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DETERMINATION OF MITRAGYNINE AS A SUBSTRATE, INDUCER, OR INHIBITOR OF P- GLYCOPROTEIN DRUG TRANSPORTER, AND PREDICTION OF DRUG-HERB INTERACTION

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DETERMINATION OF MITRAGYNINE AS A SUBSTRATE, INDUCER, OR INHIBITOR OF P- GLYCOPROTEIN DRUG TRANSPORTER, AND PREDICTION OF DRUG-HERB INTERACTION

RISKS

NORADLIYANTI BINTI RUSLI

UNIVERSITI SAINS MALAYSIA

2017

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DETERMINATION OF MITRAGYNINE AS A SUBSTRATE, INDUCER, OR INHIBITOR OF P- GLYCOPROTEIN DRUG TRANSPORTER, AND PREDICTION OF DRUG-HERB INTERACTION

RISKS

by

NORADLIYANTI BINTI RUSLI

Thesis submitted in fulfillment of the requirements for the degree of

Master of Science

June 2017

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ACKNOWLEDGEMENT

Praise to Allah S.W.T for blessing me with patience and perseverance to conduct this research well.

First and foremost, I would like to wish countless thanks and gratitude to my supervisor, Assc. Prof. Dr. Tan Mei Lan for all her guidance, knowledge, advice, and comments that she shared and taught, throughout my research project, especially in conducting experiments and writing this thesis. Her great support, understanding, and patience in providing me with a great facilities and good working environment really help me in finishing this project well. Same appreciation goes to my Co-supervisor, Prof. Dr. Gurjeet Kaur Chatar Singh for her time, comments and advice especially on the analysis of immunocytochemistry images.

I would like to acknowledge Fundamental Research Grant Scheme (FRGS) from the Ministry of Higher Education Malaysia as well as ScienceFund from the Ministry of Science, Technology and Innovation Malaysia for providing me financial support in completing this research project. Same appreciation goes to the Ministry of Higher Education and Universiti Sains Malaysia, which have sponsored my tuition fees through the MyBrain15 program and USM Fellowship as well as IPharm for the great facilities provided. I would also like to dedicate my special thanks to my labmates (Yea Lu, Asyraf, Yi Fan, Yoong Min, Heng Kean, Rina and others) for helping much and putting all their effort, time and energy in guiding me on the procedure as well as for all the best moments that we shared together. Their encouragement and knowledge that been shared with me will always be remembered.

Last but not least, I would like to thank my dearest family members (En.Rusli, Pn.Norsiah, Azwan, Amalina, Amelia and Hamizan) for their unlimited moral support and prays that kept me motivated to finish my study.

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TABLE OF CONTENTS

Acknowledgement ii

Table of Contents iii List of Tables ix

List of Figures xi List of Abbreviations vx

List of Symbols xviii

List of Units xix

Abstrak xx

Abstract xxii

CHAPTER 1: INTRODUCTION 1.1 Background 1

1.2 Drug interactions 4 1.3 Pharmacodynamic mechanism of drug interactions 5

1.4 Pharmacokinetic mechanism of drug interactions 7

1.4.1 Drug absorption and distribution 7

1.4.2 Drug metabolism 8

1.4.3 Drug elimination 10

1.5 Membrane transporter 11

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1.6 ABC transporter superfamily 12

1.7 P-glycoprotein (P-gp) 18

1.7.1 Background and structure of P-gp 18

1.7.2 Substrate of P-gp 22

1.7.3 Inhibitor and inducer of P-gp 24

1.7.4 Roles of P-gp in drug interactions 29

1.8 Drug-herb interactions 31

1.9 Approaches for assessing P-gp mediated drug-drug or drug-herb 32 interactions

1.9.1 Computational in silico methods 32

1.9.2 In vitro models 34

1.10 Mitragyna speciosa Korth 34

1.11 Rationale of the study 38

1.12 Objectives of the study 39

CHAPTER 2: MATERIALS AND METHODS

2.1 Experimental design 40

2.2 Materials and reagents 40

2.3 Preparation of materials 40

2.4 Cell culture 45

2.4.1 Maintenance of cells 45

2.4.2 Thawing frozen cells 45

2.4.3 Subculturing of cells 45

2.4.4 Cell counting using hemocytometer 46

2.4.5 Cryopreservation of cells 47

2.5 In silico simulation for prediction of P-gp substrate and inhibitor 47

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2.5.1 Preparation of macromolecule 49

2.5.2 Preparation of ligands 49

2.5.3 Grid generation and docking simulation using Autodock 4.2 49 2.5.4 Docking visualization and protein-ligand interaction prediction 50

2.6 Cell proliferation assay 50

2.6.1 Cells seeding and treatment of cells 50

2.6.2 Determination of cytotoxic parameters and optimum

concentration range for mitragynine in Caco-2 cell line 52

2.7 Bidirectional transport assay 54

2.7.1 Determination of compounds’ retention time and HPLC

method validation 54

2.7.1(a) HPLC instrumentation and conditions 54 2.7.1(b) Determination of compounds’ retention time 55 2.7.1(c) Bio-analytical method validation 55

2.7.1(c)(i) Selectivity 56

2.7.1(c)(ii) Linearity 56

2.7.1(c)(iii) Precision 57

2.7.1(c)(iv) Accuracy 58

2.7.2 Cell seeding and differentiation 58

2.7.3 Checking TEER value 59

2.7.4 Optimization of bidirectional assay 62

2.7.4(a) Optimization of incubation time using digoxin,

a known P-gp substrate 62

2.7.4(b) Optimization of bidirectional assay for inhibitor

determination using quinidine, a known P-gp inhibitor 65

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2.7.5 Determination of mitragynine as P-gp substrate 66 2.7.6 Determination of mitragynine as P-gp inhibitor

using bidirectional assay 66

2.8 One-step reverse transcription quantitative polymerase

chain reaction (RT-qPCR) 67

2.8.1 Primers and probes design 67

2.8.2 Determination of optimum primer annealing temperature

and melt curve analysis 67

2.8.3 Determination of optimum probe concentration 70 2.8.4 Determination of RT-qPCR amplification efficiency 70 2.8.5 Cell seeding and treatment for determination of the

effects of mitragynine on P-gp gene expression 72

2.8.6 Isolation of total cellular RNA 72

2.8.7 Quantitation and assessment of purity of total cellular RNA 73

2.8.8 DNase treatment of total cellular RNA 73

2.8.9 Agarose gel preparation and gel electrophoresis of

total cellular RNA 74

2.8.10 Determination of mRNA expression of target genes 74

2.9 Western blot analysis 75

2.9.1 Buffer preparation 75

2.9.2 Cell seeding and treatment for determination of

the effects of mitragynine on P-gp protein expression 75 2.9.3 Protein extraction using Mem-PER plus

membrane protein extraction kit 75

2.9.4 Protein quantitation using Bio-Rad DC protein assay 77

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2.9.5 Sodium dodecyl sulfate polyacrylamide gel electrophoresis

(SDS-PAGE) 78

2.9.6 Immunoblotting and visualization of protein 78

2.10 Immunocytochemistry 80

2.10.1 Cell seeding and treatment for immunocytochemistry 80 2.10.2 Fixation, immunofluorescence staining and confocal

Microscopy 81

2.11 Data analysis 82

CHAPTER 3: RESULT

3.1 Molecular docking 84

3.1.1 Molecular docking of digoxin and mitragynine

within the P-gp substrate binding site 84

3.1.2 Molecular docking of quinidine and mitragynine

within the P-gp ATP-binding site 89

3.2 The optimum concentration range of mitragynine in Caco-2

cell line 94

3.3 Bidirectional transport assay 94

3.3.1 HPLC parameters and HPLC method validation 94 3.3.1(a) Chromatographic separation of compounds 94 3.3.1(b) Bio-analytical method validation 97 3.3.2 Determination of TEER value during 21 days of culture 105 3.3.3 Optimization of bidirectional assay 105 3.3.4 Determination of mitragynine as a substrate of

P-gp using bidirectional transport assay 110

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3.3.5 The effects of mitragynine on the transport activity

of P-gp 110

3.4 The effects of compounds on P-gp mRNA expression 113

3.4.1 Primers and probes sequence 113

3.4.2 Purity and integrity of RNA 117

3.4.3 Optimum primer annealing temperature and primer specificity by melt curve analysis 117

3.4.4 RT-qPCR amplification efficiency 117

3.4.5 The effects of mitragynine, rifampicin, and quinidine on the mRNA expression of P-gp in Caco-2 cell line 121

3.5 The effects of compounds on the P-gp protein expression in Caco-2 cell line 126

3.6 The effects of compounds on the protein expression and localization of P-gp using immunocytochemistry 131

CHAPTER 4: DISCUSSION 137

CHAPTER 5: CONCLUSION 153

REFERENCES 154

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LIST OF TABLES

Page Table 1.1 Human ABC transporter genes, and their functions. 15 Table 1.2 P-gp substrates, inhibitors, and inducers organized by drug class. 26 Table 2.1 List of materials and reagents with their manufacturers. 42 Table 2.2 Stock and working solutions preparation. 44 Table 2.3 Two-dimensional (2D) structure of ligands for docking

simulation within P-gp. 48

Table 2.4 Oligonucleotide primer and probe sets used for the

amplification of gene expression in Caco-2 cell line. 68 Table 2.5 RT-qPCR master mix and amplification cycle for iTaq

Universal SYBR® Green One-Step kit. 69

Table 2.6 RT-qPCR master mix and amplification cycle for Taqman®

RNA-to-CT 1-Step kit. 71

Table 2.7 Composition for resolving and stacking gel of polyacrylamide

gel. 79

Table 3.1 Molecular interaction of digoxin and mitragynine within the

substrate binding site of P-gp. 86

Table 3.2 Molecular interaction of quinidine and mitragynine within

the ATP-binding site of P-gp. 90

Table 3.3 Summary of precision of HPLC assay for digoxin and

mitragynine in complete transport buffer. 103 Table 3.4 Summary of accuracy of HPLC assay for digoxin and

mitragynine in complete transport buffer. 104

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Table 3.5 Representative readings for TEER values of 12 monolayer

cells after 21 days of culture. 106 Table 3.6 Primers and probes sequences used for the RT-qPCR. 115

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LIST OF FIGURES

Page Figure 1.1 Generalized mechanistic insight of drug interactions. 6 Figure 1.2 Various distribution of protein transporter in the membrane

of cells in human. 13

Figure 1.3 Basic units of P-gp. 20

Figure 1.4 Localization of P-gp in various organs of human. 21 Figure 1.5 Mechanism for transportation of substrate via P-gp. 23 Figure 1.6 The plant and leaves of M.speciosa Korth. 35

Figure 2.1 Experimental flow chart. 41

Figure 2.2 Cell seeding and treatment labelling for cell proliferation assay. 51 Figure 2.3 Formula to calculate percentage of growth. 53 Figure 2.4 Illustration of cells growing on the polycarbonate membrane insert. 60 Figure 2.5 Voltohmmeter with its compartments and illustration on how the

TEER value was measured. 61

Figure 2.6 Formula to calculate apparent permeability coefficient (Papp)

and net efflux ratio (ER). 64

Figure 2.7 Mathematical model for relative quantification in RT-qPCR . 76 Figure 2.8 The 10 sites for image capturing and image selection for

P-gp protein expression using Image J analysis software. 83 Figure 3.1 Detailed molecular interaction between digoxin and substrate

binding-site of P-gp. 87

Figure 3.2 Detailed molecular interaction between mitragynine and

substrate binding-site of P-gp. 88

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Figure 3.3 Detailed molecular interaction between quinidine and nucleotide

binding domain (NBD) of P-gp. 92

Figure 3.4 Detailed molecular interaction between mitragynine and

nucleotide binding domain (NBD) of P-gp. 93 Figure 3.5 The cytotoxicity effects of mitragynine and etoposide on

Caco-2 cell line. 95

Figure 3.6 Retention time and chromatogram of tested compound and

substrate using optimized HPLC parameters. 96 Figure 3.7 HPLC/UV chromatograms of complete transport buffer spiked

with compounds and blank complete transport buffer for

selectivity of the method used to quantify mitragynine. 98 Figure 3.8 HPLC/UV chromatograms of complete transport buffer spiked

with compounds and blank complete transport buffer for

selectivity of the method used to quantify digoxin. 99 Figure 3.9 Linear regression data of mitragynine with concentrations

ranged from 0.1-20 µM. 100

Figure 3.10 Linear regression data of digoxin with concentrations

ranged from 0.1-20 µM. 101

Figure 3.11 Optimization of incubation time of the bidirectional assay. 107 Figure 3.12 Bidirectional Papp and ER values of digoxin for both without

and with the presence of the inhibitor (quinidine). 109 Figure 3.13 Papp and efflux ratio (ER) of mitragynine across Caco-2

monolayer cell with digoxin as a control. 111 Figure 3.14 Effects of various concentration of mitragynine on transport

activity of digoxin, a known P-gp substrate with rifampicin

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and quinidine as a control for inducer and inhibitor respectively. 112 Figure 3.15 IC50 determination of the mitragynine for bidirectional assay. 114 Figure 3.16 Detailed on primer blast for primer set of P-gp (ABCB1). 116

Figure 3.17 Representative image of agarose gel electrophoresis to

determine RNA integrity. 118

Figure 3.18 Annealing temperature optimization for amplification of P-gp. 119 Figure 3.19 A representative melt curve plot for amplification of P-gp. 120 Figure 3.20 RT-qPCR amplification efficiency for P-gp, ACTB and GAPDH. 122 Figure 3.21 The effects of rifampicin on the gene expression of P-gp

(ABCB1) after 72 h of treatment. 123 Figure 3.22 The effects of quinidine on the gene expression of P-gp

(ABCB1) after 72 h of treatment. 124 Figure 3.23 The effects of mitragynine on the gene expression of P-gp

(ABCB1) after 72 h of treatment. 125 Figure 3.24 The effects of rifampicin on the protein expression of P-gp

after 72 h of treatment. 128

Figure 3.25 The effects of quinidine on the protein expression of P-gp

after 72 h of treatment. 129

Figure 3.26 The effects of mitragynine on the protein expression of P-gp

after 72 h of treatment. 130

Figure 3.27 Representative images of the z stack image of the Caco-2

cells for immunocytochemistry slide (600x magnification). 132 Figure 3.28 Representative images of the cross section of the Caco-2

cells for immunocytochemistry slide (600x magnification). 133

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Figure 3.29 Graph of relative protein expression of P-gp in Caco-2 cells for the immunocytochemistry results analyzed using

ImageJ software. 135

Figure 3.30 Graph of the percentage number of cells which expressed

P-gp in Caco-2 cells in immunofluorescence. 136 Figure 4.1 Decision tree for substrate determination based on the

FDA (USA) guideline for drug interaction studies. 147 Figure 4.2 Decision tree for inhibitor determination based on

FDA (USA) guideline for drug interaction studies. 149 Figure 4.3 Overview of effects of mitragynine on P-gp. 152

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LIST OF ABBREVIATIONS

2D two-dimensional

ABC ATP binding cassette

ABCB1 ATP binding cassette subfamily B member 1 ABCG2 ATP binding cassette subfamily G member 2

ADMET Absorption, distribution, metabolism, excretion and toxicity ADT AutoDockTools

ALD adrenoleukodystrophy ATP adenosine triphosphate

BCRP breast cancer resistance protein

CAM complementary and alternative medicine cDNA complementary deoxyribonucleic acid

CFTR cystic fibrosis transmembrane conductance regulator CYP cytochrome

DDI drug-drug interaction

ER efflux ratio

FDA Food Drug and Administration

GAPDH Glyceraldehyde 3-phosphate dehydrogenase GCN20 ATP binding cassette subfamily F

HDL high-density lipoproteins HIV human immunodeficiency virus

HPLC high performance liquid chromatography IC50 half maximal inhibitory concentration Ki inhibition constant

LLOQ lower limit of quantification

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xvi LSGGQ ABC signature motif or C motif MDR1 multi drug resistance 1

Mg2+ magnesium ion

mRNA messenger ribonucleic acid

MRP multi-drug resistance associated protein NBD nucleotide binding domain

OABP ATP binding cassette subfamily E member 1 OAT organic anion transporter

OATP organic anion-transporting polypeptide OCT organic cation transporter

Papp apparent permeability PDB Protein Data Bank P-gp P-glycoprotein

QSAR quantitative structure–activity relationship

RM Ringgit Malaysia

RNA ribonucleic acid

RT-qPCR reverse transcription quantitative polymerase chain reaction SD standard deviation

SEM standard error of the mean SLC solute carrier

TAP transporter associated with antigen processing TEER transepithelial electrical resistance

TMD transmembrane domain

Tyr tyrosine

US United States

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xvii US$ United States dollar

UV ultraviolet

v/v volume/volume

w/v weight/volume

WHO World Health Organization

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LIST OF SYMBOLS

α alpha

~ approximately

* asterisk β beta

‒ dash

= equals

> greater than - hyphen

< less than

≤ less-than or equal to

/ or

± plus-minus

® registered trademark

× times

™ trade mark

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LIST OF UNITS

Å Ångström

°C degree Celcius

Da Dalton

g gram (weight per unit mass)

h hour

kcal/mol kilocalorie per mole

µg microgram

µL microliter

µm micrometer

µM micromolar

mL milliliter

mm millimeter

mM millimolar

min minute

M molar

nm nanometer

nM nanomolar

Ω ohm

% percentage

psi pounds per square inch U/mL unit per milliliter

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PENENTUAN MITRAGININA SEBAGAI SUBSTRAT, PENGARUH, ATAU PERENCAT P-GLIKOPROTEIN DAN RAMALAN RISIKO INTERAKSI

DRUG-HERBA

ABSTRAK

P-Glikoprotein (P-gp) adalah protein pengangkut yang banyak terdapat di dalam tisu usus dan berfungsi dengan merembes keluar pelbagai substrat dari sel.

Perubahan terhadap aktiviti, serta gen dan protein P-gp yang disebabkan oleh ubat- ubatan atau sebatian herba akan menjejaskan bioketersediaan ubat yang dimakan dan berpotensi untuk meyebabkan interaksi di antara ubat dan ubat atau ubat dan herba.

Mitragyna speciosa Korth atau Ketum digunakan secara tradisional untuk pelbagai penyakit tetapi disebabkan oleh kesan euforia, tumbuhan ini sering disalahgunakan oleh penduduk tempatan. Walaupun Ketum adalah bahan terkawal di negara-negara Asia, termasuk Malaysia, namun penggunaannya tidak dikawal selia dengan ketat di negara lain. Mitragynine adalah satu komponen bioaktif utama dalam ekstrak mentah Ketum dan keselamatan alkaloid ini dalam menyebabkan interaksi ubat dan herba melalui P-gp masih tidak disiasat sepenuhnya. Oleh itu objektif utama kami adalah untuk menentukan sama ada mitragynine adalah substrat P-gp atau mempunyai potensi untuk merencat atau meningkatkan aktiviti pengangkutan serta ekspresi P-gp di dalam sel kultur Caco-2. Satu kaedah penyaringan in silico, bagi meramal bentuk pengikatan mitragynine kepada P-gp telah dijalankan dengan menggunakan Autodock 4.2 dan seterusnya disahkan dengan menggunakan kaedah in vitro asai pengangkutan dwiarah. Pengoptimuman asai pengangkutan dwiarah telah dijalankan dan semua kompaun dianalisis menggunakan pengesan HPLC/UV dengan teknik elusi isokratik. Kesan mitragynine kepada ungkapan mRNA dan protein P-gp telah

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dijalankan menggunakan optimisasi RT-qPCR, analisis Western blot serta immunofluorescence. Mitragynine tidak bertindak sebagai substrat P-gp berdasarkan kedua-dua simulasi dok molekul dan asai pengangkutan dwiarah. Walau bagaimanapun, mitragynine membentuk ikatan hidrogen dan interaksi hidrofobik dengan P-gp dan didapati menghalang aktiviti pengangkutan oleh P-gp dengan penurunan sebanyak 30% dibandingkan dengan kontrol. Mitragynine didapati merencatkan ungkapan mRNA serta protein P-gp. Pada kepekatan tertinggi, iaitu 10 µM, perencatan ungkapan mRNA dan protein adalah sebanyak 35% dan 40% dan adalah selaras dengan penurunan dalam aktiviti pengangkutan digoxin melalui P-gp.

Oleh itu, mitragynine adalah merupakan perencat P-gp secara in vitro. Rifampicin didapati mengaruh ekspresi protein P-gp setelah dinilai menggunakan kedua-dua analisis Western blot dan imunositokimia. Manakala, quinidine telah didapati merencat P-gp pada tahap transkripsi dan juga aktiviti pengangkutan P-gp.

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DETERMINATION OF MITRAGYNINE AS A SUBSTRATE, INDUCER, OR INHIBITOR OF P-GLYCOPROTEIN DRUG TRANSPORTER, AND

PREDICTION OF DRUG-HERB INTERACTION RISKS

ABSTRACT

P-glycoprotein (P-gp) is a multidrug transporter, mainly expressed in the intestinal tissue as a secretory efflux protein. Changes in the activity, gene and protein expression of P-gp caused by drugs or herbal compounds will affect oral drug bioavailability and may potentially lead to drug-drug or drug-herb interactions.

Mitragyna speciosa Korth or Ketum is traditionally used for various ailments but due to its euphoric effects, this plant is often misused by the local population. Although Ketum is a controlled substance in most Asian countries, including Malaysia, its use is not strictly regulated in other parts of the world. Mitragynine is a major bioactive component in the crude extract of the plant and the safety of this alkaloid causing adverse drug interaction via P-gp has not been fully investigated. Therefore our main objective is to determine if mitragynine is a substrate of P-gp or has the potential to inhibit or induce the P-gp transport activity and expression in Caco-2 cells. An in silico computational method to predict the binding conformation of mitragynine to the substrate binding site as well as the nucleotide binding domain (NBD) of the P- gp was carried out using Autodock 4.2 and further validated using in vitro bidirectional transport assay. Optimization of the bidirectional transport assay was carried out and both mitragynine and digoxin were analyzed using HPLC/UV detector with isocratic elution. The effects of mitragynine on mRNA and protein expression of P-gp were carried out using an optimized RT-qPCR, Western blot analysis and immunofluorescence. Mitragynine is unlikely a P-gp substrate based on

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both the molecular docking simulation and bidirectional transport assay. However, it appears to form hydrogen bonds and hydrophobic interactions with P-gp and was found to inhibit the P-gp transport activity by 30% reduction when compared with control. Mitragynine was found to inhibit mRNA and protein expression of P-gp. For the highest concentration of 10 µM, inhibition of mRNA and protein were approximately 35% and 40% that of the control respectively and were consistent with the decrease in the transport activity of digoxin via P-gp. Thus, mitragynine is a significant in vitro P-gp inhibitor. Rifampicin was only found to significantly induce the protein expression evaluated using both Western blot analysis and immunocytochemistry. Meanwhile, quinidine was found to significantly inhibit the P-gp at the transcriptional level as well as its transport activity.

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1 CHAPTER 1 INTRODUCTION

1.1 Background

Herbal medicine is used by herbalists and indigenous communities to prevent and treat various diseases over years. According to the definition by the World Health Organization (WHO), herbal medicines include herbs, herbal materials, herbal preparations, and finished herbal products that contain parts of plants, other plant materials, or combinations as active ingredients (Nworu et al. 2015). There are more than 35,000 species of plants worldwide which are known and used for medicinal purposes and about 250-500 species of plants that are commonly used in Asian and other countries (Chen et al. 2011). Herbal medicine is part of complementary and alternative medicine (CAM) where it comprises a diverse medical and health care systems, therapies, and products that are not presently considered to be part of conventional medicine (Barnes et al. 2004, Poonthananiwatkul et al. 2015). The usage of complementary and alternative medicine (CAM) has been increased in developing countries including Malaysia, and recently, the usage of CAM has also expanded to developed countries (Aziz and Tey 2009).

The 2012 National Health Interview Survey of the United States reported that, 38.3% of adults and 11.8% of children used herbal medicine and supplements which resulted in total expenditure of $30.2 billion (Black et al. 2015, Clarke et al.

2015). In addition, other studies showed that an approximately 25% of adults in developed countries and more that 80% of the population in most developing

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countries including Malaysia are using herbal medicine either for treatment of disease or as a supplement (Chen et al. 2011, Jayaray 2010, Mukherjee et al. 2011).

From a survey conducted in Malaysia, about 63.9% Malaysian population are practicing and using herbal medicine and supplements. From 2000 to 2005, the annual sales for traditional medicines in Malaysia has increased from US$ 385 million (RM 1 billion) to US$ 1.29 billion (RM 4.5 billion) (Aziz and Tey 2009).

The number of herbal medicine and/or natural products users are increasing worldwide, partly due to the increasing preference for natural therapies and/or preventive medicine (Silvanathan and Low 2015). Rising concerns about the undesirable side effects of conventional medicine and the spreading belief that natural products are safer are known to be the contributing factors (Calixto 2000, Zhang et al. 2015). Other common reasons for herbal medicine consumption include the desire to improve physical and mental symptoms, and quality of life as well as to help deal with the disease and its unpleasant treatment (Poonthananiwatkul et al.

2015). In Malaysia, the popularity of herbal medicine usage among the elderly was associated with its lower cost, a lower rate of side effects, more effective, more natural and better accessibility compared to conventional Western medicines (Mitha et al. 2013, Silvanathan and Low 2015). In addition, the usage of herbal medicine was also relatively high in middle-aged adults. Both patients and the public have been known to use herbal medicines to improve and maintain health, treatment or prevention of minor ailments as well as chronic diseases (Barnes 2003, Chang et al.

2007, Mehta et al. 2007). Among Malaysian adults, being a woman, Malay, suffering from health problem, earning a high income, and having favourable opinions about herbal medicines were significant positive forecasters of use of herbal medicines (Aziz and Tey 2009).

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However, with increasing number of herbal medicine usage, the number of adverse events which occurred after consumption of herbal product as well as herbal product abuse are also increasing. Ingestion of herbal products such as yohimbine (an alkaloid from Pausinystalia yohimbe), maca (Lepidium meyenii), horny goat weed (epimedium sp.), Mitragyna speciosa and Ginkgo biloba were reported to cause modification of the function of central nervous system which leads to changes in psychological behavioral and addiction (Corazza et al. 2014). Several herbal medicines, such as Ma-Huang (Ephedra sinica), kava (Piper methysticum), and chaparral leaf (Larrea divaricate), have been implicated as hepatotoxins where hepatotoxicity may be the most frequent adverse reaction to these herbal remedies when taken in excessive quantities. Other herbal plants such as Aspalathus linearis (red bush tea), Echinacea angustifolia and Valeriana officinalis may also cause hepatotoxicity as well as proved to have effects on coagulation and platelets function (Reddy et al. 2016, Wang et al. 2015).

In Malaysia, the increasing use of herbal plant either for a herbal supplement, herbal medicine or herbal addiction and abuse by the community is of special concern because these herbal preparations are not strictly regulated by the Drug Control Authority (DCA) of Malaysia (Aziz and Tey 2009). The evaluation of the quality and safety of herbal medicines and supplements by the DCA of Malaysia before approval is only limited to control the content of specified adulterants and contaminants such as heavy metals and microorganisms (Aziz 2004, Bas and Oliu Castillo 2016). Thus, there is lack of information on the standard preparation procedure, general effects and its safety information for the herbal medicine to be considered safe for consumption. In addition, the main concern regarding the use of herbal medicine and supplements is the potential for dangerous adverse effects and

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drug-herb interactions, especially when the herbal products were taken simultaneously with conventional medicine (Silvanathan and Low 2015). Hence, it is important to further investigate the safety, quality and therapeutic efficacy of herbal medicine as well as herbal plant derived compound.

1.2 Drug interactions

Drug-drug interaction (DDI) is defined as a pharmacological or clinical response to the administration of two or more drugs that is different from the response they initiate when individually administered (Rodrigues et al. 2015). Drug interactions occur when either pharmacokinetics or pharmacodynamics or both of one drug are altered by the co-administration of another drug. Changes in the pharmacokinetics and pharmacodynamics of one drug will affect the effectiveness of another either by causing treatment failure or toxicity (Chen and Raymond 2006).

Drug interactions usually occur when one of the drug or xenobiotics having properties to interact with the mechanism of action, metabolism or transportation of the other drug. The effect may mimic, magnify or oppose the effect of drugs and usually produce adverse effects (Fugh-Berman 2000). These adverse reactions caused by the concomitant use of drugs or other xenobiotics can potentially lead to severe, and perhaps even life-threatening, adverse reactions. The severity of the adverse reaction can range from theoretical to clinically significant, including prolonged morbidity and even death (Chen et al. 2011, Manzi and Shannon 2005).

In addition, many medicinal herbs and pharmaceutical drugs are therapeutic at one dose and toxic at another especially for drugs with narrow therapeutic indices such as digoxin and warfarin (Chen et al. 2011). Alteration in the pharmacology of those drugs leads to changes in the concentration of the drugs at the site of action producing side effects. Drug interactions are the most common causes for medication

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error in a developed country, with a prevalence of 20-40% which mostly occurred in elderly due to polytherapy (Palleria et al. 2013). Most of the drug interactions are potentiated by the concurrent use of herbals medicine and prescription drugs as identified by case reports and clinical studies worldwide (Chen et al. 2011). An example of DDIs is by co-administration of quinidine, dronedarone or verapamil with edoxaban and it has been found to increase the concentration of the edoxaban and lead to bleeding potential (Mendell et al. 2013). In addition, administration of warfarin together with some known herbs such as cranberry, soya, St John’s wort, and danshen had been found to alter the concentration of warfarin and leading to drug-herb interactions (Ge et al. 2014). Generally, the mechanism for drug interactions is divided into two types, namely pharmacodynamics and pharmacokinetics mechanism of drug interactions as shown in Figure 1.1.

1.3 Pharmacodynamic mechanism of drug interactions

Pharmacodynamics is the study of how drugs have effects on the body (Maxwell 2016, Meibohm and Derendorf 1997). Pharmacodynamics interactions are the result of the effects of combined treatment at the site of action which altered pharmacological actions at standard plasma concentration (Kashuba and Bertino 2005, Palleria et al. 2013). Pharmacodynamic interactions are more difficult to identify and measure than pharmacokinetic interactions since they result in a modification of the pharmacological action of a drug without any change in the plasma concentration (Spina et al. 2016). Pharmacodynamic interactions are divided into three subgroups based on the mechanism either by direct effect at receptor function, interference with a biological or physiological control process, or additive or opposed pharmacological effect (Palleria et al. 2013). The effects of

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Figure 1.1 Generalized mechanistic insight into drug interactions where it can be divided into two based on the mechanism, pharmacokinetics drug interactions and pharmacodynamics drug interactions. Adapted from Underestimating the Toxicological Challenges Associated with the Use of Herbal Medicinal Products in Developing Countries, page 6 (Neergheen-Bhujun 2013).

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pharmacodynamics type of drug interactions can either be synergistic where the combined effects are greater than expected from the sum of individual effects, additive where the effects are equal to the sum of the effects of the individual drugs, or antagonistic where the combined effects are less than additive (Spina and Italiano 2015). The ability of diverse xenobiotics to interact with different receptor sites and alter the physiological environment can also partly explain pharmacodynamic interactions.

1.4 Pharmacokinetic mechanism of drug interactions

Pharmacokinetics interaction is defined as changes in the absorption, distribution, metabolism or excretion of a drug and/or its metabolite(s) after the co- administration of another drug (Spina et al. 2016). These interactions affect the way xenobiotics or drugs are absorbed, distributed, metabolized and excreted, resulting in altered plasma drug concentration (Ge et al. 2014, Spina et al. 2016). Over the past decade, drug metabolism was known as a major contributor in drug interactions.

However, other than metabolism, drug absorption, distribution, and excretion are also shown to have important influences on pharmacokinetics, bioavailability, and consequently therapeutic efficacy of drugs (Faber et al. 2003, Meyer et al. 2015, Muller and Fromm 2011). Both in vitro and in vivo studies have indicated that hepatic or intestinal drug-metabolizing enzymes and drug transporters both equally contribute to the pharmacokinetic interactions (Zhou et al. 2003).

1.4.1 Drug absorption and distribution

Drug absorption refers to the movement of the drug from its site of administration (either via gastrointestinal tract or skin) into the blood circulation.

Once a drug has gained access to the blood circulation, it will be distributed to other

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tissues for any effects to be produced. Drugs absorption can occur via passive diffusion, facilitated diffusion or active transport by protein transporters into the blood circulation before distribution takes place (Artursson et al. 2012, Chillistone and Hardman 2014). For drugs with oral route of administration, absorption occurs in the lower part of the gastrointestinal tract (jejunum and ileum of the small intestine and large intestine) due to the larger surface area of the intestine (Bergström et al.

2014). The absorption process occurs via the enterocytes lining the intestinal tract.

Enterocytes are polarized simple columnar epithelial cells with microvilli on the apical surface of the cells and joined together by tight junctions (Snoeck et al. 2005).

The most common mechanisms of interaction occurring during absorption are an alteration in the active and passive intestinal transport, alteration in the intestinal cytochrome P450 isozyme activity, alteration in the intestinal P-glycoprotein (P-gp) activity, and alteration of gastric pH, gastric emptying, intestinal motility, and intestinal blood flow (Kashuba and Bertino 2005). In addition, absorption across the intestinal membrane is also affected by other transporters on both luminal and basolateral membrane. These transporters can be either influx or efflux type of transporter (Chillistone and Hardman 2014). Other than P-glycoprotein, other drug transporters such as organic anion transporter (OAT), organic cation transporter (OCT) and solute carrier (SLC) transporter which are also abundantly expressed in the drug’s absorption site are responsible for maintaining balanced absorption in the intestine (Tsuji 2002).

1.4.2 Drug metabolism

Drug metabolism and drug excretion represent the detoxification processes that protect the human body from xenobiotics and their toxic metabolites (Leslie et al. 2005). Generally, drug metabolism or biotransformation is a chemical alteration

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of the drug in the body (Peng and Zhong 2015). Liver is the primary site for drug metabolism and this process can be divided into two phases, which are phase I metabolism and phase II metabolism (Konstandi et al. 2014, Nowak et al. 2014).

Hepatic detoxification is generally initiated by the uptake of xenobiotics into liver hepatocytes, by uptake transporter followed by phase I metabolism such as reduction, oxidation, and hydrolysis. Subsequently, phase II metabolism by conjugation processes such as glutathione conjugation, glucuronidation, and sulfation are performed before proceeding with excretions of xenobiotics and/or their metabolites to the bile or through renal excretion (Song et al. 2013).

In drug interactions, potential mechanisms involving metabolism are the genetic polymorphism, inhibition, and induction of enzyme activity (Kashuba and Bertino 2005). Nonrandom genetic modification generates polymorphisms which occurred in at least 1% of a population and give rise to distinct subgroups that differ in their ability to metabolized xenobiotics (Daly et al. 1998). For the inhibition of enzyme activity, there are several mechanisms of inhibition exist such as reversible and irreversible inhibition where reversible is the most common type of enzyme inhibition. Reversible inhibition do not permanently disable the enzyme activity and it occurs when weak bonds were quickly formed between compounds and CYP P450 isozyme (Kashuba and Bertino 2005). This reversible inhibition can occur both competitively and noncompetitively. In addition, there is also reversible inhibition due to the oxidation of inhibitor which forms a slowly reversible reactions (Thummel and Wilkinson 1998). The formation of CYP-mediated reactive metabolite caused irreversible inhibition and this metabolite can covalently and irreversibly bind to the catalytic site residue which permanently inactivate the enzyme (Ho et al. 2015). For

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induction of enzyme activity, it generally happens with an increase in P450 synthesis either by mRNA stabilization or receptor-mediated transcriptional activation.

1.4.3 Drug elimination

Kidneys play an important role in drug excretion. Liver and kidney transporters such as solute carrier (SLC) transporter family and ATP-binding cassette (ABC) transporter family are known to play an important role in excretion and elimination of drugs and other foreign substances from the body (Le Vee et al. 2015).

Generally, elimination can occur via tubular secretion, glomerular filtration, or a combination of both pathways. Recently, the role of these transporters in the excretion of drugs have drawn major attention because of their involvement in drug interactions (Moss et al. 2014). SLC transporter family can be subdivided into cationic transporters, anionic transporters, and other transporters. These SLC transporters family are expressed in both apical and basolateral membrane of the proximal tubule cells and control the entry of xenobiotics into the epithelial cells (Morrissey et al. 2013). Meanwhile, ATP-binding cassette (ABC) transporter help to eliminate and excrete xenobiotics and endogenous compounds across the proximal tubule cells in kidney, the apical membrane of hepatocytes, capillary endothelial cells at the blood-brain barrier as well as the brush border membrane of enterocytes (Giacomini et al. 2010, van Montfoort et al. 2003).

There are five potential mechanisms of drug interactions affecting excretion at the site of renal elimination (Bonate et al. 1998). The three most common mechanisms are glomerular filtration, tubular secretion, and tubular reabsorption.

Changes in renal blood flow, cardiac output, and extend of protein binding will affect rates of glomerular filtration which disturb the normal excretion process (Kashuba and Bertino 2005). However, the most common renal drug interactions occur at the

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transport site of tubular secretion. Many organic anions and cationic drugs and metabolites compete with each other for secretion as they are sharing the same proximal tubular active transport system. In addition, inhibition of renal P-gp which has been identified in the apical membrane of the proximal tubule leads to an increase in plasma drug concentrations and potentially contribute to significant drug interactions. In tubular reabsorption, changes in the urinary pH can alter the reabsorption process but these interactions are not known to be clinically significant.

1.5 Membrane transporter

As discussed earlier, transporters and drug metabolizing enzymes are two major components, playing an important role in pharmacokinetics drug interactions (Wu et al. 2016). While many researches have been focused on the role of drug metabolizing enzymes in drug interactions, less emphasis has been placed on the importance of transporter in drug interactions. Transporters mostly involve in the absorption, distribution and elimination of xenobiotics either into or outside of the cells, whereas drug metabolizing enzymes are mostly involved in the metabolism process (Scherrmann 2009). The major physiological functions of transporters are to facilitate the transfer of nutrients or endogenous substrate across the cell membrane, such as endogenous metabolites and signaling molecules. There are two main transporter superfamilies, namely SLC and ABC transporters and both are involved in transporter-mediated drug interactions (Giacomini et al. 2010). SLC transporters comprise of facilitated and ion-coupled transporters, including organic cation transporters (OCTs), organic anion transporters (OATs) and organic anion- transporting polypeptides (OATPs), where most of the SLC transporters mediate uptake of substrates into the cells (Koepsell 2013, Wessler et al. 2013). On the other

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hand, ABC transporters, including P-glycoprotein (P-gp or MDR1), breast cancer resistance protein (BCRP or ABCG2), and multi-drug resistance associated proteins (MRPs), are considered to be responsible for efflux of xenobiotics where they rely on ATP to actively pump their substrate across cell membranes (Leslie et al. 2005).

These specific uptake and efflux transporters are extensively expressed in the apical and luminal membrane of epithelia of many organs as shown in Figure 1.2 (Giacomini et al. 2010, Sai 2005). Their expression in cells of all of these major barriers such as intestine, blood-brain barrier as well as in metabolic organs such as liver (hepatocytes) and kidney (kidneys proximal tubules) also explains their influence on the pharmacology properties of drugs and drugs candidates (Estudante et al. 2013, Montanari and Ecker 2015). Among all the protein transporters, ABC transporters especially P-gp has drawn major attention for its great influence on drug resistance and drug interactions problem (Hennessy and Spiers 2007, Li et al. 2014).

1.6 ABC transporter superfamily

The ATP-binding cassette (ABC) transporters form a large superfamily of membrane proteins which are responsible for various functions, including the active transportation of ions and peptides, excretion of harmful compounds, and cell signaling (Leslie et al. 2005). There are more than 100 membrane transporters/channels in the ABC transporter superfamily and they are universally expressed in all living organisms ranging from prokaryotes to mammals (Hennessy and Spiers 2007, Montanari and Ecker 2015). In humans, 49 ABC transporters have

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Figure 1.2 Various distribution of protein transporter in the membrane of cells in the a) intestine, b) liver, c) kidney, and d) brain are shown. Arrows represent the direction of substrate transport for each transporter.

Orange circles: key drug transporters mentioned in both US FDA draft guidance and EMA guideline on DDIs (Giacomini et al. 2010, Maeda and Sugiyama 2013).

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been identified, and organized into 7 subfamilies: ABCA (12 members; previously ABC1), ABCB (11 members; previously MDR/TAP), ABCC (13 members;

previously MRP/CFTR), ABCD (4 members; previously ALD), ABCE (1 member;

previously OABP), ABCF (3 members; previously GCN20) and ABCG (5 members;

previously White) (Table 1.1) (Dean and Allikmets 2001, Dean et al. 2001, Vasiliou et al. 2009). These ABC transporters consist of several core domains (transmembrane domains and intracellular nucleotide binding domains) depending on different subfamilies. The nucleotide binding domains (NBDs) are usually well conserved across subfamilies while transmembrane domains (TMDs) are less conserved and possibly account for substrate specificity of the different transporters. In addition, these TMDs form the translocation chamber across the transporter which explained the ability for their substrate to be transported (Tarling et al. 2013).

Generally, the TMD of ABC transporters consists of few membrane spanning segments (α-helices) separates by hydrophilic loops and intracellular NBD (Kast et al. 1995, Loo and Clarke 1995). In each NBDs, two sequence motifs known as Walker A and Walker B which located 100-200 amino acids apart, are conserved among all ABC transporter superfamily members, as well as numerous other ATP- binding proteins (Walker et al. 1982). The lysine residue in the Walker A motif is involved in the H-bonding with the ATP while the aspartic acid residue in the Walker B motif interacts with Mg2+ (Hung et al. 1998, Sharom et al. 1999). In addition, another highly conserved amino acid sequence, ABC signature motif or C motif (ALSGGQ) which located between the Walker A and B motifs, as well as the D,H, Q, and A loops were known to have implication in the recognition, binding, and hydrolysis of ATP. Several of these motifs shown to interact with the adenine ring of ATP and appear to form part of the ATP-binding site (Loo et al. 2002).

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Table 1.1 Human ABC transporter genes, and their functions (Dean et al. 2001).

Gene Chromosome

location Exons AA Accession

number Function

ABCA1 9q31.1 36 2261 NM005502 Cholesterol efflux onto HDL

ABCA2 9q34 27 2436 NM001606 Drug resistance

ABCA3 16p13.3 26 1704 NM001089 Multidrug resistance

ABCA4 1p22 38 2273 NM000350

N-retinylidene-

phosphatidylethanolamine (PE) efflux

ABCA5 17q24.3 31 1642 NM018672

Urinary diagnostic marker for prostatic

intraepithelial neoplasia (PIN)

ABCA6 17q24.3 35 1617 NM080284 Multidrug resistance ABCA7 19p13.3 31 2146 NM019112 Cholesterol efflux ABCA8 17q24 31 1581 NM007168 Transports certain

lipophilic drugs

ABCA9 17q24.2 31 1624 NM080283

Might play a role in monocyte

differentiation and macrophage lipid homeostasis

ABCA10 17q24 27 1543 NM080282 Cholesterol-responsive gene

ABCA12 2q34 37 2595 NM173076 Has implications for prenatal diagnosis ABCA13 7p12.3 36 5058 NM152701 Inherited disorder

affecting the pancreas ABCB1 7q21.1 20 1280 NM000927 Multidrug resistance ABCB2 6p21.3 11 808 NM000593 Peptide transport ABCB3 6p21.3 11 703 NM000544 Peptide transport

ABCB4 7q21.1 25 1279 NM000443 Phosphatidylcholine (PC) transport

ABCB5 7p15.3 17 812 NM178559 Melanogenesis

ABCB6 2q36 19 842 NM005689 Iron transport

ABCB7 Xq12-q13 14 753 NM004299 Fe/S cluster transport

ABCB8 7q36 15 718 NM007188

Intracellular peptide trafficking across Membranes

ABCB9 12q24 12 766 NM019625 Located in lysosomes ABCB10 1q42.13 13 738 NM012089 Export of peptides derived

from proteolysis of inner- membrane proteins ABCB1 2q24 26 1321 NM003742 Bile salt transport ABCC1 16p13.1 31 1531 NM004996 Drug resistance ABCC2 10q24 26 1545 NM000392 Organic anion efflux

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16 Table 1.1 Continued

Gene Chromosome

location Exons AA Accession

number Function

ABCC3 17q22 19 1527 NM003786 Drug resistance ABCC4 13q32 19 1325 NM005845 Nucleoside transport ABCC5 3q27 25 1437 NM005688 Nucleoside transport ABCC6 16p13.1 28 1503 NM001171 Expressed primarily in

liver and kidney

ABCC7 7q31.2 23 1480 NM000492

Chloride ion channel (same as CFTR gene in cystic fibrosis) ABCC8 11p15.1 30 1581 NM000352 Sulfonylurea receptor

ABCC9 12p12.1 32 1549 NM005691

Encodes the regulatory SUR2A subunit of the cardiac Kþ(ATP) channel

ABCC10 6p21.1 19 1464 NM033450 Multidrug resistance ABCC11 16q12.1 25 1382 NM033151 Drug resistance in breast

cancer

ABCC12 16q12.1 25 1359 NM033226 Multidrug resistance

ABCC13 21q11.2 6 325 NM00387

Encodes a polypeptide of unknown

Function

ABCD1 Xq28 9 745 NM000033

Very-long-chain fatty acid (VLCFA)

Transport

ABCD2 12q11-q12 10 740 NM005164

Major modifier locus for clinical diversity

in X-linked ALD (X- ALD)

ABCD3 1p22-p21 16 659 NM002858

Involved in import of fatty acids and/or

fatty acyl-coenzyme As into the

peroxisome

ABCD4 14q24 19 606 NM005050 May modify the ALD

phenotype

ABCE1 4q31 14 599 NM002940 Oligoadenylate-binding protein

ABCF1 6p21.33 19 845 NM001025

091

Susceptibility to

autoimmune pancreatitis

ABCF2 7q36 14 634 NM005692

Tumour suppression at metastatic sites and in endocrine pathway for breast cancer/

drug resistance

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17 Table 1.1 Continued

Gene Chromosome

location Exons AA Accession

number Function

ABCF3 3q27.1 21 709 NM018358

Also present in

promastigotes (one of five forms in the life cycle of trypanosomes)

ABCG1 21q22.3 13 678 NM004915 Cholesterol transport

ABCG2 4q22 16 655 NM004827 Toxicant efflux, drug

resistance

ABCG4 11q23.3 15 646 NM022169 Found in macrophage, eye, brain and spleen

ABCG5 2p21 11 651 NM022436 Sterol transport

ABCG8 2p21 10 673 NM022437 Sterol transport

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18 1.7 P-glycoprotein (P-gp)

1.7.1 Background and structure of P-gp

P-glycoprotein (P-gp) is one of the drug transporters that play an important role in the pharmacokinetics of drugs or xenobiotics. It is a 170 kDa (~170-180 kDa) polypeptide consisting of approximately 1280 amino acids (Chen et al. 1986, Miyata et al. 2016). P-gp is a multidrug transporter and one of the members of the ABC (ATP-binding cassette) superfamily encoded by the MDR1 gene in human which is now known as ABCB1 (Hennessy and Spiers 2007). Since P-gp is one of ABC transporter, the basic units of P-gp consists of two units of TMDs and two units of NBDs as depicted in Figure 1.3. In addition, it appears that P-gp is generated by a gene duplication event, fusing two related half molecules (van Veen et al. 2000).

Each half molecules consists of one unit of TMD and one unit of NBD (Miyata et al.

2016). Generally, the two homologous halfs of the protein were connected by a central sequence known as the “linker” region. The two half share 43% sequence identity and 78% similarity (Grandjean-Forestier et al. 2009).

The TMD unit was made up of six transmembrane segments where each segment is connected by extracellular or cytosolic loops as shown in Figure 1.3b.

The last cytosolic loop was then, followed by a large cytosolic domain containing an ATP-binding site or NBD where the first half is NBD1 and the second half is NBD2 (Dean et al. 2001, Silva et al. 2015). Furthermore, the secondary structure of P-gp shows that it consists of approximately 32-43% α-helix, 16-26% β-sheet, 15-29% β- turn and 13-26% unordered structure (Dong et al. 1998, Sonveaux et al. 1996).

In P-gp, two TMDs units constitute the drug transport pore while, the NBDs bind and hydrolyze ATP to provide energy for the movement of its substrates across membranes (Wessler et al. 2013). For efficient ATP hydrolysis, there is evidence that

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the two NBDs have to interact by forming a sandwich dimer so that the LSGGQ motif of one NBD comes into contact with the loop of the other NBD to form the nucleotide-binding pocket (Leslie et al. 2005). The linker region also plays a role in P-gp function by creating flexible secondary structure. This flexibility is sufficient for the coordinate functioning of both halfs of P-gp, which are likely required for the proper interaction of the two ATP-binding sites (Grandjean-Forestier et al. 2009).

In normal cells expressing P-gp, this protein is synthesized in the endoplasmic reticulum as a core glycosylated intermediate with a molecular weight of 150 kDa before subsequently modified in the Golgi apparatus prior to export to the surface of the cell (Grandjean-Forestier et al. 2009). P-gp protects the cells from xenobiotics and toxins by pumping them out from the cells. The efflux of the drug helps in preventing it from reaching the systemic circulation (Vaalburg et al. 2005).

P-gp is mainly expressed at the apical (luminal) side of the epithelial cells of the intestine (enterocytes), in the brain capillary endothelial cell of the blood brain barriers, renal proximal tubular cells, hepatocytes, blood-testis barrier in testis as well as in placental fetal-maternal barrier (Figure 1.4).

Generally, P-gp works in two steps where the first is a catalytic cycle of ATP hydrolysis, while second is the movement of the substrate from the cytoplasmic side to the extracellular side of the membrane (Grandjean-Forestier et al. 2009). In normal state, the P-gp pore opens towards the cytoplasm of the cells with both NBDs and TMDs open inward as shown in Figure 1.5. The substrate from the cytoplasm will bind to the substrate binding-site located within the cytoplasmic membrane leaflet (Higgins and Gottesman 1992). Then, low-affinity binding of ATP to both

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Figure 1.3 Basic units of P-gp which consist of two related half molecules (each molecules consists of one unit of TMD and one unit of NBD). a) Transport cycle for substrate efflux pumped by P-glycoprotein (substrates are colored red and ATP is magenta) b) Topological model of P-gp, showing the two homologous halfs, each with one transmembrane domain (TMD), containing six highly hydrophobic transmembrane α-helices, and one nucleotide binding domain (NBD) located on the cytoplasmic side of the membrane (Chen et al. 2012).

a)

b)

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Figure 1.4 Localization of P-gp in various organs of human (Borst and Schinkel 2013).

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NBDs will induce the formation of a putative nucleotide sandwich dimer which drive the transportation process (Hennessy and Spiers 2007). At this stage, both the TMDs and NBDs are closed inward and catalysis of ATP into ADP and phosphate occurs.

Subsequently, the TMDs open outward allowing the substrate to be transported to the extracellular space (Wu et al. 2016). Finally, P-gp transforms back to its normal conformation releasing the ADP and phosphate.

1.7.2 Substrates of P-gp

Due to its extreme broad substrate specificity (poly-specificity or promiscuity) in P-gp, it can actively transport a plethora of substrates compounds with varying size and structure out of the cells (Montanari and Ecker 2015, Pan et al.

2016). P-gp is unique in its ability to recognize and transport its substrates that differ considerably in chemical structure and pharmacological action, including many clinically important agents. In earlier studies, P-gp is known to plays a role in multiple drug resistance especially in cancer therapy (Januchowski et al. 2016).

Many of these anti-cancer drugs that are important in managing the cancer patients such as doxorubicin, and daunorubicin were known to be a P-gp substrate (Al-Saraf et al. 2016). Other than these two anthracyclines, P-gp can also transport other anti- cancer drugs such as vinblastine, vincristine, actinomycin D, paclitaxel, teniposide, and etoposide (Hennessy and Spiers 2007).

Other therapeutic drugs such as HIV protease inhibitors (maraviroc), gastrointestinal agents (loperamide, ondansetron) as well as rheumatologic or immunosuppressant agents (cyclosporine, tacrolimus) were found to be transported

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Figure 1.5 Mechanism for transportation of substrate via P-gp (Wu et al. 2016)

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by P-gp (Alam et al. 2016, Mendes et al. 2009, Wagner et al. 2001). In addition, antimicrobial agents such as erythromycin, as well as anti-helminthic agent such as ivermectin, were also known to be a P-gp substrates (Griffin et al. 2005, Takano et al. 1998). Neurologic agents which are used in treating pain in post-herpetic neuralgia as well as for local analgesia such as lidocaine are also transported by P-gp (Funao et al. 2003, Wessler et al. 2013). Interestingly, there is rising concern on the roles of P-glycoprotein in cardiovascular as these cardiac agents are found to interact with P-gp (Wessler et al. 2013). For example, antiarrhythmic agents such as digoxin and verapamil which are indicated for congestive cardiac failure and cardiac arrhythmia are known as P-gp substrates (Hansen et al. 1997, Römermann et al.

2013, Tuncok et al. 1997). P-gp can also transports anticoagulant agents such as dabigatran, edoxaban and warfarin as well as antiplatelet agents such as clopidogrel and ticagrelor (Chen et al. 2016, Mendell et al. 2011, Wessler et al. 2013). In addition, statins such as lovastatin and atorvastatin have been found to be transported by P-gp and co-administration of any P-gp inhibitor will affects its bioavailability (Goard et al. 2010). P-gp can also transport talinolol, an antihypertensive agents used for treatment of hypertension and to manage cardiac arrhythmias (Eyal et al. 2009, Nguyen et al. 2014). Other than these therapeutic drugs, plant crude extract as well as its natural compound such as berberine which is an alkaloid extracted from Berberis vulgaris is also proved to be transported by P-gp (Gozalpour et al. 2014).

1.7.3 Inhibitor and inducer of P-gp

Some compounds and xenobiotics are found to interact with P-gp by causing inhibition or induction. For example, antimicrobial agents such as ketoconazole and erythromycin produce inhibitory effects on P-gp transport activity (Stappaerts et al.

2013). Tariquidar, an anti-cancer agent which is known as P-gp substrate is also

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found to act as P-gp inhibitor (Loo and Clarke 2014). Oral amiodarone and quinidine inhibit intestinal P-gp membrane efflux causing increased plasma concentration of P- gp substrate (Fromm et al. 1999, Robinson et al. 1989). In addition, dronedarone, another antiarrhythmic agents, displays an even greater inhibition on the P-gp transport activity compared to amiodarone (Vallakati et al. 2013). Other than antiarrhythmic agents, calcium-channel blockers such as nicardipine, verapamil, nifedipine and diltiazem inhibit the P-gp mediated transportation of P-gp substrate (Cavet et al. 1996, Takara et al. 2002). Preliminary evidence suggests that warfarin, an oral anticoagulant may inhibit P-gp activity in liver cells. Other than these therapeutic drugs, other xenobiotics such as propiconazole which commonly used on fruits and vegetables as an agricultural fungicide was shown to inhibit the P- glycoprotein transport activity (Mazur et al. 2015). P-gp was also found to be inhibited by spinosad, an oral flea insecticide and was suggested as the underlying cause of the drug interactions with ivermectin (Schrickx 2014). For instance, sinapine which is a small molecular alkaloid extracted from the seeds of cruciferous vegetable (traditional Chinese medicine) plays an important role in downregulation of P-gp expression in tumors (Guo et al. 2014). Another alkaloid compound from gum resin of Commiphora mukul (guggulsterone) also showed inhibition potential of cyclooxygenase-2 by downregulating the P-gp expression and was suggested to be used to reverse the imatinib-resistance problem (Xu et al. 2014).

On the contrary, some of these conventional drugs as well as other xenobiotics also act to induce the P-gp activity and might also induce its expression.

Rifampicin which is used for treatment of several types of bacterial infections especially tuberculosis and leprosy, upregulate as well as inducing P-gp transport activity. Digoxin which is also known as P-gp substrate, also act to induce both the

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