64, F3087.35 π-charge: Hydrophobic: I175ECL2 C1093.25, R176ECL2, P178ECL2, C187ECL2

Tacrine Pose, Score: 2b, 35.19 1a, 33.82 1a, 36.59 29b, 37.97 ECL2 (Orthosteric) H-bond: C187 Charge: D1253.32 D1163.32 π-π: F2886.51 Y2545.38, F3646.51 F1123.28 π-charge: Hydrophobic: V1073.33, C1103.36, A1223.29, C1293.36, C1803.36, I248ECL2, A932.61, Y962.64, I178ECL2, V1855.39, V197ECL2, W3076.48, A2555.39, W3616.48, F1123.28, I1133.29, W2856.48, M2926.55 F3106.51 F3646.51, L3686.55 I189ECL2 Tacrine Pose, Score: 73e, 34.26 1e, 43.79 3.26 ECL2 (Allosteric) H-bond: D110 , D180 Charge: D1103.26 π-π: π-charge: F862.64, F3087.35 Hydrophobic: F862.64, I175ECL2, C1093.25, R176ECL2, F3127.39 P178ECL2, R181ECL2, C187ECL2 a highest scoring pose of the largest cluster, which is pose 1 b highest scoring pose of the largest cluster, which is not pose 1 c pose 1, which is not in the largest cluster d largest cluster contains <10 members e pose/cluster of interest

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Figure 6.1 Representative poses of acridines and quinolines docked into aminergic receptor homology models Representative poses of 9-aminoacridine (brown), 4- aminoquinoline (orange), C2 bisacridine/bisquinoline (purple), C4 bisquinoline (blue), C9 bisquinoline (green), and

tacrine (red) docked into the α1A adrenoceptor (A, B), α1B adrenoceptor (C, D), α1D adrenoceptor (E, F), and serotonin 5-HT1A receptor (G, H). Left hand panels show docking poses of the monovalent 9-aminoacridine, tacrine and 4- aminoquinoline. Right hand panels show docked poses of C2, C4, and C9 bisquinolines with monovalent 4-aminoquinoline. Receptors are shown in grey ribbon representation with ECL3 and TMI labelled for orientation. Residues of note are also labelled and displayed as sticks (H: white, O: red, N: blue).

E ECL3 F ECL3

G ECL3 H ECL3

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Table 6.4 GOLDScore and unweighted GOLDScore components of docked ligands Receptor Ligand Pose Internal VDW Internal Torsion External VDW External H GOLDScore

α1A 9-aminoacridine 3 0 0 28.6529 1.2554 40.6532 C9 bisacridine 10 -122.113 -14.2647 57.1933 0 -57.7372 C9 bisacridine 1 -132.558 -19.0457 -77.4232 0.025 “0” C9 bisquinoline 1 -9.9877 -19.8131 67.5561 6.186 69.2748 prazosin 27 -7.2713 -27.0466 44.3471 5.0922 31.7515 5-methylurapidil 1 -53.3118 -16.8996 49.3785 8.3497 6.0337

α1B 9-aminoacridine 1 0 0 27.4549 2.8129 40.5634 C9 bisacridine 6 -130.811 -13.1913 60.8149 2.4617 -57.92 C9 bisacridine 1 -138.061 -20.0519 -345.105 0.4029 “0” C9 bisquinoline 4 -4.4558 -19.5228 56.5614 8.5724 62.3657 prazosin 1 -3.5987 -28.0688 41.9361 4.8503 30.8449 5-methylurapidil 2 -56.5119 -13.6281 47.6705 00.5129 -1.6023

α1D 9-aminoacridine 1 0 0 29.6624 1.7038 42.4896 C9 bisacridine 8 -121.448 -13.1026 56.9153 2.682 -53.6098 C9 bisacridine 1 -126.108 -16.6133 -1500.54 0 “0” C9 bisquinoline 1 -3.7837 -17.3847 56.798 6 62.9287 prazosin 1 -1.1802 -34.6953 45.3796 3.1612 29.6827 5-methylurapidil 1 -52.7466 -14.559 49.0262 1.811 1.9165

5-HT1A 9-aminoacridine 5 0 0 26.3056 9.6396 45.8097 C9 bisacridine 8 -125.037 -15.7464 63.7046 6 -47.1894 C9 bisacridine 1 -148.18 -20.9253 -307.403 3.0545 “0” C9 bisquinoline 4 -10.0279 -16.785 61.1947 0 57.3299 prazosin nd 5-methylurapidil 1 -53.2816 -17.7062 49.4386 8.4029 5.3932 Internal VDW: ligand intramolecular van der Waals forces Internal Torsion: torsional strain of the ligand pose External VDW: intermolecular van der Waals forces between the ligand and receptor External H: H-bond interactions between the ligand and receptor GOLDScore: Weighted sum of all four scored components “0”: reported values where poor poses are not scored

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Table 6.5 Interactions of docked quinolines

Compound Interactions 1A-AR 1B-AR 1D-AR 5-HT1A-R 4-aminoquinoline Pose, Score: 1a, 43.59 1c, 40.25 1a, 38.24 49b, 39.63 H-bond: S832.61 S1022.61 C187ECL2 Charge: E872.65 E1062.65 D1163.32 π-π: F862.64 F3347.39 F1123.28 π-charge: F3127.39 F3347.39 Hydrophobic: K3097.36 K3317.36 V1773.33, C1803.36 A932.61 4-aminoquinoline Pose, Score: 59e, 35.04 10b, 35.65 1e, 47.48 H-bond: S1925.46 S2115.46 D1103.26 Charge: F3116.52 D1103.26 π-π: F2896.52 π-charge: V1263.33, C1293.36 Hydrophobic: V1073.33, C1103.36, C1093.25, R176ECL2, A1895.43 P178ECL2, C187ECL2 C2 bisquinoline Pose, Score: 2b, 43.43 1a, 43.39 12b, 37.72 6b, 36.59 H-bond: D1063.32, C176ECL2, D123.325, C195 ECL2, S2625.46 D1163.32, C187ECL2 Charge: S1925.46 S2115.46 π-π: W1723.28, F3656.52, F1123.28 π-charge: W1023.28, F2896.52 W1213.28, F3116.52 F3847.35 Hydrophobic: I1133.29, V1173.33, A1033.29, V1073.33, A1223.29, V1263.33, V1773.33, C1803.36, C1203.36, I189ECL2, C1103.36, A1895.43 C1293.36, C195ECL2, I248ECL2, L3686.55 A2035.46 V197ECL2

C4 bisquinoline Pose, Score: 8b, 40.54 3b, 39.90 2b, 43.88 1a, 44.58 H-bond: S1925.46 S2115.46 D1163.32, S1995.42 Charge: E194ECL2 π-π: F862.64, F2896.52 W1213.28, F3116.52 F3887.38 Y962.64, F1123.28, π-charge: F862.64, F3127.39 F3626.52 Hydrophobic: V1073.33, C1103.36, L1052.64, V1263.33 M1562.64, V1773.33, Y962.64 I175ECL2 I248ECL2, A2555.39, A932.61, V1173.33, L3686.55 C1203.36, I189ECL2, A2035.46 C9 bisquinoline Pose, Score: 1a, 69.27 4b, 62.37 1c, d, 62.93 10b, 55.51 H-bond: S832.61 S2115.46 S1532.61 Charge: E872.65 E1062.65 E1572.65 π-π: F862.64 F3116.52 Y254, F3656.52 Y962.64, F3626.52 π-charge: F3127.39 F3347.39 F152, F3887.38 Hydrophobic: V1073.33, C1103.36, V1263.33, C1293.36, M1562.64, C1803.36, A932.61, V1173.33, I178ECL2, K3097.36 K3317.36 I248ECL2, A2555.39, A186ECL2, I189ECL2, L3686.55 A2035.46, A3656.55 a highest scoring pose of the largest cluster, which is pose 1 b highest scoring pose of the largest cluster, which is not pose 1 c pose 1, which is not in the largest cluster d largest cluster contains <10 members e pose/cluster of interest

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Identification of the allosteric site of the α1A adrenoceptor extracellular space (Figure 6.1). Docked C2bisquinoline produced unique interactions 3.32 with the α1A and α1B adrenoceptors. D was able to interact with a charged nitrogen, however it was with the distal, protonated ring nitrogen not the ‘orthosterically’ located nitrogen. This was not observed in any other bisquinoline, as the increasing linker length did not allow the correct location of the distal ring nitrogen. C2 bisacridine is fairly unique among the bisacridines in that it is selective for the α1B adrenoceptors. Extrapolating from this unique interaction observed for C2 bisquinoline, it may be that adoption of a unique binding pose is the cause of C2 bisacridine’s distinct subtype selectivity. C4 bisquinoline, which is not selective like C4 bisacridine, showed π-π 6.52 5.46 interactions with F and a H-bond interaction with S at the α1A and α1B 2.64 adrenoceptors, as well as a π-π interaction with F at the α1A adrenoceptor.

C9 bisquinoline, which had high, 54 nM and 100 nM, affinity for the α1A and α1B adrenoceptors, respectively, and was a potent negative allosteric modulator of α1A adrenoceptor activation by noradrenaline (Chen et al., 2013) showed an extended pose in all receptors and, most notably, was able to make simultaneous contact with orthosteric residues F6.52 and S5.46 as well as with residues S2.61 and E2.65 at the top of 2.64 TMII in all three adrenoceptors and F/L in the α1A and α1B adrenoceptors. The quinoline moiety making interactions at the top of TMII superimposed well with the allosteric poses of monovalent 4-aminoquinoline and 9-aminoacridine (Figure 6.1). It was therefore postulated that these residues at the top of TMII were contributing to the allosteric binding of these compounds 6.3.2 Mutagenesis To investigate whether the docking studies had identified an allosteric binding site 2.61 2.64 2.65 for the α1 adrenoceptors, the three residues at the top of TMII, S , F , and E , were all targeted for alanine substitution mutations. Of the three, only F2.64 has been 2.64 implicated in ligand binding to the α1 adrenoceptors. F86 on the α1A adrenoceptors has been shown to be responsible for the α1A over α1B adrenoceptor subtype selective binding of niguldipine (Hamaguchi et al., 1996) and is the only one of the TMII residues, which were implicated in the putative allosteric binding site by docking, that is not conserved across the α1 adrenoceptor subfamily. The docked C4 bisquinoline molecule provided no immediate explanation for the

α1A subtype selectivity of C4 bisacridine. The selectivity of this molecule may be

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Identification of the allosteric site of the α1A adrenoceptor attributable to a series of three residues in ECL2 that have previously been shown to be responsible for the selective binding of some adrenergic antagonists. While no direct interactions are predicted between C4 bisquinoline and this triplet, there is less than 4 Å between the side chain of Q177ECL2 and the most extracellular quinoline moiety.

Therefore a triple mutation was made in ECL2 of the α1A adrenoceptor introducing the ECL2 three corresponding residues from the α1B adrenoceptor (QIN177-179 GVT). The most drastically different substitution, glycine for glutamine, was also made on its own (Q177ECL2G). All mutations were confirmed by sequencing of the full-length sense and antisense strands of the receptor at Garvan Molecular Genetics, Sydney, Australia. 6.3.3 Ligand affinities at mutant receptors

Initial characterisation of the mutated α1A adrenoceptors showed a decreased 3 2.64 affinity for [ H]prazosin at the F86 A (KD: 2282 pM, P < 0.05) and QIN177- ECL2 179 GVT (KD: 2393 pM, P < 0.01) mutants compared to wild-type (380 pM)(Table 6.6). No other mutations had any significant effect on the affinity of [3H]prazosin. The 2.65 -1 E87 A mutant had significantly reduced expression (Bmax: 0.6 pmol.mg , P < 0.05) -1 compared to WT (Bmax: 6.5 pmol.mg ). No other receptor mutant expressed at levels significantly different to WT (Table 6.6). The affinity of phentolamine, the selective acridines, tacrine, 9-aminoacridine, C2 and C4, as well as the non-selective C9 bisacridine were all tested to observe whether their affinity and selectivity was governed by the QIN triplet in ECL2 or interaction with residues at the top of TMII. Phentolamine displayed slight but significant α1A subtype selectivity (P < 0.05) which could be converted to α1B affinity by substitution of the three amino acids at positions 177-179ECL2 in the human receptors (Figure 6.2), recapitulating previous observations using the radioligand [125I]HEAT at the rodent receptors (Hwa et al., 1995; Zhao et al., 1996). No other mutation significantly altered the affinity of phentolamine (P > 0.05)(Figure 6.2). The triple mutation in ECL2 was also sufficient to convert the α1A subtype selective ligands tacrine (P = 0.15), 9- aminoacridine, and C4 bisacridine to an α1B subtype affinity (Figure 6.2) suggesting the

α1A subtype selectivity of these compounds is primarily governed by the three residues in ECL2 and that they bind in a similar mode to phentolamine. This mutation did not 2.64 affect the affinity of the α1B subtype selective C2 bisacridine. The F86 A mutation also significantly reduced the affinity of C4 bisacridine to levels similar to its affinity for the α1B adrenoceptor (P < 0.01 compared to α1A, P > 0.95 compared to α1B). The

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3 Table 6.6 [ H]prazosin binding at α1A adrenoceptors a KD Bmax Koff log(Koff) Kon n log(Kon) Predicted Kon (pM) (pmol.mg-1) n (min-1) n (x108 M-1.min-1) (x108 M-1.min-1)

α1A WT 380 ± 24 6.5 ± 1.2 5 0.06 ± 0.01 3 -1.2 ± 0.1 1.0 ± 0.1 4 8.0 ± 0.1 1.0 ± 0.1 S832.61A 248 ± 28 6.7 ± 0.6 3 0.01 ± 0.01 3 -2.3 ± 0.1*** 0.4 ± 0.1 3 7.6 ± 0.1# 0.4 ± 0.1# F862.64A 2282 ± 980** 8.6 ± 0.1 3 0.16 ± 0.02 3 -0.8 ± 0.1*** 0.7 ± 0.1 3 7.8 ± 0.1 0.7 ± 0.1 E872.65A 595 ± 154 0.6 ± 0.1* 4 0.07 ± 0.01 3 -1.2 ± 0.1 0.8 ± 0.2 3 7.9 ± 0.1 0.8 ± 0.2 Q177ECL2G 490 ± 210 7.9 ± 2.4 3 0.08 ± 0.01 3 -1.1 ± 0.1 nd 1.7 ± 0.7 QIN177-179ECL2GVT 2393 ± 448** 3.0 ± 0.8 4 1.48 ± 0.2 3 0.2 ± 0.1*** nd 6.2 ± 1.4

α1B WT 229 ± 70 5.7 ± 1.3 3 nd nd nd nd 3 KD: Affinity. Equivalent to the concentration of [ H]prazosin required to occupy 50% of binding sites. Bmax: Maximum number of available binding sites. Koff: Dissociation rate constant, determined in HEM buffer. Predicted Kon: Association rate constant, calculated according to KD = Koff/Kon using the mean of all available repeats. Errors are calculated according to section 2.11. Binding kinetics curves can be seen in Figure 6.3 and Figure 6.4. All values are given as the mean ± SEM for ‘n’ repeats. nd, not determined *, **, *** P < 0.05, 0.01, 0.001 compared to WT by one-way ANOVA with Tukey post-test. #: P < 0.05 compared to WT by one-way ANOVA with Tukey post-test. a: Data generated jointly with Ms. Karmen Xu

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S832.61A, E872.65A, and Q177ECL2G mutations did not significantly alter the affinity of phentolamine of any tested acridines (P > 0.05)(Figure 6.2). The bisacridines still displayed competition binding slopes greater than 1 and no mutation significantly altered the observed Hill slopes compared to those observed at the WT receptors. 6.3.4 [3H]prazosin dissociation from mutant receptors As affinity is a function of both association and dissociation rates, any change in affinity would be expected to be associated with a corresponding change in dissociation and/or association rate. Furthermore, a “silent” allosteric modulator may cause no change in affinity while changing association and dissociation rates to an equal degree. Therefore, to investigate whether any of the mutated residues are involved in the binding vestibule/allosteric pocket the binding kinetics of [3H]prazosin were characterised for all mutations. Where association data was not available, predicted values were generated based on observed affinity and dissociation rate values. Association rates were also derived for observed receptors, and compared for validity. Dissociation rates of [3H]prazosin were determined for all mutations. The E872.65A and Q177ECL2G mutations had no effect on [3H]prazosin dissociation kinetics. The S832.61A mutations resulted in a dramatic 10 fold slowing of [3H]prazosin dissociation rate (P < 0.001)(Figure 6.3). F862.64A and QIN177-179ECL2GVT mutations both increased the dissociation rate of [3H]prazosin (Figure 6.3, Table 6.6). F862.64A caused a modest, but significant 2.5 fold increase in dissociation rate of prazosin (P < 0.001)(Figure 6.3) while the QIN177-179ECL2GVT mutation caused a far greater 23 fold increase in dissociation rate (P < 0.001)(Figure 6.3). The effect of receptor mutations was also observed for those mutations that were postulated to contribute to the allosteric site/binding vestibule of the α1 adrenoceptors. The E872.65A and Q177ECL2G mutations had little effect on the dissociation rate of [3H]prazosin (Figure 6.3). Combined with the lack of change in [3H]prazosin affinity, these mutations are not predicted to cause any substantial change in the association rate of [3H]prazosin, which is confirmed by the observations from association kinetics experiments (Table 6.6, Figure 6.4). The observed affinity and dissociation rate of 3 [ H]prazosin at the WT α1A adrenoceptor predicts an association rate constant of 1.7 x 108 M-1.min-1 (Table 6.6). The observed association rate constant of 1.0 ± 0.1 x 108 M- 1.min-1 is in good agreement with the predicted values indicating reliability of the measurements. There was an approximate 10-fold decrease in [3H]prazosin dissociation

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Figure 6.2 Affinities at WT and mutant α1 adrenoceptors Apparent affinity of phentolamine and acridines at WT α1A adrenoceptor, mutant α1A adrenoceptors and WT α1B adrenoceptor. 1-7 μg membrane expressing COS-1 membranes were incubated with 250 pM [3H]prazosin and increasing concentrations of competing ligand in 200 μL HEM buffer for 2 hours at room temperature. Reactions were terminated by the addition of cold PBS and filtered through GF/C Whatman glass fibre filter. Curves were fit using a variable-slope competitive binding curve and logKi calculated using the method of Cheng and Prusoff (1973). WT α1A adrenoceptor and α1B adrenoceptor values are taken from section 4.3.2. Points and bars represent the mean ± SEM of 3-6 experiments performed in duplicate. *, **, *** P<0.05, 0.01, 0.001 compared to WT by two-way ANOVA and Tukey post-test. 0.05 < P < 0.2. is given in superscript.

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3 Figure 6.3 [ H]prazosin dissociation from WT and mutant α1A adrenoceptors 1-7 μg receptor expressing COS-1 membranes were incubated with 250 pM [3H]prazosin in 400 μL HEM buffer for 2 hours at room temperature. Reassociation was inhibited by addition of 100 μL phentolamine to a final concentration of 100 μM at indicated time points. Reactions were terminated by addition of cold PBS and vacuum filtration through GF/C Whatman glass fibre. Points and bars represent the mean ± SEM of 3 individual experiments performed in duplicate. All curves were fit to a one-phase exponential dissociation curve in GraphPad Prism v.6 and are quantified in Table 6.6.

3 Figure 6.4 [ H]prazosin association at WT and mutant α1A adrenoceptors 1-14 μg receptor expressing COS-1 membranes were incubated with 250 pM [3H]prazosin in 500 μL HEM buffer for given times at room temperature. Reactions were terminated by addition of cold PBS and vacuum filtration through GF/C Whatman glass fibre. Points and bars represent the mean ± SEM of 3-4 individual experiments performed in duplicate. 2-3 repeats of each experiment were performed by Ms. Karmen Xu. All curves were fit to a one-phase exponential dissociation curve in GraphPad Prism v.6 and are quantified in Table 6.6. 128

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rate from the S832.61A mutant (P < 0.001)(Table 6.6, Figure 6.3). There was no change in affinity observed at this receptor which predicts a proportional decrease in association rate (Table 6.6). A decrease in association rate of [3H]prazosin was indeed observed for this mutation (Table 6.6, Figure 6.4). While this change is not quite to the expected magnitude, it is similar to the predicted value (Table 6.6). The F862.64A 2.5- and 23-fold increases in dissociation rate of [3H]prazosin (Figure 6.3). This mutation also caused a 6-fold decrease in affinity (Table 6.6). This increased dissociation rate is not sufficient to explain the decreased affinity at the F862.64A mutant, and predicts a corresponding ~2-fold decrease in association rate. The association rate constant of [3H]prazosin at this receptor was observed to be 0.7± 0.1 x 108 M-1.min-1 identical to the predicted value (Table 6.6).

6.3.5 Allosteric modulation of α1A adrenoceptor binding kinetics by the acridines Finally, it was assessed whether the receptor mutations could affect the change in dissociation kinetics caused by the acridines. 9-aminoacridine and C4 and C9 bisacridines were again tested against all mutant receptors for comparison with previous results, except on the QIN177-179ECL2GVT mutant where [3H]prazosin dissociation is so rapid that no further effect could be seen for any of the acridines (Figure 6.5, Figure 6.6). The F862.64A mutation resulted in a significantly reduced modulation effect of 9- aminoacridine and C9 bisacridine, while no significant effect was observed for C4 bisacridine (P = 0.34)(Table 6.6). The S832.61A mutation, which is closest to the orthosteric site, had a significantly increased modulation effect for C9 bisacridine only (P < 0.001) while C4 bisacridine and the monovalent 9-aminoacridine were unaffected (Figure 6.6). S832.61A and F862.64A were also both associated with a change in [3H]prazosin dissociation kinetics. The E872.65A and Q177ECL2G mutations, which caused no change to [3H]prazosin kinetics, caused no change in the effect of any of the tested acridines when tested at 100 µM (Figure 6.6).

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3 Figure 6.5 Modulation of [ H]prazosin dissociation from WT and mutant α1A adrenoceptors by 9-aminoacridines 1-7 μg receptor expressing COS-1 membranes were incubated with 250 pM [3H]prazosin in 400 μL HEM buffer for 2 hours at room temperature. Reassociation was inhibited by addition of 100 μL phentolamine to a final concentration of 100 μM in the absence and presence of 9-aminoacridines to a final concentration of 100 μM at indicated time points. Non-specific binding was determined using 100 μM phentolamine. Reactions were terminated by addition of cold PBS and vacuum filtration through GF/C Whatman glass fibre. Points and bars represent the mean ± SEM of 3 individual experiments performed in duplicate for all receptors except E872.65A which was 2 individual experiments. All curves were fit to a one-phase exponential dissociation curve in GraphPad Prism v.6. Non-specific binding was constrained to 0 for curves of the S832.61A mutant.

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Figure 6.6 Increase in [3H]prazosin dissociation rate in the presence of 9- aminoacridines Dissociation rates were observed in the absence or presence of 100 μM acridines. Bars and error bars represent the mean ± SEM of 3 individual experiments performed in duplicate for all receptors except E872.65A, which was 2 individual experiments. *, **, *** P< 0.05, 0.01, 0.001 compared to WT by two-way ANOVA with Tukey post-test. P values less than 0.5 shown as text.

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6.4 Discussion

The antagonist binding pocket of the α1 adrenoceptors includes the binding site of the endogenous agonists, a site buried within the TM bundle and typically confined to TM helices III, IV, and V (Hwa et al., 1995; Hwa & Perez, 1996; Porter et al., 1996) and extends to make interactions with more distant regions such as ECL2 (Zhao et al., 1996). The change in [3H]prazosin kinetics and phentolamine affinity at the QIN177- 179ECL2GVT mutant is evidence that this region is indeed important for antagonist binding. The change in affinity for phentolamine, a subtype selective antagonist, has been previously observed (Zhao et al., 1996) but the changes in [3H]prazosin kinetics are unexpected. Prazosin is a non-selective ligand yet has 6-fold lower affinity and faster dissociation kinetics at the QIN177-179ECL2GVT mutant. The mutation replaces three residues of ECL2 in the α1A adrenoceptor with the three corresponding residues from the α1B receptor. Where these mutations in ECL2 are sufficient to explain phentolamine selectivity, prazosin may have a slightly different binding mode at the α1 adrenoceptors that requires additional contacts in the α1A adrenoceptor that are important for high affinity binding. The importance of ECL2 has also been demonstrated at the M2 muscarinic receptor where mutations that decrease the flexibility of ECL2 slow the kinetics of the tested radioligand, and also show a generally decreased affinity for all tested ligands (Avlani et al., 2007). Evidently ECL2 affects ligand binding kinetics for more than just subtype selective ligands. The competitive effects of the bisacridines can be explained by the docked poses of 9-aminoacridine and tacrine in the canonical orthosteric site seen in the α1 adrenoceptor homology models. 9-aminoacridine and tacrine bind in similar, if not identical orthosteric poses at the α1A adrenoceptor with a small deviation compared to the binding pose of 4-aminoquinoline, which is located deeper within the receptor cavity. This may explain the ~100-fold difference in binding affinities between 9- aminoacridine and 4-aminoquinoline at the α1A adrenoceptor ( 4-aminoquinoline Ki: 23 µM, (Chen et al., 2013)). Presence of the third aromatic ring in the acridines perturbs the binding pose of the acridines compared to 4-aminoquinoline, consequently permitting the formation of additional or stronger interactions that are more favourable for the binding of tacrine and 9-aminoacridine, which are unfortunately beyond the abilities of algorithms such as GOLD to calculate. At the α1B adrenoceptor, 9- aminoacridine does not dock in a pose similar to the observed clusters 9-aminoacridine

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at the α1A adrenoceptor, instead finding a pose closer to the extracellular surface of the receptor (Figure 6.1). Such a dramatic change in pose of the acridines would explain the

10-fold difference in affinity of 9-aminoacridine and tacrine between the α1A and α1B adrenoceptors. A previous study noted that the molecular mass of adrenergic antagonists was generally smaller for α1B and α1D adrenoceptor selective ligands than for α1A adrenoceptor ligands (MacDougall & Griffith, 2006). This mirrors the current observation that the bulky tacrine and 9-aminoacridine molecules cannot be accommodated in the α1B or α1D adrenoceptors in the same pose as in the α1A adrenoceptor and there is greater than a 10-fold difference in their affinity for the two receptors whereas the smaller 4-aminoquinoline can be accommodated at both receptors with less than 3-fold difference in their affinity. While size exclusion may be a fairly crude method for imparting selectivity, it may explain why it is generally easier to achieve substantial selectivity for the α1A adrenoceptor than selectivity for the α1B adrenoceptor (Bremner et al., 2000; Kuo et al., 2000); larger molecules, represented by the bulkier 9-aminoacridine are easily precluded from binding at the α1B adrenoceptor. The bisacridine series was employed as a tool to discover and define potentially novel binding sites on the α1 adrenoceptors and their relative proximity to the orthosteric binding site. In addition to the competitive effects of the acridines, kinetics binding studies demonstrated non-competitive effects, which implied the existence of an allosteric site. The allosteric effects, however, occurred at concentrations higher than apparent affinity and did not correspond to the binding affinity of the bisacridines leading to the proposition that the competitive effects were being dictated by binding to the orthosteric site, and the non-competitive effects were attributable to an as-yet undescribed allosteric pocket on the α1 adrenoceptors. A second major site docking site was identified, by docking, at the top of TMII and was a prime candidate for the site responsible for allosteric interactions of the acridines. While it is interesting that 4-aminoquinoline docked preferentially in the extracellular site at the top of TMII for both the α1A and α1B adrenoceptors rather than the traditional orthosteric site, this should be interpreted with caution. It is well known limitation of GOLD that scores do not necessarily correlate well to binding affinity (Cao & Li, 2014; Li et al., 2010; Pecic et al., 2010) and it is an explicit limitation of GOLD that the algorithm is not designed to calculate entropy of binding (Jones et al., 1997). This result nonetheless suggests that there is an accommodating pocket at the

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extracellular face of the α1 adrenoceptor homology models which may be representative of the allosteric site in the α1 adrenoceptors. The docking results then drove mutagenesis of the three residues identified in TMII. One mutant, E872.65A was pharmacologically silent. Equivalent residues at this position have also been mutated at other aminergic receptors with little effect. T1002.65I was identified as being partially responsible for the species dependent differences in affinity at the 5-HT1D receptor (Pregenzer et al., 1999) 2.65 and V119 was mutated to alanine in the β1 adrenoceptor with no observed effect on the affinity of [125I]cyanopindolol or the subtype selective agonist RO363 (Sugimoto et al., 2002). While the E872.65A mutation was largely silent, two of the identified residues caused changes in ligand binding kinetics and affinity, as well as the modulation effect of the acridines identifying this region as having a role on receptor ligand interactions for the α1 adrenoceptors. 2.61 Mutation of S83 to alanine in the α1A adrenoceptor causes no change in affinity for any ligand, suggesting no gross change in the state or conformation of the receptor or orthosteric binding site. This mutation did cause a dramatic, equivalent slowing in both the association and dissociation rate of [3H]prazosin suggesting that it plays equivalent roles in the binding and de-binding pathways of [3H]prazosin, at least. 2.61 Similarly, T83 A in the M1 muscarinic receptor produced a slight 2.5-fold slowing of [3H]NMS off-rate with no corresponding change in affinity (Matsui et al., 1995) 2.61 mirroring the same result seen for the equivalent S83 A mutation seen at the α1A adrenoceptor. This suggests that a binding/debinding pathways that involves a residue at position 2.61 exists in both the α1A adrenoceptor and M1 muscarinic receptor. At the D2 dopamine receptor, V912.61A mutation also has no effect on the affinity of the bivalent ligand SB269652, but does diminish the negative cooperativity between SB269652 and the antagonist antagonist, [3H]raclopride (Lane et al., 2014). There are at least three examples, therefore, of residues at position 2.61 affecting either orthosteric binding kinetics or the magnitude of effect of an allosteric or bitopic ligand. Being the closest to the orthosteric binding site of the three identified residues, it is plausible that S832.61 is located between the two sites and and mediates [3H]prazosin binding kinetics by acting as a “hinge” or “gate” to facilitate movement between the two sites potentially as a transition residue between the allosteric and orthosteric site. Assuming that a ligand leaves via the same vestibule as it enters, lack of this critical residue would thereby decrease both association and dissociation rates.

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The only acridines that was affected by the S832.61A mutation was C9, which is the only ligand that both occupies the two sites simultaneously, and has a methylene linker; Two 9-aminoacridine monomers may occupy both sites but they lack a methylene linker, while C4’s linker is too short to allow simultaneous binding. S832.61 is the closest residue to the orthosteric site of three identified and may exist in the linker region, rather than the allosteric site. Alanine is a smaller and more hydrophobic residue and this mutation may better accommodate than methylene linker, explaining why the increased effect is only seen for C9 bisacridine; C4 bisacridine and the monovalent 9- aminoacridine are unaffected as they would not place a methylene chain in the vicinity 2.61 of S83 . The exact mechanism of this process is not clear for the α1 adrenoceptors, however SB269652, a heterobivalent, dopamine receptor ligand, is predicted to function in a very similar manner at the dopamine D2 receptor (Lane et al., 2014). SB269652 binds bivalently at one receptor protomer and induces a conformation change in a dimer partner to interact “allosterically”. As mentioned, the allosteric effects at the D2 receptor are dependent on V912.61 indicating that this residue may be involved in the binding/debinding pathway that exists in the α1 adrenoceptors, the dopamine receptors, and, to a minor degree, the atypical site in the muscarinic receptors. Assuming that the

α1 adrenoceptors are working as a dimer, and a state-specific interface exists between the two protomers as is seen in the D2 dopamine receptor (Han et al., 2009), if C9 bisacridine is binding to one this effect could be transmitted to the dimer partner, permitting greater dissociation of [3H]prazosin. The other residue of major interest was F862.64. If C9 bisacridine is able to span the orthosteric and putative allosteric site on the α1 adrenoceptor, then it would be C9 and the monovalent 9-aminoacridine that would be most sensitive to this mutation. C4 would be too short and its interactions would be limited to the orthosteric site, and selectivity residues in ECL2. Apparent affinity would be unchanged as high affinity binding is due to interaction with the orthosteric site but what was observed was a reduced modulation effect by C9 and 9-aminoacridine at the F862.64A mutation. Aromatic residues play a critical role for binding of endogenous ligands in the orthosteric site, and F862.64 could be an equivalent contact in the binding vestibule. Thus interaction with this residue may be a critical determinant of high affinity binding for allosteric ligands of the α1A adrenoceptor. A loss in affinity was only seen for prazosin and C4 bisacridine, while a loss in the ability to modulate was observed for 9-

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Identification of the allosteric site of the α1A adrenoceptor aminoacridine and C9 bisacridine so it seems that interaction with this residue is only critical for a subset of ligands. F862.64 is the only residue of the three identified residues in TMII that is not conserved across all receptor. Incidentally, F862.64 has been demonstrated to be responsible for the α1A subtype selectivity of niguldipine (Hamaguchi et al., 1996). Niguldipine was not included in the test set, but given that 2.64 F86 A determines selectivity for this ligand, is not conserved in the other α1 adrenoceptor subtypes, and can influence binding kinetics, it could be hypothesised that niguldipine’s selectivity arises due to modulation of its own kinetics and warrants further investigation.

The putative allosteric site identified on the α1 adrenoceptors does not correspond to the extensively described allosteric site identified on the muscarinic receptors at the top of TMVII (Dror et al., 2013; Gregory et al., 2010; Kruse et al., 2013), considered the primary allosteric site of the muscarinic receptors. This is not unexpected as tacrine displayed opposite effects at the adrenoceptors and muscarinic receptors (Pearce & Potter, 1988; Potter et al., 1989; Tränkle et al., 2005). Muscarinic receptors are often considered archetypal members of the small-molecule, rhodopsin-like GPCRs. Based on modelling of allosteric ligand binding, it was proposed that the allosteric pocket of the

M2 muscarinic receptor is larger than that identified in the crystal structure (Tränkle et al., 2005). This pocket can accommodate one molecule of larger modulators such as LY2119620, Duo3 and W84, however smaller allosteric ligands, such as tacrine, can bind twice within this pocket as it fairly diffuse and extends towards the top of TMII. The first tacrine binding site corresponds to the primary allosteric site at the top of TMVII, while the second, “atypical” site occupies an area of the diffuse pocket that corresponds to the top of TMII (Tränkle et al., 2005). This therefore accounts for the cooperative binding seen for tacrine at muscarinic receptors (Kiefer-Day et al., 1991; Tränkle et al., 2005). The different effects of tacrine on radioligand dissociation seen at the α1 adrenoceptors and muscarinic receptors and the lack of cooperative binding observed suggests that the putative allosteric site on the α1 adrenoceptors may more closely align with the atypical site on the muscarinic receptors, rather than the primary site. Instead, the pocket identified for the α1 adrenoceptors exists near the extracellular end of TMII and corresponds more to the allosteric residues identified in the dopamine

D2 receptor (Lane et al., 2014). If the allosteric site does indeed correspond to a binding vestibule of the receptors, then a different allosteric site could be indicative of a

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Identification of the allosteric site of the α1A adrenoceptor different binding/debinding pathway that has evolved within each subgroup of receptors. Both phylogenetic and ligand based classifications place the dopamine receptors and adrenoceptors located proximally with the muscarinic acetylcholine receptors located more distantly (Figure 1.2). It has been proposed that tacrine binds to an “atypical” site on the muscarinic receptors that is distinct from typical allosteric modulators (Tränkle et al., 2003). The existence of two allosteric sites within the muscarinic receptors could indicate that they are point of divergence within this receptor family. Molecular dynamics simulations of the β2 adrenoceptor (Dror et al., 2011) indicate that the β2 adrenoceptor appears more similar to the muscarinic receptors than the α1 adrenoceptors. In both classification systems, the β adrenoceptors are located distantly from the α1 adrenoceptors with the muscarinic receptors in between. It therefore appears that there may be at least two major binding pathways that have evolved within the rhodopsin-like, small-molecule GPCRs. Fully characterising this may then generate a starting location for do novo design of novel allosteric ligands of rhodopsin-like GPCRs.

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A general consensus within the drug design field is that the conserved orthosteric binding site of receptor families like the α1 adrenoceptors intrinsically limits the potential selectivity that can be achieved by any drug binding to this site. Future drugs may overcome this limitation by making interactions with novel sites, or activating receptors in a more selectively biased manner in order to generate better efficacy, selectivity, or side effect profiles (Christopoulos, 2002; Conn et al., 2014; Pin et al.,

2003). The α1 adrenoceptors, like many GPCRs are potential drug targets for the treatment of a number of conditions (Lepor et al., 2012; Perez & Doze, 2011) and allosteric modulators, or even bivalent ligands, are promising options to successfully target those receptors (Conn et al., 2014). Despite this potential, little information exists for allosteric ligands of the α1 adrenoceptors or the location of allosteric sites on the α1 adrenoceptors. The purpose of this thesis was to explore hitherto unrecognised binding sites of the α1 and examine their therapeutic potential. Structure based drug discovery has a demonstrated track record of discovering high-affinity ligands for proteins, including GPCRs once their structures have become available (Carlsson et al., 2011; Kolb et al., 2009) however there is no such structural information available for the vast majority of GPCRs. The first high resolution structure of a GPCR was released in 2000 and arose largely out of serendipity; rhodopsin was expressed abundantly in, and easily purified from rod cells, and it is a stable structure in its ground state. There are now over 120 high resolution crystal structures currently available in the PDB, but despite this, rhodopsin is still the only crystal structure of a GPCR without stabilising mutations or other engineering (Deupi, 2014). Where available though, these structures provide a valuable foundation for structure based drug discovery. Where structures are unavailable, homology models are a good substitution. Homology modelling is by far the most prominent means of generating structural data for GPCRs in the absence of crystal structures (Kufareva et al., 2011) probably owing to the good returns and economy of building homology models. With adequate expertise, 139

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Identification of the allosteric site of the α1A adrenoceptor homology models can be built using desktop computing power, to successfully identify hits from large chemical libraries and enrich test sets with high hit rates (Carlsson et al., 2011; Kneissl et al., 2009). As the number of structures released into the public domain grows, so too does the ability to pick more appropriate templates for homology modelling of different target receptors. The release of models has also been used to assess and refine modelling techniques within the modelling community; community- wide “competitions” are run before a model is released to assess and refine modelling techniques (Katritch et al., 2010; Kufareva et al., 2011). The model used in Chapter 3 was built using rhodopsin, the only available template at the time (MacDougall & Griffith, 2006) but updated models were generated for use in Chapter 6 on the basis that the extracellular loops and orthosteric biding site of the D3 dopamine receptor crystal structure were more appropriate for an α1 adrenoceptor model than rhodopsin. Others have also shown that critical evaluation of template choice, beyond sequence similarity alone, is necessary for the generation of high quality homology models (Kneissl et al., 2009). Comparing the crystal structure from Chapter 3 based the bovine rhodopsin template (MacDougall & Griffith, 2006) to the recent homology models generated for Chapter 6, it can be seen that ECL2 extends further into the extracellular space in the recent model

(Figure 7.1) most likely reflecting the template structure observed in the D3 dopamine receptor crystal structure (Chien et al., 2010). ECL2 is postulated to be quite flexible in small molecule, rhodopsin-like GPCRs (Avlani et al., 2007) so this is an acceptable difference, but also places the aspartate examined in Chapter 3 in a more solvent exposed location, which is ideal if it is to indeed act as a point of first contact for agonists. The novelty of this interaction is that the extracellular loops had not previously been implicated in agonist binding or receptor activation at the α1 adrenoceptors. Implicating ECL2 in agonist binding thereby proposes a novel site where a drug could compete with adrenaline or noradrenaline, or bind to mimic an agonist. It also defines a site that could be considered to maximise selectivity when designing a new drug. D191ECL2 acting as a temporary contact for binding ligands, is recapitulated by the theme that arises in later chapters that the binding vestibule is, by necessity, a low- affinity binding site for orthosteric ligands. Rapid dissociation rates, a feature of low affinity binding, for ligands contacting D191ECL2 would create high micro- concentrations of agonist around the opening to the binding cleft to facilitate

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Figure 7.1 Proposed binding mechanism for the α1 adrenoceptors ECL2 Homology model of the α1A adrenoceptor. Highlighted residues are E171 ECL2 2.61 2.64 2.65 (equivalent to D191 of the α1B adrenoceptor) in green, S83 , F86 , and E87 in yellow, canonical orthosteric binding residues in orange, and QIN177-179ECL2 in blue. Arrows represent a potential stepwise pathway for ligands to follow from the extracellular space to the orthosteric binding site.

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Identification of the allosteric site of the α1A adrenoceptor progression to the orthosteric site. In contrast, high affinity binding would be characterised by longer residence time of ligands in the vestibule and would consequently inhibit progression to the orthosteric binding site. D191ECL2 is therefore ideally located to act in a catch-and-release manner, and this interaction is mostly likely to be a relatively low-affinity one. The value of in silico techniques and homology modelling can be seen by the fact that almost all of the mutations generated in this thesis were a direct result of observations made using homology models or docked ligands. One of the more serendipitous results of this thesis was the identification of the binding pocket at the extracellular end of TMII. Docking algorithms such as GOLD are designed primarily to identify a ligand’s pose inside a known binding pocket (Jones et al., 1995), not to discover binding sites. This partly arises from an understanding of the binding process to be one of conformational selection, rather than induction i.e. binding pockets may not exist stably in the absence of a ligand, and partly because computational time is minimised by designating a restricted region within which the ligand is docked; leaving this open-ended would create a more complex and computationally lengthy problem. GOLD was exploited, however, by assuming that if one 9-aminoacridine moiety was indeed binding orthosterically, then the allosteric binding site must be restricted to a location dictated by the linker length of the bisacridines. GOLD was even able to independently identify the allosteric binding site for the monovalent ligands that was also comfortably spanned by the bivalent ligand with a 9-carbon linker, which corresponded to the peak in binding cooperativity seen in competition binding assays. Bitopic binding to the orthosteric and allosteric site is the most feasible solution to explain all of the docking and empirical observations made and it is therefore a conclusion of this thesis that residues at the extracellular end of TMII are forming an allosteric pocket of the α1 adrenoceptors. Assuming that the allosteric pocket does indeed represent that binding vestibule of GPCRs, then these residues may also represent the binding/debinding pathway of the α1 adrenoceptors as shown by the change in orthosteric ligand kinetics in Chapter 6, and possibly other, closely related aminergic GPCRs such as the dopamine receptors (Figure 1.2). The complex relationship between GPCRs, their orthosteric and allosteric ligands, and signalling pathways results in a multitude of potential signalling outcomes. The negative cooperativity for the 9-aminoacridines was preserved between dissociation

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Chapter 7 General discussion and future directions kinetics assays with [3H]prazosin and IP accumulation assays with noradrenaline, which may be explained by molecular dynamics simulations at the M2 muscarinic receptor that suggest that charge-repulsion is often sufficient to explain negative cooperativity between cationic allosteric and orthosteric ligands bound to a single receptor. IP accumulation was the only signalling outcome to be assessed here, and is likely an appropriate pathway to be target for smooth muscle relaxation, in benign prostatic hyperplasia for example, but anti-epileptiform effects in the CNS are more likely to be mediated through Gi (Hillman et al., 2009) while cardiac protection or hypertrophy are likely to be mediated through an as yet undefined nuclear signalling pathway (Ardati & Nemer, 1993; Papay et al., 2013). These would all need to be assessed before chasing a ligand for a specific outcome. The results obtained with tacrine suggest that some modification of 9- aminoacridine is possible, and allosteric modulators of receptors such as the metabotropic glutamate receptors (O'Brien et al., 2003) and muscarinic receptors (Gharagozloo et al., 1999) have respond well to structure-activity modifications, so further development is definitely plausible. Linker composition and attachment points have also been shown to be a factor that can be modified to improve bivalent ligand properties (Gogoi et al., 2012; McRobb et al., 2012). An underappreciated confounding factor appears to be the effect of dimerisation on the pharmacology of these receptors. Dimerisation, like allosterism, is a complex and sometimes unpredictable effect. It was proposed that the bisacridines were exerting their effect across a dimer pair. Fully exploring whether this is indeed the case, and whether physiologically relevant dimers are present in target tissues may steer the development of α1 adrenoceptor allosteric ligands towards a more therapeutically relevant mechanism at early, rather than later stages of development. There are ligands of the α1 adrenoceptors and dopamine receptors which do not bind oligomeric receptors (Vicentic et al., 2002; Zawarynski et al., 1998) so physiological monomeric/oligomeric distribution should be fairly straight forward to deduce, at least in animal models. Recapitulating monomeric or dimeric systems is becoming increasingly more common (Denisov et al., 2004).

In this study, I have identified two regions of the α1 adrenoceptors to be important for normal function of α1 adrenoceptors. Mutation of ECL2 affected agonist binding, antagonist selectivity, and [3H]prazosin dissociation kinetics. Mutation of TMII also

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Chapter 6

Identification of the allosteric site of the α1A adrenoceptor changed [3H]prazosin kinetics as well as the allosteric effect of some bisacridines. Both of these regions are near the extracellular surface of the receptors making them accessible to ligands, and potential drug binding sites. Alternatively, characterising which signalling pathways each of these residues affects could help to describe the specific structural features are associated with different signalling states of the receptor. In silico techniques were invaluable in the identification of all of the residues discussed in this thesis. Following this, in silico techniques may again find use in the identification and modification of novel molecules. Tools such as LUDI can identify novel interactions within a binding pocket (Honma, 2003), and this information turned into a pharmacophore to screen vast chemical libraries for potential binders. Docking will again find use in maximising contacts made by drug-like molecules. Importantly, having identified the location of a potential binding pocket will steer this identification of novel ligands towards a more efficient, rational and informed “design” rather than “discovery” strategy. In conclusion, I have presented here a previously undescribed role for ECL2 of the α1B adrenoceptor, and provided the most comprehensive description, to date, of allosteric interactions at the α1 adrenoceptors. Elucidating these mechanisms will hopefully be of critical importance for the development of an effective, allosteric α1 adrenoceptor therapy.

144

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European Journal of Pharmacology 733 (2014) 90–96

Contents lists available at ScienceDirect

European Journal of Pharmacology

journal homepage: www.elsevier.com/locate/ejphar

Molecular and cellular pharmacology

An aspartate in the second extracellular loop of the α1B adrenoceptor regulates agonist binding

Adrian P. Campbell a, Iain J.A. MacDougall b, Renate Grifﬁth a, Angela M. Finch a,n a Department of Pharmacology, School of Medical Sciences, University of New South Wales, Kensington, NSW 2052, Australia b School of Environmental and Life Sciences, The University of Newcastle, Callaghan, NSW 2308, Australia article info abstract

Article history: The extracellular loops of the adrenoceptors present a potential therapeutic target in the design of highly Received 18 December 2013 selective adrenergic drugs. These regions are less conserved than the orthosteric binding site but have to Received in revised form date not been implicated in activation of adrenoceptors. A previously generated homology model identified 20 March 2014 an extracellular residue, D191, as a potential regulator of agonist binding. We have generated mutants of the Accepted 24 March 2014 adrenoceptor replacing the charged aspartate, D191, as well as a potential interaction partner, K331, with Available online 29 March 2014 α1B uncharged alanines to observe effects on ligand binding and receptor activation. Significant 4–6fold Keywords: reductions in affinity for the endogenous agonists, epinephrine and norepinephrine were observed for GPCR receptors with the D191A mutation in the second extracellular loop. While changes in EC50 were observed, Adrenergic receptor α1B operational analysis yielded no apparent change in receptor activation. Based on these findings, we suggest Receptor activation that D191, in the second extracellular loop of the adrenoceptor, acts as a ‘point of first contact’ for the Second extracellular loop α1B receptor's endogenous agonists. Implication of the non-conserved extracellular regions of the receptor in agonist binding makes it a potential target for the design of highly selective drugs. & 2014 Elsevier B.V. All rights reserved.

1. Introduction et al., 2008; Waugh et al., 2001; Zhao et al., 1996). The less-conserved nature of the extracellular loops creates an ideal target for ligand The α1 adrenoceptors are a family of three receptors that are selectivity. Indeed it has been demonstrated that a triplet of residues responsible for alterations of cellular function via the Gq/11 path- at the beginning of extracellular loop 2 in the α1A and α1B way in response to the presence of extracellular epinephrine or adrenoceptors is responsible for the selective binding of a series of norepinephrine. Activation typically promotes functions asso- adrenergic antagonists (Zhao et al., 1996). There is currently no ciated with the ‘fight or flight’ response such as smooth muscle demonstrated role of the extracellular domains in agonist binding for contraction and vasoconstriction. the adrenoceptor family. Epinephrine and norepinephrine, the two endogenous agonists of With no solved crystal structures available for the α1 adreno- the α1 adrenoceptors, bind within the transmembrane bundle to a ceptor family, structural information is often extrapolated from well-defined site 11 Å below the extracellular surface, which is homology models. We previously generated a homology model of conserved amongst the nine adrenoceptor subtypes. Major contri- the α1B adrenoceptor from a rhodopsin template (MacDougall and butors to binding are D3.32, 1(Porter et al., 1996), S5.42(Cavalli et al., Griffith, 2006). Newer crystal structures of the more phylogeneti- fi 1996; Hwa and Perez, 1996), and various, receptor speci cphenyla- cally similar β1 and β2 adrenoceptor are available (Cherezov et al., 6.51 lanines; namely F in the α1B adrenoceptor (Chen et al., 1999), as 2007; Rasmussen et al., 2011; Rosenbaum et al., 2011; Warne et al., 4.62 5.41 well as F and F in the α1A adrenoceptor (Waugh et al., 2000). 2008), however, the rhodopsin structure is still a valid template for Antagonists for the adrenoceptors are typically larger than the extracellular regions, given the longer second extracellular agonists and have interaction sites that extend outside the agonist loop of the β adrenoceptors which contain a unique disulphide site, towards the extracellular domain (Ahmed et al., 2008; Nagaoka bond that stabilises an additional α-helix within the loop. The model predicted an interaction between K3317.36 in the seventh transmembrane helix and D191 in the second extracellular n Corresponding Author. Tel.: 61 2 9385 1325. þ loop (Fig. 1). This lysine has a well-characterised role in an inter- E-mail address: angela.fi[email protected] (A.M. Finch). helical salt-bridge, where a charge interaction with D1253.32 is 1 Residue designations specify the amino acid followed by the absolute position of the residue within the receptor. Superscript numbers designate postulated to constrain the receptor in an inactive state. Upon agonist Ballesteros–Weinstein numbering convention (Ballesteros and Weinstein, 1995). binding, the charge interaction is disrupted by competition from the http://dx.doi.org/10.1016/j.ejphar.2014.03.034 0014-2999/& 2014 Elsevier B.V. All rights reserved. A.P. Campbell et al. / European Journal of Pharmacology 733 (2014) 90–96 91

Fig. 1. Homology model of the α1B adrenoceptor. Model was based on rhodopsin (1U19) template (Palczewski et al., 2000). Shown, right, with transmembrane helices I and IV labelled for orientation. Enlarged, left, with helices I, II, and III removed for clarity, and helices VI and VII labelled for orientation. The proposed salt-bridge between the D191 and K331 sidechains can be observed clearly (MacDougall and Griffith, 2006). positively ionised nitrogen of adrenergic agonists (Porter et al., 1996) 2.2. Mutagenesis which allows the receptor to assume an active conformation. Based on this homology model, we hypothesised that, follow- Mutations were generated by site directed mutagenesis of 7.36 ing binding, K331 is free to interact with D191, forming an hamster α1B adrenoceptor in pMT30 vector using Phusion poly- active state lock between the second extracellular loop and merase mediated PCR, followed by DpnI digestion of methylated transmembrane helix VII. wild-type constructs. PCR-digestion products were transformed To test our hypothesis we constructed individual alanine muta- into competent DH5-α Escherichia coli as per the protocol of Inoue tions of the α1B adrenoceptor at positions D191 and K331 as well as et al. (1990). Clones were retrieved by miniprep and sequenced at a double alanine mutation at both positions to test the importance the Ramaciotti Centre for Gene Function Analysis (University of of each residue on agonist binding and receptor activation. New South Wales, Sydney, Australia). Confirmed mutations were amplified in DH5-α E. coli, retrieved by maxiprep and stored in milliQ water at 20 1C. À 2. Materials and methods 2.3. Transfection for radioligand binding [3H]prazosin, [3H]myo-inositol, and Ultima Gold and Ultima Cells were plated at a density of 2.5–2.8 104 cells per cm2 in fully Flo scintillation cocktails were purchased from Perkin Elmer Â (Waltham, MA, USA). Dulbecco's Modified Eagle Medium (DMEM) supplemented DMEM 24 h before transfection. Cells were transfected 1 without inositol was purchased from MP Biomedicals (Santa Ana, using a transfection cocktail of 0.5 mg mlÀ DEAE dextran and 125 nM 2 CA, USA). Foetal bovine serum (FBS) was purchased from Invitro- chloroquine in serum-free DMEM and 85 ng construct per cm .Cells gen (Carlsbad, CA, USA). Epinephrine hydrochloride, norepinephr- were incubated in the transfection cocktail for 3 h at 37 1Cand5%CO2. ine hydrochloride, phentolamine hydrochloride, 5-methylurapidil, Following incubation, transfection cocktail was aspirated, cells were lithium chloride, propranolol hydrochloride, diethylaminoethyl- washed in 10% DMSO in phosphate buffered saline (PBS) for 2–3min, dextran (DEAE dextran), ammonium formate, chloroquine dipho- then returned to 37 1Cand5%CO2 in fully supplemented DMEM. 24 h sphate, 2-amino-2-hydroxymethyl-propane-1,3-diol (Tris) and following transfection, cells were lifted using trypsin and replated in 1 2-[4-(2-hydroxyethyl)piperazin-1-yl]ethanesulfonic acid (HEPES) DMEM supplemented with 10% FBS, 100 mgmlÀ glutamine, and 1 were purchased from Sigma Aldrich (St. Louis, MO, USA). Ethylene 100 mgmlÀ penicillin–streptomycin. glycol-bis(2-aminoethylether)-N,N,N0,N0-tetraacetic acid (EGTA), 2.4. Membrane preparation MgCl2, NaCl, KCl, Na2HPO4, KH2PO4 and glycerol were purchased from Ajax Finechem (Taren Point, NSW, Australia). Phusion High- fidelity DNA Polymerase was from Finnzymes (Keilaranta, Espoo, Cells were harvested 72 h after transfection by scraping into Finland). DpnI was purchased from NEB (Ipswich, MA, USA). Mini- cold PBS. Harvested cells were pelleted by centrifugation at 1000 g for 5 min at 4 1C. The pellet was resuspended in 0.25 M and Maxi-prep kits were from Qiagen (Venlo, Netherlands). jetPEI Â was purchased from PolyPlus-transfection SA (Illkirch, France). AG sucrose with protease inhibitors and homogenised in a Dounce fi 1-X8 formate resin was from Bio-Rad (Hercules, CA, USA). homogeniser with a tight tting pestle. Homogenates were centrifuged at 1260 g for 5 min at 4 1C. The supernatant was added Â to 25 ml membrane precipitation buffer (50 mM tris, 12.5 mM 2.1. Cell culture MgCl , 5 mM EGTA) and centrifuged at 37 000 g for 15 min at 2 Â 4 1C. Supernatant was discarded and the pellet was resuspended in COS-1 cells were maintained in DMEM supplemented with 10% 25 ml membrane precipitation buffer and centrifuged again. 1 1 (v/v) heat treated FBS, 100 mgmlÀ glutamine, and 100 mgmlÀ Supernatant was discarded and the pellet was resuspended in penicillin–streptomycin. Cultures were kept at 37 1Cand5%CO2 membrane precipitation buffer 10% glycerol. The suspension was þ and passaged as they approached confluence by standard tissue passed through an insulin syringe 10–15 times then stored at culture techniques. 80 1C in 50 ml aliquots. Protein concentration was determined À 92 A.P. Campbell et al. / European Journal of Pharmacology 733 (2014) 90–96 using the Bradford protein assay (Sigma Aldrich, St. Louis, method of Cheng and Prusoff (1973) where K IC /1 (L/K ), i¼ 50 þ D MO, USA). whereby IC50 is the concentration of competing ligand required to inhibit radioligand binding by 50%, L is the concentration of the

2.5. Radioligand binding competing ligand, and KD is the concentration of radioligand required to occupy 50% of available binding sites, as calculated

All binding assays were performed in triplicate, at room by saturation binding. KE values were determined using the temperature, in 200 ml HEM buffer (20 mM HEPES, 1.4 mM EGTA, operational model of pharmacological agonism of Black and Leff 12.5 mM MgCl2, pH 7.4) and allowed to equilibrate for 1 h. (1983),wherebyE (Rt A Emax)/(KA KE A(Rt KE)), where E is 3 ¼ Â Â Â þ þ Saturation binding was performed with 50–4000 pM [ H]prazosin. the observed effect, Rt is the total concentration of receptors, Emax is Competition binding was performed in the presence of 250 pM the maximum inducible effect of receptor activation, KA is the [3H]prazosin. Nonspecific binding was determined using 100 mM binding affinity of the agonist as determined by competition binding, phentolamine. Each reaction tube contained 1–5 mg protein. Reac- and KE is the concentration of receptors necessary to elicit 50% of tions were terminated with 4 1C PBS and vacuum filtered through maximum response. Energy of binding (ΔG)wascalculatedas 1 1 GF/C glass fiber filters (Whatman, Maidstone, UK). Bound radi- G RT log(1/K )whereR is the gas constant in J KÀ molÀ , T is Δ ¼À i oligand was extracted from dried filters in Ultima Gold liquid temperature in Kelvin, and Ki is the binding affinity as determined by scintillation cocktail and quantified in a liquid scintillation counter. competition binding. Mutant cycle analysis of binding was performed with mean ΔG values. Mutant cycle analysis of function was 2.6. Transfection for IP accumulation assay performed as per (Gleitsman et al., 2009)wherebyΩ (EC (WT) ¼ 50 Â EC (mutations 1 2))/(EC (mutation 1) EC (mutation 2)). Ω was 50 þ 50 Â 50 Resuspended COS-1 cells were diluted to a concentration of calculated using mean EC50 values from all available experiments. All 5 1 1 10 cells mlÀ DMEM. Cells were transfected with 1 mg con- data are presented as mean7S.E.M., and were compared by one-way Â struct and 2 ml jetPEI transfection reagent per 1 105 cells as per ANOVA with Newman–Keuls post-test. Â the manufacturer's instructions. Cells were plated into 96 well plates (200 ml per well) for IP accumulation assays and 6 well plates (6 ml per well) for whole cell binding analysis. Plates were 3. Results left at room temperature for 1 h following transfection and then transferred to a 37 1C, 5% CO2 incubator. 3.1. Characterisation of receptors by radioligand binding

3 fi 2.7. IP accumulation assay [ H]prazosin af nity for the wild-type (WT) α1B adrenoceptor (220780 pM) is similar to previously published results, as is affinity Media was aspirated and replaced with DMEM without for the K331A mutation (198766 pM) (Porter et al., 1996). There was 1 3 inositol supplemented with 10% FBS, 100 mg mlÀ glutamine, and no significant difference between [ H]prazosin affinity for the WT 1 3 100 mg mlÀ penicillin–streptomycin plus [ H]myo-inositol to a and K331A receptors (Table 1). The K331A mutant expresses at only 1 final concentration of 85 nM (10 mCi mlÀ )16–24 h post- 40% of WT (Po0.01), again similar to previous experiments (Table 1) transfection. Labelled cells were returned to 37 1C and 5% CO2. (Porter et al., 1996). The D191A mutant is expressed at similar levels Media was aspirated 24 h post labeling and replaced with inositol to WT, and there is no significant difference in affinity for [3H] free DMEM and the cells returned to 37 1C for 2 h. Media was then prazosin (374.1776.5 pM). The double D191A.K331A mutant has a supplemented to a final concentration of 10 mM LiCl and 10 mM [3H]prazosin affinity similar to WT, but expresses at 29% of WT levels, propranolol and incubated for 20 min at 37 1C. Reactions were similar to the K331A mutant (Table 1). started with the addition of epinephrine or norepinephrine to a final volume of 150 l and incubated for 30 min at 37 C. Reactions m 1 3.2. Characterisation of competition ligand binding were stopped by the addition of 50 ml 400 mM formic acid. Cells were lysed by freeze-thawing at 80 1C and 45 1C. Soluble inositol À Phentolamine and 5-methylurapidil, described as competitive phosphates were collected by 30 min incubation and vacuum inverse agonists of the α1B adrenoceptor (Rossier et al., 1999), show filtration through activation AG 1-X8 formate resin in a 96 well 32 nM and 80 nM affinities for the WT receptor, respectively, in MultiScreen filter plate (Millipore) then eluted with 1 M ammo- agreement with other studies (Porter et al., 1996; Zhao et al., 1996). nium formate in 100 mM formic acid. 200 l eluate was diluted m None of the mutants show significantly different affinities for either with 1 ml reverse osmosis (RO) water and emulsified in 3 ml of the competing antagonists (Fig. 2, Table 2). Ultima Flo liquid scintillation cocktail and quantified by counting The endogenous agonist ( )-epinephrine has 1.3 mM affinity at for 5 min in a liquid scintillation counter. À the WT receptor, consistent with previously reported values (Porter et al., 1996). In contrast to a previous study, we observe 2.8. Whole cell binding

Table 1 Cells in 6-well plates were lifted with trypsin and diluted to Saturation binding. 5 1 4 10 cells mlÀ . Binding was performed in a total volume of Â 4 3 1 200 ml HEM buffer with 4 10 cells for 1 h with 4 nM [ H] KD (pM) nBmax (pmol mgÀ ) n Â prazosin. Nonspecific binding was determined using 100 mM fi WT 219.6780.1 7 14.671.0 4 phentolamine. Bound radioligand was extracted from dried lters K331A 197.8765.6 6 5.970.2a 4 in Ultima Gold liquid scintillation cocktail and quantified in a D191A 374.1776.5 10 15.371.0 5 liquid scintillation counter. D191A.K331A 251.7755.7 9 4.370.7a 5

3 2.9. Data analysis KD, dissociation constant, equivalent to the concentration of [ H]prazosin required to occupy 50% of expressed receptors.

Bmax, maximal receptor concentration as calculated by non-linear regression of Saturation binding data were analysed by non-linear regression saturation binding. in GraphPad Prism v.5. Competition binding data were analysed by All data are expressed as the mean7S.E.M. for ‘n’ repeats, performed in triplicate. non-linear regression in GraphPad Prism v.5 and calculated by the a Po0.001 compared to WT. A.P. Campbell et al. / European Journal of Pharmacology 733 (2014) 90–96 93

Fig. 2. Competition binding curves for adrenergic ligands. Competition binding curves for phentolamine (panel A), 5-methylurapidil (panel B), epinephrine (panel C), and norepinephrine (panel D) at WT (●), K331A (▼), D191A (▲), and D191A/K331A (♦) receptors. Binding assays was performed against 250 pM [3H]prazosin with 1–5 mg protein, as determined by Bradford assay, in a ﬁnal volume of 200 ml HEM buffer. Reactions were allowed to equilibrate for 1 h at room temperature. Points and bars represent the mean7S.E.M. of 3–5 experiments performed in triplicate. Afﬁnity values and statistical analysis are given in Table 2.

Table 2 Competition binding.

WT K331A D191A D191A.K331A

pKi nKi (nM) pKi n Ki (nM) pKi nKi (nM) pKi nKi (nM)

Phentolamine 7.570.2 4 32 7.870.1 4 16 7.270.2 4 63 7.870.2 4 16 5-Methylurapidil 7.170.1 4 79 7.370.1 4 50 6.870.1 4 160 7.070.1 4 100 Epinephrine 5.970.1 5 1300 6.070.1 6 1000 5.170.1a 6 7900 5.370.1a 6 5000 Norepinephrine 5.470.1 4 4000 5.970.1a 4 1300 4.870.1a 4 16000 5.270.1 4 6300

pKi, negative log of the inhibition constant, equivalent to the concentration of ligand required to bind to 50% of unoccupied receptor. Calculated from observed IC50 values according to the Cheng–Prusoff equation (Cheng and Prusoff, 1973).

Ki, calculated inhibition constant, equivalent to the concentration of ligand required to occupy 50% of unoccupied receptors. Derived from pKi. All data are presented as mean7S.E.M. for ‘n’ repeats, performed in triplicate. a Po0.01 compared to WT. no significant difference in affinity for epinephrine at the K331A To assess any residue interactions, the change in binding mutant receptor, where an increased affinity has previously been energies was calculated and analysed by mutant cycle analysis observed (Porter et al., 1996). Both the D191A and D191A.K331A (Table 3). The sum of binding energies from individual mutants mutants display a significant decrease in affinity for epinephrine was not significantly different from the change in binding energy compared to WT and K331A receptors (Table 2). of the double mutant for either agonist. ( )-Norepinephrine displays 4.0 M affinity at the WT recep- À μ tor, consistent with previously reported values (Porter et al., 1996). We observed a small but significant increase in affinity for 3.3. Characterisation of receptor activity norepinephrine at the K331A mutant (3-fold, Po0.01). A previous study observed a more dramatic 7-fold increase in affinity for this Given the change in affinity for agonists, the ability of the mutant (Porter et al., 1996). With the D191A mutant, we observe a receptors to become activated was studied using a radiolabelled fi fi modest, but signi cant 4-fold decrease in af nity for norepinephr- precursor of the second messenger inositol triphosphate (IP3). The ine (Po0.01). In contrast to epinephrine, norepinephrine affinity K331A mutant shows a 4.1-fold increase in basal signaling over the at the double D191A.K331A receptor is similar to, and not WT receptor (Po0.01). Neither of the D191A mutants demon- significantly different from, WT (Table 2, Fig. 2). strate significantly increased basal signaling over WT receptor. 94 A.P. Campbell et al. / European Journal of Pharmacology 733 (2014) 90–96

Table 3 Change in energy of agonist binding.

K331A D191A D191A.K331A G G ΔΔ K331AþΔΔ D191A

1 1 1 ΔΔG (kj molÀ ) n ΔΔG (kj molÀ ) n ΔΔG (kj molÀ ) n

Epinephrine 0.970.4b 5 4.370.2 5 3.370.5 5 3.470.4 À Norepinephrine 2.970.3b 4 3.470.6a 4 1.270.5 4 0.570.7 À G, change in energy of binding, expressed as G G , where G RTlog(1/K ). ΔΔ Δ mutant ÀΔ WT Δ ¼À i All data are presented as mean7S.E.M. for ‘n’ repeats. All analyses were performed on each repeat, and the resulting values averaged. a Po0.05 compared to D191A.K331A double mutant. b Po0.001 compared to D191A.K331A double mutant.

and norepinephrine, respectively. At the K331A mutation, KE values were 22.4% and 38.1% for epinephrine and norepinephrine. Addition of the D191A mutation to WT or K331A mutant receptors did not

significantly change KE.TheeffectoftheK331Amutationonreceptor activation could not be reliably quantified as comparison to a receptor lacking this mutation is difficult due to differences in receptor reserve (Table 1).

4. Discussion

The D191A mutation caused a decreased affinity for both agonists. This was surprising, as no extracellular residues have previously been shown to be involved in binding of the endogenous agonists for this receptor. There is increasing evidence that the extracellular regions of aminergic receptors form binding ‘vesti- Fig. 3. Agonist independent receptor signaling. Fold-WT basal signaling of K331A bules’ where ligands briefly reside before proceeding on, to the (4.070.7), D191A (0.970.5), and D191A.K331A (2.071.0), corrected for vector orthosteric binding site (Dror et al., 2011; Kruse et al., 2012). The only signaling. All data were normalized to receptor expression levels as determined by whole cell binding with 4 nM [3H]prazosin. All data were analysed by ligands investigated in these simulation studies contain positively one-way ANOVA with Newman–Keuls post-test. nnPo0.01, n 3–8. charged amines, and both simulations identified acidic residues in ¼ the second extracellular loop (ECL2) as important for vestibule binding. It is possible that an aspartic acid in the extracellular Addition of the D191A mutation to the K331A receptor returns region of the α1B adrenoceptor could interact with positively basal signaling to WT levels (Fig. 3). charged aminergic agonists in a similar manner to the conserved The mutant receptors showed altered and differing responses acidic residue at position 3.32, which is considered critical for to the endogenous agonists ( )-epinephrine and ( )-norepi- ligand binding, to create this binding vestibule in the extracellular À À fl nephrine. Epinephrine possesses 74 nM potency at the WT α1B region of the receptor. The exible nature of ECL2 has been shown adrenoceptor (Table 4, Fig. 4). We observe small, but significant to be an important factor in regulating ligand access to the 2.1 fold (Po0.05) and 3.6 fold (Po0.01) decreases in potency at orthosteric binding pocket of the muscarinic acetylcholine recep- the K331A and D191A mutants (Table 4, Fig. 4). At the double tors (Avlani et al., 2007). D191 is located in a fairly unstructured mutant, epinephrine has an 8.5 fold decrease in potency compared and unconstrained loop, and would thus be ideally placed to to WT (Table 4, Fig. 4) which is significantly different from WT sample the surrounding environment for suitable ligands and (Po0.001), as well as the K331A (Po0.01) and D191A (Po0.05) provide an initial point of contact before the ligand advances to single mutants. Norepinephrine displays 347 nM potency at the the orthosteric binding pocket within the transmembrane helix WT receptor. The K331A mutation has no significant effect on bundle. norepinephrine potency. We observe a 3.3 fold decrease in The K331A α1B adrenoceptor mutation has been previously potency at the D191A mutant (Po0.01 compared to WT), and a described (Porter et al., 1996; Porter and Perez, 1999). Our study 3.9 fold decrease in potency at the double mutant (Po0.01 extends these observations by comparing binding and function of compared to WT and K331A) (Table 4, Fig. 4). Mutant cycle analysis both endogenous agonists. In agreement with the previous study (Ambrosio et al., 2000) was used to examine residue interaction (Porter et al., 1996), we find the K331A mutation results in a for receptor activation (Table 4). Ω values did not deviate sig- constitutively active receptor. The increased agonist independent nificantly from unity, providing no evidence for interaction signaling indicates that this receptor has a reduced capacity to between the mutated residues. maintain its inactive, ground state. This is consistent with a previous Functional data was then analysed in the presence and absence of conclusion that this residue is involved in a salt-bridge interaction the D191A mutation using the Operational Model of Agonism (Black that prevents receptor transition to a signaling conformation. and Leff, 1983)(Table 5)withrespecttoexperimentallyderived This active state conformation would normally be expected to binding data to attempt to reconcile the divergent observations for favour agonist binding. This is indeed the case for norepinephrine, agonist affinity and potency. Operational analysis yielded values of however epinephrine binding is unchanged for this mutant. While the percent of receptors occupied to cause half-maximal activation mutation of K331 produces a constitutively active receptor, this

(KE). WT receptors reached half-maximal activation with only 8.5 and residue may also have a positive role in promoting epinephrine 10.3% receptor occupation for the endogenous agonists, epinephrine binding. Thus, K331A may create a constitutively active mutant A.P. Campbell et al. / European Journal of Pharmacology 733 (2014) 90–96 95

Table 4 Agonist induced receptor activation.

WT K331A D191A D191A.K331A Ω

pEC50 n EC50 (nM) pEC50 n EC50 (nM) pEC50 n EC50 (nM) pEC50 n EC50 (nM)

Epinephrine 7.170.1 5 74 6.870.1a 4 160 6.670.1b 5 260 6.270.1c 4 630 1.07 Norepineprhine 6.570.1 5 350 6.570.1 3 320 5.970.1b 3 1100 5.970.1b 3 1300 1.14

pEC50, negative log of the concentration of agonist required to activate the receptor to 50% of observed maximum.

EC50, calculated concentration of agonist needed to activate the receptor to 50% of observed maximum. Derived from pEC50.

Ω, Coupling parameter of a mutant cycle analysis, where Ω is equal to the ratio of the product of the EC50 values of WT and double mutant receptors to the product of the

EC50 values of the single mutation receptors, as described in Section 2.9. All data are presented as mean7S.E.M. for ‘n’ repeats, performed in triplicate. a Po0.05 compared to WT. b Po0.01 compared to WT. c Po0.001 compared to WT.

Fig. 4. Agonist associated receptor activation. Epinephrine (panel A) and norepinephrine (panel B) induced production of soluble inositol phosphates by WT(●), K331A (▼), D191A (▲), and D191A/K331A (♦) receptors. Points and bars represent mean7S.E.M of 3–5 experiments performed in triplicate.

Table 5 and D191 were engaged in a stepwise redirection of charge. This Operational analysis of receptor activation. observation was quantiﬁed using mutant cycle analysis. Theoreti- cally, if both residues are acting independently, then the change in WT K331A D191A D191A.K331A binding energy of the double mutation should be the same as the

KE nKE nKE nKE n sum of the change in binding energies of the individual mutations. The similarity of the observed double mutation, and summed b a Epinephrine 8.572.0 5 22.471.9 4 4.571.5 5 16.271.8 4 individual mutations for both agonists does not provide evidence Norepinephrine 10.371.8 5 38.1710.9b 3 9.771.9 3 27.274.0 3 for an interaction between these two residues. It would appear

KE, percent of receptors required to be occupied to cause half-maximal activation. that K331 and D191 are able to exert independent effects on the Calculated according to the Operational Model of Agonism as described binding of agonists to the α1B adrenoceptor. The extracellular in Section 2.9. regions of this receptor have been shown to be a source of All data are expressed as mean7S.E.M. for ‘n’ repeats. selectivity for antagonists (Porter et al., 1996) and this data a Po0.05 compared to WT. suggests that they are also able to contribute to the binding of b Po0.001 compared to WT. agonists. Following the change in agonist affinities, the role of these with a higher affinity for agonists in general but also remove a residues in receptor function was examined. In contrast to nor- feature of epinephrine binding, resulting in an apparently epinephrine's increased affinity for the mutant receptor, its unchanged affinity. Previous study of this mutation showed potency was similar at both WT and K331A receptors. Also, while increased affinity for both ligands at the K331A mutation when epinephrine had an unchanged affinity for the K331A mutation, it in competition with the radioligand [125I]HEAT, however [125I] displayed decreased potency. Due to K331’s suggested role in HEAT and prazosin have previously been shown to produce agonist binding as well as receptor activation, it is difficult to different results at mutant adrenoceptors (Chen, 2001), possibly delineate the precise influences this residue has on binding as well as a result of different binding modes for each radioligand. as receptor activation. Unlike residues such as R3.50, K331 has The unchanged affinity of the three inverse agonists, [3H] influence over not only receptor activation, but ligand binding. prazosin, phentolamine and 5-methylurapidil at the K331A This dual role will produce complex effects on the affinity of, and mutant suggests no gross distortions of the ligand binding pocket activation by agonists. Such mixed results could be explained if and that the observed increase in affinity for norepinephrine is not K331 were considered a micro-switch that is involved in both the a product of a global folding disorder. inactive and active states of the receptor. The combination of both mutations yielded agonist binding Following the decrease in agonist affinity at the D191A mutant, profiles which appear to be a combination of both individual both agonists showed decreased potency. Neither receptor gener- mutations. We originally hypothesised that the two residues, K331 ated significantly different levels of basal or Emax signaling, so it 96 A.P. Campbell et al. / European Journal of Pharmacology 733 (2014) 90–96 would appear that this residue's sole role is in agonist binding. Chen, S., Xu, M., Lin, F., Lee, D., Riek, P., Graham, R.M., 1999. Phe310 in transmem- Application of an operational model of agonism (Black and Leff, brane VI of the α1B-adrenergic receptor is a key switch residue involved in activation and catecholamine ring aromatic bonding. J. Biol. Chem. 274, 1983) further confirms this as the fraction of occupied receptors 16320–16330. fi necessary to elicit half-maximal activation was not signi cantly Cheng, Y.-C., Prusoff, W.H., 1973. Relationship between the inhibition constant (KI) different between WT and the D191A mutant, or between K331A and the concentration of inhibitor which causes 50 per cent inhibition (I50) of and D191A.K331A mutants for either agonist. The non-conserved an enzymatic reaction. Biochem. Pharmacol. 22, 3099–3108. Cherezov, V., Rosenbaum, D.M., Hanson, M.A., Rasmussen, S.r.G.F., Thian, F.S., and unrestrained nature of the ECL2 would ideally place this Kobilka, T.S., Choi, H.-J., Kuhn, P., Weis, W.I., Kobilka, B.K., Stevens, R.C., 2007. residue in extracellular space that would allow it to interact with High-resolution crystal structure of an engineered human β2-adrenergic nearby, solvated ligand. The positively charged amine group of the G protein-coupled receptor. Science 318, 1258–1265. Dror, R.O., Pan, A.C., Arlow, D.H., Borhani, D.W., Maragakis, P., Shan, Y., Xu, H., Shaw, aminergic ligands interacts with a highly conserved aspartate in D.E., 2011. Pathway and mechanism of drug binding to G-protein-coupled 3.32 TMIII: D125 . An identical residue in the extracellular space receptors. Proc. Nat. Acad. Sci. 108, 13118–13123. could possibly be a point of first contact, interacting with ligands Gleitsman, K.R., Shanata, J.A.P., Frazier, S.J., Lester, H.A., Dougherty, D.A., 2009. Long- in a similar manner to the conserved D1253.32. Furthermore, while range coupling in an allosteric receptor revealed by mutant cycle analysis. Biophys. J. 96, 3168–3178. addition of the D191A mutation to the K331A receptor appeared to Hwa, J., Perez, D.M., 1996. The unique nature of the serine interactions for decrease potency, it should be considered that addition of this -adrenergic receptor agonist binding and activation. J. Biol. Chem. 271, mutation would alter agonist affinity. Indeed, operational analysis 6322–6327. Inoue, H., Nojima, H., Okayama, H., 1990. High efficiency transformation of reveals that the fraction of occupied receptors necessary to Escherichia coli with plasmids. Gene 96, 23–28. activate the double mutant receptors is not significantly different Kruse, A.C., Hu, J., Pan, A.C., Arlow, D.H., Rosenbaum, D.M., Rosemond, E., Green, H. from the K331A single mutation for either agonist. Again, D191 F., Liu, T., Chae, P.S., Dror, R.O., Shaw, D.E., Weis, W.I., Wess, J., Kobilka, B.K., 2012. appears to be involved solely in agonist binding. Structure and dynamics of the M3 muscarinic acetylcholine receptor. Nature 482, 552–556. We present here data to suggest that at least one residue in the MacDougall, I.J.A., Griffith, R., 2006. Selective pharmacophore design for second extracellular loop of the α1B adrenoceptor, D191, is able to α1-adrenoceptor subtypes. J. Mol. Graphics Modell. 25, 146–157. promote the binding of the endogenous agonists epinephrine and Nagaoka, Y., Ahmed, M., Hossain, M., Bhuiyan, M.A., Ishiguro, M., Nakamura, T., Watanabe, M., Nagatomo, T., 2008. Amino acids of the human -adrenergic norepinephrine. This is a novel role for the second extracellular ɑ1D receptor involved in antagonist binding. J. Pharmacol. Sci. 106, 114–120. loop in the α1 adrenoceptors and may create an alternative site for Palczewski, K., Kumasaka, T., Hori, T., Behnke, C.A., Motoshima, H., Fox, B.A., Trong, I. targeted, highly-selective ligands of the α1 adrenoceptors. L., Teller, D.C., Okada, T., Stenkamp, R.E., Yamamoto, M., Miyano, M., 2000. Crystal structure of rhodopsin: a G protein-coupled receptor. Science 289, 739–745. Porter, J.E., Hwa, J., Perez, D.M., 1996. Activation of the -adrenergic receptor is Acknowledgements α1B initiated by disruption of an interhelical salt bridge constraint. J. Biol. Chem. 271, 28318–28323. The authors would like to thank Dr. Trevor Lewis for helpful Porter, J.E., Perez, D.M., 1999. Characteristics for a salt-bridge switch mutation of – discussions. the α1B adrenergic receptor. J. Biol. Chem. 274, 34535 34538. Rasmussen, S.G.F., Choi, H.-J., Fung, J.J., Pardon, E., Casarosa, P., Chae, P.S., APC acknowledges the financial support of the Australian DeVree, B.T., Rosenbaum, D.M., Thian, F.S., Kobilka, T.S., Schnapp, A., Konetzki, Postgraduate Award. I., Sunahara, R.K., Gellman, S.H., Pautsch, A., Steyaert, J., Weis, W.I., Kobilka, B.K., 2011. Structure of a nanobody-stabilized active state of the ß2 adrenoceptor. Nature 469, 175–180. References Rosenbaum, D.M., Zhang, C., Lyons, J.A., Holl, R., Aragao, D., Arlow, D.H., Rasmussen, S.G.F., Choi, H.-J., DeVree, B.T., Sunahara, R.K., Chae, P.S., Gellman, S.H., Dror, R. O., Shaw, D.E., Weis, W.I., Caffrey, M., Gmeiner, P., Kobilka, B.K., 2011. Structure Ahmed, M., Hossain, M., Bhuiyan, M.A., Ishiguro, M., Tanaka, T., Muramatsu, I., and function of an irreversible agonist-ß2 adrenoceptor complex. Nature 469, Nagatomo, T., 2008. Mutational analysis of the ɑ1A-adrenergic receptor binding pocket of antagonists by radioligand binding assay. Biol. Pharm. Bull. 31, 236–240. 598–601. Rossier, O., Abuin, L., Fanelli, F., Leonardi, A., Cotecchia, S., 1999. Inverse agonism Ambrosio, C., Molinari, P., Cotecchia, S., Costa, T., 2000. Catechol-binding serines of and neutral antagonism at α1A- and α1B-adrenergic receptor subtypes. Mol. Pharmacol. 56, 858–866. β2-adrenergic receptors control the equilibrium between active and inactive receptor states. Mol. Pharmacol. 57, 198–210. Warne, T., Serrano-Vega, M.J., Baker, J.G., Moukhametzianov, R., Edwards, P.C., Avlani, V.A., Gregory, K.J., Morton, C.J., Parker, M.W., Sexton, P.M., Christopoulos, A., Henderson, R., Leslie, A.G.W., Tate, C.G., Schertler, G.F.X., 2008. Structure of a β1 2007. Critical role for the second extracellular loop in the binding of both adrenergic G-protein-coupled receptor. Nature 454, 486–491. orthosteric and allosteric G protein-coupled receptor ligands. J. Biol. Chem. 282, Waugh, D.J.J., Gaivin, R.J., Zuscik, M.J., Gonzalez-Cabrera, P., Ross, S.A., Yun, J., Perez, 25677–25686. D.M., 2001. Phe-308 and Phe-312 in transmembrane domain 7 are major sites Ballesteros, J.A., Weinstein, H., 1995. Methods in Neurosciences. In: Stuart, C.S. (Ed.), of α1-adrenergic receptor antagonist binding: imidazoline agonists bind like 1995. Academic Press, pp. 366–428 antagonists. J. Biol. Chem. 276, 25366–25371. Black, J.W., Leff, P., 1983. Operational models of pharmacological agonism. Proc. R. Waugh, D.J.J., Zhao, M.-M., Zuscik, M.J., Perez, D.M., 2000. Novel aromatic residues Soc. Lond. 220, 141–162. in transmembrane domains IV and V involved in agonist binding at Cavalli, A., Fanelli, F., Taddei, C., De Benedetti, P.G., Cotecchia, S., 1996. Amino acids α1A-adrenergic receptors. J. Biol. Chem. 275, 11698–11705. fi of the α1B-adrenergic receptor involved in agonist binding: differences in Zhao, M.M., Hwa, J., Perez, D.M., 1996. Identi cation of critical extracellular loop docking catecholamines to receptor subtypes. FEBS Lett. 399, 9–13. residues involved in α1 adrenergic receptor subtype-selective antagonist Chen, S., 2001. Molecular mechanisms of α1-adrenergic receptor activation. binding. Mol. Pharmacol. 50, 1118–1126. Bioorganic & Medicinal Chemistry 22 (2014) 5910–5916

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Bioorganic & Medicinal Chemistry

journal homepage: www.elsevier.com/locate/bmc

Human a1-adrenoceptor subtype selectivity of substituted homobivalent 4-aminoquinolines

Junli Chen a, , Adrian P. Campbell a, , Kaniz F. Urmi a, Laurence P. G. Wakelin a, William A. Denny b, a a, Renate Grifﬁth , Angela M. Finch ⇑ a Department of Pharmacology, School of Medical Sciences, Wallace Wurth Building, UNSW Australia, Sydney, NSW 2052, Australia b Auckland Cancer Society Research Centre, School of Medical Sciences, University of Auckland, Private Bag 92019, Auckland 1142, New Zealand article info abstract

Article history: A series of ring-substituted ethyl- and heptyl-linked 4-aminoquinoline dimers were synthesized and Received 25 May 2014 evaluated for their affinities at the 3 human a1-adrenoceptor (a1-AR) subtypes and the human serotonin Revised 1 September 2014 5-HT1A-receptor (5-HT1A-R). We find that the structure-specificity profiles are different for the two series Accepted 9 September 2014 at the a1-AR subtypes, which suggests that homobivalent 4-aminoquinolines can be developed with a1- Available online 16 September 2014 AR subtype selectivity. The 8-methyl (8-Me) ethyl-linked analogue has the highest affinity for the a1A-AR, 7 nM, and the greatest capacity for discriminating between a1A-AR and a1B-AR (6-fold), a1D-AR (68-fold), Keywords: and the 5-HT1A-R (168-fold). a1B-AR selectivity was observed with the 6-methyl (6-Me) derivative of the a1-adrenoceptor ethyl- and heptyl-linked 4-aminoquinoline dimers and the 7-methoxy (7-OMe) derivative of the heptyl- 5-HT1A-receptor 4-Aminoquinolines linked analogue. These substitutions result in 4- to 80-fold selectivity for a1B-AR over a1A-AR, a1D-AR, and Affinity 5-HT1A-R. In contrast, 4-aminoquinoline dimers with selectivity for a1D-AR are more elusive, since none Selectivity studied to date has greater affinity for the a1D-AR over the other two a1-ARs. The selectivity of the 8-Me ethyl-linked 4-aminoquinoline dimer for the a1A-AR, and 6-Me ethyl-linked, and the 6-Me and 7-OMe heptyl-linked 4-aminoquinoline dimers for the a1B-AR, makes them promising leads for drug development of a1A-AR or a1B-AR subtype selective ligands with reduced 5-HT1A-R affinity. Ó 2014 Elsevier Ltd. All rights reserved.

1. Introduction makes it a therapeutic target for the treatment of benign prostatic hyperplasia (BPH).1 BPH is a common disease among aging men,

The a1-adrenoceptors are G protein-coupled receptors (GPCRs) causing difficulties in urination and a variety of lower urinary tract 2 that exert their function predominantly by mediating smooth mus- symptoms. a1-AR antagonists are widely used to treat this condi- cle contraction. The a1A-AR is the predominant a1-AR subtype tion, as inhibition of a1A-AR stimulation relaxes prostate smooth expressed in the fibro-muscular stroma of the prostate and is muscle, thus relieving the symptoms.3 However, the side effect involved in the contraction of prostatic smooth muscle, which profile of current a1-AR antagonists used in this setting can be associated with their affinity for a1-AR subtypes other than a1A-AR, or for ‘‘off-target’’ affinity for other biogenic amine recep- Abbreviations: [3H] prazosin, [7-methoxy-3H] prazosin; [3H]-OH-DPAT, 8-[3H- tors such as the serotonin 5-HT1A-receptor (5-HT1A-R) and dopa- hydroxy-N,N-di-n-propyl-2-aminotetralin]; BPH, benign prostatic hyperplasia; AR, 4–7 mine D3-R. Prazosin, terazosin and alfuzosin have a adrenoceptor; 5-HT1A-R, serotonin receptor 1A; D3-R, dopamine D3-receptor; DMEM, Dulbecco’s modified Eagle’s medium; FBS, fetal bovine serum; DMSO, quinazoline chemical scaffold (Fig. 1), and due to their equal affin- dimethylsulfoxide; PBS, phosphate buffered saline; DEAE-dextran, diethylaminoe- ity for each of the a1-AR subtypes, have cardiovascular side effects thane-dextran; HEPES, 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid; EDTA, 6 mediated by a1B-AR. Significantly, the cardiovascular side effects ethylenediaminetetraacetic acid; EGTA, ethylene glycol tetraacetic acid; GPCR, G of the quinazoline compounds are mostly avoided with the use protein-coupled receptor; TM, transmembrane helix; GOLD, Genetic Optimization 8 for Ligand Docking; DS, Discovery Studio. of the modestly a1A/a1D-AR-selective antagonist tamsulosin. Corresponding author. Tel.: +61 2 9385 1325. However, tamsulosin and naftopidil, the most prevalently used ⇑ E-mail addresses: [email protected] (J. Chen), [email protected]. au a1A-AR selective drugs for treatment of BPH, fail to discriminate (A.P. Campbell), [email protected] (K.F. Urmi), [email protected] (L.P.G. 5,7 between their intended target, the a1A-AR, and the 5-HT1A-R, Wakelin), [email protected] (W.A. Denny), r.griffi[email protected] contributing in a major way to their side effect profile.9 Thus, the (R. Griffith), angela.fi[email protected] (A.M. Finch). Contributed equally. discovery of new classes of a1A-AR subtype-selective compounds http://dx.doi.org/10.1016/j.bmc.2014.09.017 0968-0896/Ó 2014 Elsevier Ltd. All rights reserved. J. Chen et al. / Bioorg. Med. Chem. 22 (2014) 5910–5916 5911

Prazosin Tamsulosin

Terazosin Naftopidil

Alfuzosin

R = 6-Me, 6-OMe, 7-Me, 7-OMe, 8-Me, and 8-OMe

Figure 1. Structures of selected a1-adrenergic antagonists and studied homobivalent 4-aminoquinoline dimers. Structures of clinically relevant a1-adrenergic antagonists and the unsubstituted 4-aminoquinoline dimer. 4-aminoquinoline dimers are referred to in the text as Cn in Table 1, where n represents the number of methylene groups in the linking chain, along with the substituent and its position, for example, 3 = 6-Me C2.

5,7 with the potential for an enhanced degree of specificity for a1A-AR drugs, we have also investigated binding of the 4-aminoquino- over the other ARs and the 5-HT1A-R is of interest for the treatment lines to the human 5-HT1A-R. of BPH. In previous work, before a1-AR subtypes were identified, some 2. Results and discussion of us had shown that an homologous series of 4-aminoquinoline dimers linked through the 4 position with an alkyl chain (Fig 1), 2.1. Synthesis binds with high affinity to a1-AR in rat cerebral cortex and rat kid- 10,11 ney cortex membranes. In both tissues, highest affinity was The substituted 4-aminoquinolines 1–12 shown in Figure 1 found for the ethyl-, 1, and heptyl-, 2, linked dimers, with the inter- were designed to probe steric and hydrogen bonding interactions vening members, and those longer than 2, having lower affin- between adrenoceptor binding sites and the 6-, 7-, and 8-positions 10,11 ity. This phenomenon was attributed to there being two of the quinoline ring. The 4-aminoquinolines were prepared via binding features on the receptor surface available to this series of reaction of the appropriate commercial 4-chloroquinolines and 11 compounds. In recent work, using recombinant human receptors, either ethane-1,2-diamine or heptane-1,7-diamine in refluxing 13,14 we confirmed this binding pattern with the three a1-AR subtypes, phenol under conditions described previously. and found that 1 has higher affinity at the a1A-AR than 2, as well as selectivity for the a1A-AR and a1B-AR over the a1D-AR, while 2 can- 2.2. Biological results and structure–activity relationships 12 not discriminate between the three a1 subtypes. Our recent findings prompted us to investigate whether deriva- The substituted 4-aminoquinolines 1–12 were evaluated for tives of 1 and 2 have the capacity for more selective discrimination receptor affinity on membrane-expressed human a1-ARs and the between the various a1-AR subtypes, and here we report the syn- 5-HT1A-R in competition radioligand binding experiments using 3 thesis of the compounds and their affinities for the 3 human a1-AR [ H] prazosin (a1A-AR KD = 0.58 ± 0.15 nM, n = 6; a1B-AR subtypes. In addition, because it is commonly found that a1-AR KD = 0.25 ± 0.10 nM, n = 4; a1D-AR KD = 0.45 ± 0.06 nM, n = 3) and 3 antagonists also have substantial affinity for the 5-HT1A-R, and this [ H]-OH-DPAT (5-HT1A-R KD = 1.62 ± 0.46 nM, n = 4). As seen in 12 is believed to be the cause of some of the unwanted effects of these our previous study, 1 has equal affinity for the a1A- and 5912 J. Chen et al. / Bioorg. Med. Chem. 22 (2014) 5910–5916

Table 1

Afﬁnities of homobivalent 4-aminoquinoline analogues at human a1-AR subtypes and the human 5-HT1A-R

Compound a1A-AR a1B-AR a1D-AR 5-HT1A-R

a b a b a b a b pKi Ki (nM) n pKi Ki (nM) n pKi Ki (nM) n pKi Ki (nM) n

*, *, ; 1 C2 7.58 ± 0.07 26 3 7.55 ± 0.12 28 3 6.48 ± 0.04 331 3 5.64 ± 0.19 2291 3 * 3 6-Me C2 6.87 ± 0.09 135 3 7.72 ± 0.25 19 3 6.31 ± 0.04 490 3 6.21 ± 0.44 617 3 *, 4 7-Me C2 6.92 ± 0.19 120 3 7.32 ± 0.07 48 3 6.69 ± 0.08 204 3 5.46 ± 0.29 3467 3 *, *, 5 7-OMe C2 7.16 ± 0.18 69 3 7.30 ± 0.13 50 4 6.67 ± 0.10 214 3 6.05 ± 0.11 891 3 , * *, *, 6 8-Me C2 8.13 ± 0.07 7 3 7.40 ± 0.05 40 3 6.32 ± 0.11 479 3 5.93 ± 0.13 1175 3 *, , *, 7 8-OMe C2 6.71 ± 0.27 195 3 6.49 ± 0.09 324 3 5.70 ± 0.03 1995 3 5.51±0.19 3090 3 *, 2 C7 6.90 ± 0.18 126 3 6.83 ± 0.13 148 3 6.51 ± 0.04 309 3 6.08 ± 0.27 832 3 ,à * 8 6-Me C7 6.21 ± 0.16 617 3 6.82 ± 0.16 151 3 6.32 ± 0.03 479 3 5.96 ± 0.13 1096 3 9 6-OMe C7 6.50 ± 0.15 316 3 6.83 ± 0.03 148 3 6.43 ± 0.33 372 3 5.86 ± 0.20 1380 3 *, 10 7-Me C7 6.95 ± 0.12 112 3 7.29 ± 0.36 51 3 6.31 ± 0.26 490 3 5.90 ± 0.07 1259 3 * *, 11 7-OMe C7 6.59 ± 0.07 257 3 7.46 ± 0.02 35 3 6.64 ± 0.32 229 3 5.55 ± 0.12 2818 3 *, *, 12 8-OMe C7 7.13 ± 0.23 74 3 6.81 ± 0.20 155 3 6.12 ± 0.03 759 3 6.22 ± 0.11 603 3

The data shown for each compound is the mean ± SE of separate assays, performed in duplicate. n Equals the number of assays performed. * Indicates significant difference from the a1A-AR (p <0.05). Indicates significant difference from the a1B-AR (p <0.05). Indicates significant difference for C7 and C2 substituted ligands from parent C2 for same receptor (p <0.05). à Indicates significant difference from parent C7 for the same receptor (p <0.05). a Equates to the negative log of the Ki value. Ki values were calculated according to the equation of Cheng and Prusoff. Ki = IC50/1 + ([L]/KD) where [L] is the radioligand concentration and KD its dissociation constant. b The concentration of ligand required to occupy 50% of all receptors if no radioligand is present.

a1B-ARs, a 13-fold preference for a1A-AR over a1D-AR, and an 88- all 4 receptors. In contrast to the ethyl-linked series, a 7-methyl, fold selectivity for a1A-AR over the 5-HT1A-R (Table 1). The mea- 10, or 8-methoxy, 12, substitution did not decrease binding affinity 15 sured pKa of 4-aminoquinoline is 9.13, and the calculated values, for the a1A-AR. The addition of the 7-methoxy substitution in 11 using the ACD/PhysChem Suite (version 12) from Advanced Chem- increased its a1B-AR selectivity, which was 7-, 6.5- and 81-fold ical Development Labs, Toronto, Canada, for the substituted 4-eth- for the a1A-AR, a1D-AR and the 5-HT1A-R, respectively (Table 1). ylaminoquinoline monomers lie in the range of 8.4–8.9, with the At the a1B- and a1D-ARs, substituents in both ethyl- and heptyl- exception of the 8-methoxy (8-OMe) derivative with a calculated linked series did not alter affinity, with the exception of 8-methoxy pKa of 6.7. Thus, apart from the 8-OMe dimers 7 and 12, at physi- ethyl-linked dimer, 7, which shows decreased affinity. Taking the ological pH these agents will exist predominantly as dications, a1-AR results as a whole, it is clear that 1 has a preference for bind- with the protons located on the quinoline ring nitrogens. That ing to a1A- and a1B-AR over a1D-AR, but that this preference, and the expected reduced charge density on the bulk of the 8-OMe the degree of affinity, is lost for the longer ethyl-linked homologue, 4-aminoquinolines 7 and 12 is not in itself an impediment to 2, suggesting 1 and 2 have different binding environments. receptor binding, is made clear by the finding that the binding properties of the 8-OMe substituted heptyl-linked 4-aminoquino- 2.3. Homology models and docking line, 12, are indistinguishable from those of its unsubstituted parent (Table 1). The unsubstituted bisquinolines 1 and 2, as well as the receptor For the ethyl-linked dimers, adding a 6- or a 7-methyl substitu- subtype-selective derivatives 3, 6, and 11, were docked into ent, (3 and 4), decreased the affinity at a1A-AR by approximately 5- homology models of the three human a1-ARs and the human 5- fold, but did not change the affinity for the other adrenoceptors HT1A-R to provide possible indications as to the receptor interac- compared to the parent compound (Table 1). The decreased affinity tions that contribute to the binding profiles of the selective com- of 3 for the a1A-AR facilitated its selectivity for the a1B-AR over pounds (Table 2, Fig 2). The ethyl-linked compound 1 docked a1A-, a1D-ARs and the 5-HT1A-R. Adding a methyl group in the 8- well into the models for the a1A- and a1B-ARs making H-bond position, 6, thereby extending the quinoline ring along its minor interactions with the conserved orthosteric residues D3.32 and 5.46 à axis, enhanced affinity for a1A-AR by 3.5-fold and again left binding S as well as p–p interactions with conserved aromatic residues to the other receptors unaffected (Table 1). This increased affinity (Table 2). Interaction with D3.32 is considered an essential feature of 16,17 of 6 at the a1A-AR resulted in 6-, 68-, and 168-fold selectivity for aminergic ligand binding. Interestingly, the observed interac- the a1A-AR over a1B-AR, a1D-AR, and the 5-HT1A-R, respectively. tions were with the distal quinoline 4-amino group, not the proton- In contrast, a methoxy group at this position, 7, substantially ated ring nitrogen as might have been expected. S5.46 is responsible reduced the affinity for all adrenoceptor subtypes compared to 1 for H-bond interactions with hydroxyl groups of adrenergic agonists by 6 to 12 fold, but had no effect on binding to the 5-HT1A-R and some antagonists. Compound 1 does not make all of these inter- (Table 1). actions in either the a1D-AR or 5-HT1A-R, potentially explaining the As seen in our previous study,12 the heptyl-linked dimer has a reduced affinity seen at these receptors (Table 2). lower affinity for the a1A- and a1B-ARs (p <0.05) and similar affinity The reduced affinity of compound 3 for the a1A-AR could be at the a1D-AR, compared to 1 (Table 1). As in the ethyl-linked ser- explained by lost p–p and H-bond interactions. Interestingly, the ies, the 6-methyl substitution in 8 decreased the heptyl-linked p–p interactions are also lost at the a1B-AR, however the 6-Me sub- dimer binding affinity for the a1A-AR by 5-fold, and had no discern- stitution distorts the binding pose of compound 3, resulting in ible effect on the other receptor affinities. Similar to 3, the decreased affinity of 8 for the -AR made it selective for the a1A à -AR over -, - ARs and the 5-HT -R. Expanding the bulk Superscripts indicate the Ballesteros–Weinstein numbering scheme where the a1B a1A a1D 1A first digit represents the transmembrane helix (TM) number followed by the position at the 6-position, by the addition of a methoxy group, 9, had no sig- relative to the most conserved residue in each TM, assigned number 50. Numbers nificant effect on the binding characteristics compared to 2 across decrease towards the N-terminus. J. Chen et al. / Bioorg. Med. Chem. 22 (2014) 5910–5916 5913

Table 2 Docking results of bisquinoline dimers

Compound a1A-AR a1B-AR a1D-AR 5-HT1A-R 1 Pose, score 2b, 43.43 1a, 43.39 12b, 37.72 6b, 36.59 H/charge D1063.32, C17645.50, S1925.46 D1253.32, C19545.50, S2115.46 S2625.46 D1163.32, C18745.50 p–p W1023.28, F2896.52 W1213.28, F3116.52 W1723.28, F3656.52, F3847.35 F1123.28 Hydrophobic A1033.29, V1073.33, C1103.36, A1223.29, V1263.33, C1293.36, C19545.50, V1773.33, C1803.36, I24845.52, I1133.29, V1173.33, C1203.36, A1895.44 V19745.52 L3686.55 I18945.52, A2035.46 3 Pose, score 2b, 37.39 1a, 37.51 1a, 37.72 1a, 40.39 H/charge D1063.32 S1022.60, A1223.29, D1253.32, E19445.49 A2555.40 D1163.32, C18745.50 p–p F862.63, F2886.51 F3347.39 Y2545.39 F1123.28 Hydrophobic V1073.33, I17545.49, I17845.52, L1052.63, A1223.29, V1263.33, V19745.52, F1522.59, I24845.52, A2555.40, A932.60, I1133.29, V1173.33, V1855.40, F2896.52, M2926.55, W3076.48, F3106.51 F3656.52, L3686.55, F3887.39 C1203.36, I18945.52, A2035.46, F3087.35 A3656.55, Y3907.43 6 Pose, score 11b, 34.70 2b, 33.42 1a, 34.05 1a, 40.16 H/charge D1063.32, S832.60 D1253.32, C19545.50 D1763.32 D1163.32, C18745.50 p–p F2886.51 W1726.52, F3847.35 F1123.28, F3616.51, F3626.52 Hydrophobic F862.63, V1073.33, I17845.52, L1052.63, W1213.28, A1223.29, C19545.50, F1522.59, M1562.63, V1773.33, Y962.63, F1123.28, I1133.29, F2896.52, F3127.39 V19745.52, A2045.40, F3116.52, L3146.55, C1803.36, I24845.52, F3656.52, A18645.49, I18945.52, A3656.55, P3156.56 L3686.55, F3887.39 L3666.56 2 Pose, score 1c, 64.90 1a, 64.47 1a, 67.79 1a, 55.54 H/charge S1022.60, E19445.49, S2115.46 S1532.60, E1572.64, S2625.46 A93 p–p F2896.52, F3087.35 F3116.52, F3347.39 F3656.52 F362 Hydrophobic V1073.33, C1103.36, A1895.44 L1052.63, V1263.33, C1293.36, K3317.36 M1562.63, V1773.33, C1803.36 A93, C120, A186, F361, A365 11 Pose, Score 1a, 64.87 2b, 63.99 1a, 62.84 2b,d, 56.27 H/charge E872.64 S1022.60, E19445.49, S2115.46 S1532.60, E1572.64, S2625.46 D1163.32 p–p F3127.39 F3116.52, F3347.39 Y2545.39, F3656.52 Y962.63 Hydrophobic V1073.33, C1103.36, A1895.44 L1052.63, V1263.33, C1293.36, V19745.52, M1562.63, V1773.33, C1803.36, A932.60, I1133.29, V1173.33, L3146.55 F3847.35 I18945.52

a Highest scoring pose of the largest cluster, which is pose 1. b Highest scoring pose of the largest cluster, which is not pose 1. c Pose 1, which is not in the largest cluster. d Largest cluster contains <10 members.

D1253.32 making a charge interaction with the protonated ring of the ligands in a conformation that facilitates a more favourable nitrogen, instead of a H-bond interaction with a quinoline amine electrostatic interaction with acidic amino acids in the receptor, at (Fig. 2). A similar observation is made for compound 6 at the least within the endogenous ligand binding pocket. By this means, a1A-AR. Here the distorted binding pose again facilitates a charge increases in affinity appear to be the consequence of an enhanced interaction between D1063.32 and the ring nitrogen: a feature that interaction between a protonated quinoline ring nitrogen and the potentially explains the high affinities and selectivity of com- conserved D3.32. Such a direct interaction between D3.32 and a pro- pounds 3 and 6 for a1B-AR and a1A-AR respectively. The only other tonated amine is often considered a general feature of adrenergic docked pose where a charge, rather than a H-bond interaction, was ligand-receptor interaction, however the basic amine is usually observed was for compound 6 at the a1D-AR (Table 2). Again, this located more centrally on the ligand than is the case with the biswas concomitant with a loss of p–p interaction with F6.52. It would quinolines (Fig. 1). In addition, it is also clear from the docking seem that this trade-off is only sufficient to maintain, rather than studies that the heptyl-linked dimers are able to access areas of increase binding at the a1D-AR. the receptor outside of the orthosteric binding site. For example, The heptyl-linked compound 2 when docked into the four the 7-OMe substituted compound 11 makes alternative H-bond homology models makes p–p interactions with the conserved interactions with residues outside of the endogenous ligand bind- 6.52 3.32 2.65 2.61 F but fails to interact with the conserved D at any of the ing pocket such as E87 at the a1A-AR, and S102 of the a1B-AR. receptors, likely explaining the generally poorer affinity of this These data suggest that the ethyl- and heptyl-linked dimers may compound at the a1A- and a1B-ARs (Table 2, Fig. 2). The 7-OMe be too short to simultaneously interact with orthosteric residues substituted compound 11 showed increased affinity over the par- as well as these extracellular residues. ent compound 2 at the a1B-AR (Table 1). Compound 11 made similar interactions with the a1B-AR as compound 2. The only 3. Conclusions additional contacts observed being hydrophobic interactions with § 45.52 6.55 the extracellular loop 2 residue V197 and L314 . These addi- Compound 1 has a preference for binding to a1A-AR and a1B-AR tional interactions may be contributing to the a1B-AR selectivity of over a1D-AR, but this preference, together with a degree of affinity 45.52 11 since V197 is known to be responsible for the binding selec- at a1A- and a1B-ARs is lost for the heptyl-linked homologue 2. Sub- 18 6.55 tivity of some antagonists at the a1B-AR, and L314 is thought to stitutions in the quinoline ring modify affinity and a1-AR subtype 19 play a role in the selective binding of agonists at the a1B-AR. selectivity, and the structure–affinity relationships for the three Overall, the docking studies suggest that substituents on the subtypes are different in the two ligand series. For example, at quinoline ring that influence affinity do so by promoting binding the a1A-AR, with the exception of 6, which binds more avidly, all substituents studied in both the ethyl- and heptyl-linked series

are neutral or lessen afﬁnity. At the a1B-AR, substituents in the § Superscripts indicate extracellular loop 2 numbering, corresponding residues heptyl-linked series are generally neutral, whereas in the ethyl- have been labelled 45.x, 45 indicating the location is between TMs 4 and 5 and x a linked series all substituents are again neutral or detrimental. At number relative to the conserved cysteine residue which is assigned number 50. Numbers decrease towards the N-terminus the a1D-AR, all substitutions in the heptyl-linked 4-aminoquino- 5914 J. Chen et al. / Bioorg. Med. Chem. 22 (2014) 5910–5916

Figure 2. Docking of selected aminoquinoline dimers into human a1-AR and 5-HT1A-R homology models. Compounds 1, 2, 3, 6, and 11 were docked into homology models of the a1A-AR (A,B), a1B-AR (C,D), a1D-AR (E,F), and 5-HT1A-R (G,H) based on the dopamine D3 receptor crystal structure (3PBL). The receptor is shown in light grey with helices TMIII and TMVII labelled for orientation. Compounds 1, 3, and 6 are shown in light, mid, and dark purple, respectively (A, C, E and G). Compounds 2, and 11 are shown in light and dark green, respectively (B, D, F and H). Charge interactions are shown as dashed orange lines. J. Chen et al. / Bioorg. Med. Chem. 22 (2014) 5910–5916 5915 lines are neutral, and in the ethyl-linked series they are neutral or 7.50 (d, J = 8.0 Hz, 1H), 6.98 (d, J = 8.0 Hz, 1H), 4.06 (s, 3H), 3.93 detrimental. These findings illustrate that the differences in the (m, 1H). Anal (C22H24N4O2Cl2) Reqd: C, 59.06; H, 5.40; N, 12.53; environment of the two receptor binding sites of the bisquinolines Cl, 15.85. Found: C, 59.11; H, 5.81; N, 12.36; Cl, 16.12. can be exploited independently in the search for subtype-selective agents. For instance, with the compounds studied to date, the most 4.1.6. N1,N7-Bis(6-methylquinolin-4-yl)heptane-1,7-diamine potent and selective agent for the a1A-AR is found in the ethyl- diHBr (8) 1 linked series; a1B-AR affinity and selectivity can be found in both Mp 66–69 °C. H NMR [(CD3)2SO] d 13.86 (br s, 1H), 9.07 (s, 1H), the ethyl- and heptyl-linked series; and the ligand with highest 8.45 (d, J = 7.0 Hz, 1H), 8.37 (s, 1H), 7.83 (m, 1H), 7.75 (d, J = 7.0 Hz, affinity at the a1D-AR is a derivative of the ethyl-linked homologue, 1H), 6.84 (d, J = 7.0 Hz, 1H), 3.51 (m, 2H), 1.69 (m, 2H), 1.41 (s, 3H). 1. All of the 4-aminoquinolines bind poorly to the 5-HT1A-R, with Anal (C27H34N4Br2) Reqd: C, 56.42; H, 5.97; N, 9.76; Br, 27.82. affinities generally in the micromolar range. This work provides Found; C, 56.45; H, 5.96; N, 9.93,; Br, 27.84. the foundation for future efforts to refine further a1-AR subtype selectivity amongst the 4-aminoquinoline adrenergic ligands with- 4.1.7. N1,N7-Bis(6-methoxyquinolin-4-yl)heptane-1,7-diamine out losing selectivity against the 5-HT1A-R. diHCl (9) 1 Mp 255-256 °C. H NMR [(CD3)2SO] d 13.75 (br s, 1H), 8.93 (s, 4. Experimental section 1H), 8.41 (d, J = 7.0 Hz, 1H), 7.86 (m, 1H), 7.55 (m, 1H), 6.77 (d, J = 7.0 Hz, 1H), 3.92 (s, 3H), 3.50 (m, 2H), 1.70 (m, 2H), 1.42 (m, 4.1. Chemistry 3H). Anal (C27H34N4O2Cl2) Reqd: 62.66; H, 6.62; N, 10.83; Cl, 13.70. Found: C, 62.54; H, 6.87; N, 11.66; Cl, 13.46. Further analysis NMR spectra were recorded on a Bruker Avance 400 spectrom- of compound 9 via HPLC showed a purity of 97.7%. eter; chemical shifts are reported in d using residual DMSO as 1 7 internal standard when measured in d6-DMSO. Analyses were car- 4.1.8. N ,N -Bis(7-methylquinolin-4-yl)heptane-1,7-diamine ried out in The Campbell Microanalytical Laboratory, University of diHCl (10) 1 Otago, Dunedin, New Zealand. The bisquinolines were prepared by Mp 256–258 °C. H NMR [(CD3)2SO] d 13.87 (br s, 1H), 9.22 (s, reacting equimolar amounts of the appropriate 4-chloroquinoline 1H), 8.45 (dd, J = 8.0, 12.0 Hz, 2H), 7.69 (s, 1H), 7.52 (dd, J = 10.0, and the diamine in excess phenol at 140 °C for 30–60 min, fol- 1.5 Hz, 1H), 6.77 (d, J = 7.0 Hz, 1H), 3.50 (m, 2H), 2.79 (s, 3H), lowed by crystallisation of the dihydrochloride product from 1.69 (m, 2H), 1.40 (m, 3H). Anal (C27H24N4Cl2) Reqd: 66.79; H, methanol/ethyl acetate. 7.06; N, 11.55; Cl, 14.52. Found; C, 66.81; H, 7.28; N, 11.64; Cl, 14.62. 4.1.1. N1,N2-Bis(6-methylquinolin-4-yl)ethane-1,2-diamine 1 7 diHCl (3) 4.1.9. N ,N -Bis(7-methoxyquinolin-4-yl)heptane-1,7-diamine 1 Mp >360 °C. H NMR [(CD3)2SO] d 13.82 (br s, 1H), 9.09 (s, 1H), diHCl (11) 1 8.44 (d, J = 7.0 Hz, 1H), 8.37 (s, 1H), 7.84 (m, 1H), 7.75 (d, Mp 165–167 °C. H NMR [(CD3)2SO] d 13.70 (br s, 1H), 9.15 (s, J = 7.0 Hz, 1H), 6.81 (d, J = 7.0 Hz, 1H), 3.61 (s, 3H), 3.50 (m, 2H). 1H), 8.49 (d, J = 10 Hz, 1H), 8.40 (d, J = 7.0 Hz, 1H), 7.29 (m, 2H),

Anal (C22H24N4Cl2) Reqd: C, 63.61; H, 5.82; N, 13.49; Cl, 17.07. 6.70 (d, J = 7.0 Hz, 1H), 3.93 (s, 3H), 3.47 (m, 1H), 1.67 (m, 2H), Found: C, 63.37; H, 5.84; N, 13.62; Cl, 17.19. 1.39 (m, 3H). Anal (C27H34N4O2Cl2) Reqd: 62.66; H, 6.62; N, 10.83; Cl, 13.70. Found: 66.23; H, 6.83; N, 11.08; Cl, 13.57. 4.1.2. N1,N2-Bis(7-methylquinolin-4-yl)ethane-1,2-diamine 1 7 diHCl (4) 4.1.10. N ,N -Bis(8-methoxyquinolin-4-yl)heptane-1,7-diamine 1 Mp >360 °C. H NMR [(CD3)2SO] d 13.72 (br s, 1H), 9.17 (s, 1H), diHBr (12) 1 8.49 (d, J = 10 Hz, 1H), 8.41 (d, J = 7.0 Hz, 1H), 7.25 (m, 2H), 6.70 Mp 63–66 °C. H NMR [(CD3)2SO] d 12.88 (br s, 1H), 9.12 (s, 1H), (d, J = 7.0 Hz, 1H), 4.06 (s, 3H), 3.55 (s, 3H), 3.47 (m, 1H). Anal 8.39 (d, J = 7.0 Hz, 1H), 8.36 (d, J = 9.0 Hz, 1H), 7.82 (d, J = 7.0 Hz,

(C22H24N4Cl2) Reqd: C, 63.61; H, 5.82; N, 13.49; Cl, 17.07. Found: 1H), 7.59 (m, 1H), 6.86 (d, J = 7.0 Hz, 1H), 3.52 (m, 2H), 2.63 (s, C, 63.39; H, 5.97; N, 13.65; Cl, 17.32. 3H), 1.69 (m, 2H), 1.40 (m, 3H). Anal (C27H34N4O2Br2) Reqd: 53.48; H, 5.65; N, 9.24; Br, 26.38. Found: C, 53.12; H, 5.81; 9.83; 4.1.3. N1,N2-Bis(7-methoxyquinolin-4-yl)ethane-1,2-diamine Br, 27.45. Further analysis of compound 12 via HPLC showed a pur- diHCl (5) ity of 99.2%. 1 Mp >360 °C. H NMR [(CD3)2SO] d 13.75 (br s, 1H), 9.48 (s, 1H), 8.56 (m, 1H), 8.42 (d, J = 7.0 Hz, 1H), 7.30 (m, 2H), 6.84 (d, 4.2. Binding assays

J = 7.0 Hz, 1H), 3.92 (s, 3H), 3.88 (m, H). Anal (C22H24N4O2Cl2) Reqd: C, 59.06; H, 5.40; N, 12.53; Cl, 15.85. Found: C, 59.21; H, 5.76; N, COS-1 cells (American Type Culture Collection, Manassas, VA, 12.37; Cl, 16.09. USA) were cultured in Dulbecco’s modiﬁed Eagle’s medium (DMEM) supplemented with 10% (v/v) heat inactivated foetal 1 1 4.1.4. N1,N2-Bis(8-methylquinolin-4-yl)ethane-1,2-diamine bovine serum (FBS), 100 lg mLÀ penicillin and 100 lgmLÀ strep- diHCl H2O (6) tomycin. Cells were maintained and passaged on reaching conﬂu- 1 Mp >360 °C. H NMR [(CD3)2SO] d 12.95 (br s, 1H), 9.12 (s, 1H), ence using standard cell culture techniques and replaced by 8.41 (d, J = 7.0 Hz, 1H), 8.35 (d, J = 9.0 Hz, 1H), 7.81 (d, J = 7.0 Hz, lower passage number cells upon nearing 50 passage cycles. Tran- 1H), 7.59 (m, 1H), 6.86 (d, J = 7.0 Hz, 1H), 3.52 (s, 3H), 2.63 (m, sient transfection of human a1A- and a1B-ARs and 5-HT1A-R was

2H). Anal (C22H26N4OCl2) Reqd: C, 60.97; H, 6.05; N, 12.93; Cl, performed using pcDNA 3.1+ vectors containing inserted cDNA 16.30. Found: C, 60.98; H, 6.08; N, 12.77; Cl, 16.12. for each of the receptors (Missouri S&T cDNA resource centre, MO, USA), and for the human a1D-AR via pMV6-XL5 vector (Ori- 1 2 4.1.5. N ,N -Bis(8-methoxyquinolin-4-yl)ethane-1,2-diamine gene, Rockville, MO, USA) containing inserted a1D-AR cDNA. The diHCl (7) diethylaminoethane-dextran (DEAE-dextran) methodology was 1 24 Mp 267–269 °C. H NMR [(CD3)2SO] d 13.38 (br s, 1H), 9.73 (s, used to perform the transfection as previously described. Mem- 1H), 8.33 (d, J = 7 .0 Hz, 1H), 8.27 (d, J = 9.0 Hz, 1H), 7.61 (m, 1H), brane suspensions were formed from COS-1 cells transiently trans- 5916 J. Chen et al. / Bioorg. Med. Chem. 22 (2014) 5910–5916 fected with the cDNA of interest, as previously described.25 Cells in the template structure (eticlopride) was copied into the homol- were scraped from the surface of culture plates and suspended in ogy models to avoid the collapse of the binding pockets. Homology phosphate buffered saline (PBS), which was then centrifuged at models were generated using the MODELLER21 package as imple- 500 g for 4 min. The pellet was resuspended in 20 mL of a solution mented in DS 4.0 (www.accelrys.com), generating 100 models Â containing 20 mM HEPES and 10 mM EDTA (4 °C), pH 7.4, and dis- and the top model, judged by PDF energy was used without further rupted by homogenization using an ultratrex for 10 s at a speed of refinement. 20,500 rpm and repeated 3 times, with an interval of 30 s between Possible binding sites and poses of the compounds were inves- each homogenization, during which the solution was placed on ice. tigated by docking them into homology models of the three a1-ARs Nuclear debris was removed by centrifugation at 1300 g for and the 5-HT -R using the Genetic Optimization for Ligand Dock- Â 1A 10 min at 4 °C, the supernatant was then centrifuged at 40,000 g ing (GOLD) algorithm (Cambridge Crystallography Data Centre, Â for 60 min at 4 °C. The resulting membrane pellet was resuspended UK) in its implementation in Discovery Studio software (DS), ver- in HEM buffer (20 mM HEPES, 1.4 mM EGTA and 12.5 mM MgCl2, sion 4.0 (Accelrys Inc., San Diego, CA, USA). Hydrogens were added pH 7.4) and 10% (v/v) glycerol for a1-ARs, and in HEPES/CaCl2 buf- to all ligands and the receptor prior to performing the docking fer (a 20 mM HEPES and 4 mM CaCl2; pH 7.4) and 10% (v/v) glyc- runs. All ligands were protonated at the ring nitrogens prior to erol for the 5-HT -R, and stored at 80 °C. Protein concentration docking and minimised under the CHARMm forcefield. The binding 1A À was determined by using the Bradford reagent (Sigma, St Louis, pocket was defined as a 16 Å sphere centred between residues MO, USA). F862.64, D1063.32, Q17745.51, I17845.52, N17945.53, S1885.42 and 5.46 The radioligand binding reaction mixtures were incubated at S192 in the a1A-AR and the same coordinates used for all other room temperature for 1 h, and the reaction was terminated by models. The number of docking runs was set to 100, ‘Detect Cavity’, the addition of PBS (4 °C) and vacuum filtration through GF/B fil- ‘Early termination’, and ‘Flip amide bonds’ were set to ‘False’. ‘Flip ters (Whatman, Maidstone, UK) using a Brandel 48-cell harvester pyramidal nitrogens’ was set to ‘True’. All other parameters were (Gaithersburg, MD, USA). Radioactivity was measured by liquid left at their default values. GOLD Scores were analysed for the scintillation counting. For a1-AR binding, all ligands and mem- highest scored pose and the highest scoring pose in the largest branes were suspended in HEM buffer and for 5-HT1A-R binding, cluster at an RMSD of approximately 1–2 Å. Representative poses all ligands and membranes were suspended in HEPES/CaCl2 buffer. were analysed for hydrogen bonds, charge interactions, p-interac- In saturation binding assays, membranes containing each a1-AR tions and hydrophobic interactions between the ligand and subtype or the 5-HT1A-R were incubated with various concentra- receptor. tions of [3H] prazosin (0.125–16 nM) or [3H]-OH-DPAT (0.5– 16 nM) in a total volume of 200 lL. In competition binding assays, Acknowledgments 3 a1-ARs were incubated with 200 pM of [ H] prazosin and increasing concentrations of test compounds in a total volume of 200 lL. J.C. acknowledges the financial support of the China Scholarship Non-specific binding was defined as binding in the presence of Council.

100 lM phentolamine and the 5-HT1A-R containing membranes were incubated with 1 nM of [3H]-OH-DPAT and increasing con- References and notes centrations of test compounds in a total volume of 200 lL. Non- specific binding was defined as binding in the presence of 10 lM 1. Nasu, K.; Moriyama, N.; Kawabe, K.; Tsujimoto, G.; Murai, M.; Tanaka, T.; Yano, J. Br. J. Pharmacol. 1996, 119, 797. serotonin. Nonlinear regression analysis of saturation and compe- 2. Yoo, T. K.; Cho, H. J. Korean J. Urol. 2012, 53, 139–148. tition binding data was performed using the curve fitting program 3. Beduschi, M. C.; Beduschi, R.; Oesterling, J. E. Urology 1998, 51, 861. 4. Andersson, K. E.; Wyllie, M. G. BJU Int. 2003, 92, 876. GraphPad Prism 6.0 (San Diego, CA, USA). Inhibition constants (Ki) 5. Palea, S.; Chang, D. F.; Rekik, M.; Regnier, A.; Lluel, P. J. Cataract Refract. Surg. for each tested compound were determined by transformation of 2008, 34, 489. the program-calculated IC50 (concentration of ligand resulting in 6. Rudner, X. L.; Berkowitz, D. E.; Booth, J. V.; Funk, B. L.; Cozart, K. L.; D’Amico, E. 50% inhibition of [3H] prazosin or [3H]-OH-DPAT) value using the B.; El-Moalem, H.; Page, S. O.; Richardson, C. D.; Winters, B.; Marucci, L.; Circulation 100 Cheng–Prusoff equation, whereby K = IC /1 + (L/K ), where [L] is Schwinn, D. A. 1999, , 2336. i 50 D 7. Takei, R.-I.; Ikegaki, I.; Shibata, K.; Tsujimoto, G.; Asano, T. Jpn. J. Pharmacol. 3 3 200 pM [ H] prazosin (a1-ARs) or 1 nM [ H]-OH-DPAT (5-HT1A-R) 1999, 79, 447. and KD is the dissociation constant. The competitive binding data 8. Milani, S.; Djavan, B. BJU Int. 2005, 95, 29. for each ligand was tested for both one- and two- site binding. A 9. Wolters, J. P.; Hellstrom, W. J. Rev. Urol. 2006, 8, S18. 10. Adams, A.; Jarrott, B.; Denny, W. A.; Wakelin, L. P. G. Eur. J. Pharmacol. 1986, one-site binding model was determined as the appropriate form 127, 27. of analysis for all binding data. Statistically significant differences 11. Adams, A.; Jarrott, B.; Elmes, B. C.; Denny, W. A.; Wakelin, L. P. Mol. Pharmacol. (p <0.05) between the affinities of all compounds were determined 1985, 27, 480. 12. Chen, J.; Murad, A. K.; Wakelin, L. P. G.; Denny, W. A.; Griffith, R.; Finch, A. M. using one-way ANOVA and Student–Newman–Keuls multiple Biochem. Pharmacol. 2013, 85, 1534. comparison tests. 13. Denny, W. A.; Atwell, G. J.; Roberts, P. B.; Anderson, R. F.; Boyd, M.; Lock, C. J.; Wilson, W. R. J. Med. Chem. 1992, 35, 4832. 14. Han, Y. F.; Li, C. P. L.; Chow, E.; Wang, H.; Pang, Y. P.; Carlier, P. R. Biorg. Med. 4.3. Homology models and docking Chem. 1999, 7, 2569. 15. Perrin, D. D. Dissociation Constants of Organic Bases in Aqueous Solution; ClustalW (www.uniprot.org) was used to align the related GPCR Butterworths, London: London, 1965. 16. Porter, J. E.; Hwa, J.; Perez, D. M. J. Biol. Chem. 1996, 271, 28318. sequences of human a1A-, a1B-, a1D-, and b2-ARs, human D2- and 17. Strader, C. D.; Sigal, I. S.; Register, R. B.; Candelore, M. R.; Rands, E.; Dixon, R. A. D3-Rs, human 5-HT1A-R, human histamine H1-R, turkey b1-AR Proc. Nat. Acad. Sci. U.S.A. 1987, 84, 4384. and bovine rhodopsin. The pairwise alignments used to generate 18. Zhao, M. M.; Hwa, J.; Perez, D. M. Mol. Pharmacol. 1996, 50, 1118. 19. Hwa, J.; Graham, R. M.; Perez, D. M. J. Biol. Chem. 1995, 270, 23189. the models were hand edited to ensure maximum overlap of con- 20. Chien, E. Y.; Liu, W.; Zhao, Q.; Katritch, V.; Han, G. W.; Hanson, M. A.; Shi, L.; served sequences and to minimise gaps. Chain A of the D3 recep- Newman, A. H.; Javitch, J. A.; Cherezov, V.; Stevens, R. C. Science 2010, 330, tor–eticlopride complex (PDB ID: 3PBL)20 was selected as the 1091. template. The T4 lysozyme of the template structure and corre- 21. Sali, A.; Blundell, T. L. J. Mol. Biol. 1993, 234, 779. sponding residues of target structures were removed. The ligand