SCHOOL OF CHEMICAL AND LIFE SCIENCES

Diploma in Biotechnology

AY2011/2012

Assay Virtual Screening Compounds for the Inhibitory Potencies against BACE 1

CLS-12A154

A Report

Submitted by

Samuel Chen Angjie 1011195

Anselm Joachim Yap Pun Shern 1011140

Leong Yun Zen Ben 1011351

In partial fulfilment of the requirements for the Diploma in Biotechnology

January 2013

Project Supervisor: Mr Xu Weijun

Project Co-supervisor: Dr Ong Chye Sun

i

I Acknowledgement

We would like to express our sincere gratitude to our project supervisor, Mr. Xu Wei Jun, for

his perpetual guidance and supervision throughout the project. His encouragement and insight

in drug discovery aided us in times of uncertainty. We would also like to spread our

appreciation to Dr. Ong Chye Sun and Mr. Goh Tong Hng for their positive feedbacks and

continuous support. Our gratitude also extends to Mr. Wang Bao Shuang for sharing his

knowledge on dilution of the BACE1 assay kit. Furthermore, we would like to give special

thanks to Ms Jing Wan from the Centre of Biomedical and Life Sciences for her technical

support. Lastly, we would also like to thank Ms Sun Wei and Ms Ye Song for their help in

providing us with the necessary laboratory resources for our experiments.

ii

II Abstract

Alzheimer’s disease is progressively becoming common, and thus is a growing concern. The

disease is characterised by aggregates of amyloid beta (Aβ) peptides into plaques and the

initial step in their formation is catalysed by an aspartyl protease beta-secretase 1 (BACE1).

Herein we describe the measurement of the inhibitory properties of ten organic chemical

compounds against BACE1using a fluorescence resonance energy transfer (FRET) method

for their IC50, followed by a toxicology assay on an in vitro cell model SH-SY5Y using the

tetrazolium colorimetric assay (MTT) method. Structure-activity relationship (SAR) of the

compounds was subsequently analysed and discussed in detail. Six compounds showed

potent micro-molar inhibition of BACE1 and some of them exhibited low cytotoxic effects

on SH-SY5Y cells. Encouragingly, compound 7 posseses an IC50 of 4.49 µM in BACE1

enzymatic assay and exerted no toxic effect on SH-SY5Y cells even at 10 µM. Results from

this project suggest that the structural skeleton of the compounds may be novel

pharmacophore for developing drug leads against Alzheimer’s disease.

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III Table of Contents

Section Page

I Acknowledgements i

II Abstract ii

III Table of Contents iii

IV List of Abbreviations vi

V List of Illustrations viii

1. Introduction 1

2. Literature Review 6

2.1. Alzheimer’s disease (AD) 6

2.2. Hallmarks of AD 7

2.2.1. Neurofibrillary tangles 7

2.2.2. Senile plaques 8

2.3. Stages of AD 10

2.4. Risk factors of AD 11

2.4.1. Genetics 11

2.4.2. Aging 12

2.4.3. Vascular impairment in the brain 12

2.4.4. Hypoxia 12

2.4.5. Gender 13

2.5. AD as a major health issue 13

2.6. Therapeutic strategies against AD 14

iv

2.7. Localization and Expression of BACE1 15

2.8. Regulation of BACE1 16

2.9. Active Site of BACE1 17

2.10. Role of BACE1 in Aβ formation 18

2.11. β peptide 20

2.12. Role of blood-brain barrier (BBB) 21

2.13. Cytotoxicity Assay 22

2.14. MTT Assay 23

3. Materials and Methods 23

3.1. Initial screening: Percentage Inhibition of compounds at 3 µM 23

3.2. The IC50 assay 25

3.2.1. Positive Control 26

3.3. Toxicological Study 27

3.3.1. Cell Culture 27

3.3.2. 3-[4, 5-dimethylthiazol-2-yl]-2, 5-diphenyltetrazolium bromide (MTT)

assay

31

3.3.2.1. Preparation of MTT assay reagent and assay buffer 31

3.3.2.2. The determination of Cell Number required for MTT Assay 32

3.3.2.3. Toxicological Assay 32

4. Results 33

4.1. Enzyme Kinetics Assay 33

4.1.1. Initial Screening: Percentage Inhibition of compounds at 3 µM 33

4.1.2. IC50 assay 36

v

4.1.3. Structure-activity relationship (SAR) study 39

4.2. Toxicological study 40

4.2.1. The determination of Cell Number required for MTT Assay 40

4.2.2. MTT assay 41

5. Discussion 42

5.1. Enzyme-based assay 42

5.2. Toxicological Assay 46

5.2.1. Cell Culture 46

5.2.2. Challenges faced during culturing SH-SY5Y 51

5.2.2.1. Fungal Contamination 51

5.2.2.2. Unusual morphological conformations of SH-SY5Y cells 51

5.2.2.3. High confluence 52

5.2.2.4. Enumeration of cells 52

5.2.3. The determination of Cell Number required for MTT Assay 52

5.2.4. MTT assay 54

6. Conclusion 58

7. References 59

7.1. Websites 68

7.2. Softwares 69

8. Appendix 69

8.1. Compounds analysed in initial screening and IC50 assay 69

vi

IV List of Abbreviations

AD Alzheimer's disease

Aβ, Aβ40, Aβ42 Amyloid beta, Amyloid beta with 40 amino acids, Amyloid

beta with 42 amino acids

APP Amyloid precursor protein

BACE1, BACE2 Beta-secretase 1, Beta-secretase 2

CTF99 Carboxy-terminal fragment 99

CTF Carboxy-terminal fragment

IC50 Half-maximal inhibitory concentration

VHTS Virtual high throughput screening

HTS High throughput screening

SAR Structure-activity relationship

BBB Blood-brain barrier

PK Pharmacokinetics

MCI Mild cognitive impairment

PS1 Presenilin 1

PS2 Presenilin 2

DNA Deoxyribonucleic acid

TGN Trans-Golgi network

mRNA Messenger ribonucleic acid

N Amino

ROS Reactive oxygen species

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HIF-1 Hypoxia-inducible factors

JNK c-jun N-terminal kinase

ASP2 Aspartyl protease 2

TACE Tumour necrotic factor-α converting enzyme

AICD APP intracellular domain

ADAM Disintegrin and metalloprotease domain protein-9

HIV Human immunodeficiency virus

LDH Lactate dehydrogenase

MTT 3-[4, 5-dimethylthiazol-2-yl]-2, 5-diphenyltetrazolium

bromide

NADH Nicotinamide adenine dinucleotide

NADPH Nicotinamide adenine dinucleotide phosphate

DMSO Dimethyl sulfoxide

SEM Standard error of mean

PSA Polar Surface Area

MDR1 P-glycoprotein

MDCK Madin-Darby Canine Kidney Cell

ROF Lipinski’s Rule of Five

ELISA Enzyme-linked immunoabsorbent assay

viii

V List of Illustrations

List of figures

Figure Page

1 A 3D model of BACE1 (PDB code: 1M4H) depicts the interaction

between the inhibitor and the active site of BACE1.

2

2 The template compound, showing regions of it interacting with the

sub-sites of BACE1’s active site.

5

3 The molecular model of compound 9 and the amino acid to inhibitor

interactions.

6

4 Image of neurofibrillary tangles in Alzheimer's disease. 8

5 Production of Aβ40 and Aβ42 by enzymatic function of BACE1 and

gamma-secretase on amyloid precursor protein (APP).

8

6 Microscopic evaluation of the cerebral cortex with a silver stain in a

patient with Alzheimer's disease demonstrating “senile plaques”

with neuronal degeneration.

10

7 APP metabolism by the secretase enzymes: BACE1cleaves before

gamma-secretase in the amyloidogenic pathway.

20

8 Layout of the 96-well plate of our enzyme kinetics assay

experiment.

24

9 The layout of the 96-well plate. 26

10 A schematic of the proportions of the guide lines used to determine

the cell count and therefore the cell number per millilitre.

31

11 BACE1 initial screening results of compounds at 3 µM. 36

12 The % viability of SH-SY5Y against compounds at 10, 5 and 2.5

µM.

42

ix

13 200X microscopic view of SH-SY5Y cells. Day 1. 47

14 100X microscopic view of SH-SY5Y. Day 4. 48

15 100X microscopic view of SH-SY5Y. Day 38. 49

16 100X microscopic view of SH-SY5Y. Day 59. 50

17 100X microscopic view of SH-SY5Y. Day 63. 51

18 Vial B inside a T-25 flask with 5 mL of media in 5% CO2 53

19 Vial C inside a T-25 flask with 5 mL of media in 5% CO2 53

20 The cells from vial A, taken approximately at the same time as vials

B and C after thawing.

54

List of tables

Table

1 The positions of each concentration of the inhibitors. Triplicates

were done for each concentration.

26

2 The SAR of substitution patterns of R and X. 36

3 Percentage inhibition values from 10 to 0.08 µM of compounds 1, 4,

7, 8, 9 and 10 on BACE1.

37

4 The IC50 values of the compounds tested, arranged by the most

potent compound in terms of IC50 from top to bottom.

39

5 Comparisons between the cell number after 3 days of the two

experimental initial cell number of 104 cells and 10

5 cells.

40

6 The relationship between the compounds at concentrations of 10, 5

and 2.5 µM and SH-SY5Y percentage viability with an initial cell

concentration of 5 x 104 cells per well.

41

7 The experimental numerical designations of the individual

compounds tested in this experiment.

69

x

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1. Introduction

Alzheimer's disease (AD) is a neurodegenerative disease that increases in incidence for those

who are of age 65 and older. According to a study published by the United Nations, under the

mortality conditions projected for the period 2045 - 2050, approximately 7 of every 8

newborns would survive to age 60, and more than half to age 80. This makes AD more

common in the future, and thus is a growing concern (Brookmeyer, Johnson et al. 2007).

Accumulation of amyloid beta (Aβ) in plaques is one of the main pathological features of

AD. Aβ plaques are protein aggregates of Aβ and causes neuronal dysfunction, inflammation,

appearance of neurofibrillary tangles, and neuronal loss if they continue to grow. This

cascade plays a central role in pathogenesis of AD and is commonly referred to as the

amyloid hypothesis (Hardy et al., 2002). Considerable evidence shows that Aβ production is

important to the process of brain deterioration in AD (Hardy et al., 2002).

Aβ is produced by sequential cleavage of amyloid precursor protein (APP) by BACE1 (beta-

secretase 1). BACE1 is a potential drug target to delay the progression of the disease because

the enzyme catalyses the first step in Aβ production (John et al., 2003). Other possible targets

are BACE2 and gamma-secretase, although BACE2 is present in mostly in the kidney

(Bennett et al., 2000), less in the brain compared to BACE1 (Ahmed et al., 2010) and

gamma-secretase cleaves Notch protein, a substrate that plays an important role in cellular

differentiation. Inhibitors of gamma-secretase were also shown to produce carboxy-terminal

fragment 99 (CTF99), which was toxic to cells (Kammesheidt et al., 1992), raising safety

issues.

Developing potent BACE1 inhibitors in a hope to identify suitable AD drug candidates has

been fiercely pursued for the past decade. Several strategies of drug discovery have been

explored in the search for potent BACE1 inhibitors, e.g. substrate-based design, high-

throughput screening, and fragment-based lead generation approaches. In the following text,

we will briefly review the history and current preclinical situations of BACE1 inhibitors

being developed by these different approaches.

Substrate-based methods have often been used as the starting point for developing aspartyl

protease inhibitors. P10–P4’ by StatVal was the first substrate-based BACE1 inhibitor and

was developed by Elan Pharmaceuticals in order to purify BACE1 from human brain

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homogenates. This non-peptidomimetic inhibitor is a P1 (S)-statine substituted substrate

analogue with an in vitro half-maximal inhibitory concentration (IC50) of 30 nM.

Shortly after the molecular cloning of BACE1, Tang (Oklahoma Medical Research

Foudation) and Ghosh (University of Illinois at Chicago/Purdue University) teamed up and

reported the inhibitor OM99-2 and the crystal structure of BACE1 with OM99-2 bound to its

active site. While OM99-2 exhibited excellent inhibitory potency in vitro (Ki = 1.6 nM), its

bulky non-peptidomimetic structure prevented its application in vivo. Nonetheless, the

BACE1/OM99-2 co-crystal structure provided promising molecular insight into the ligand

binding interactions with the enzyme active site and significantly advanced the BACE1

inhibitor design.

Figure 1: A 3D model of BACE1 (PDB code: 1M4H) depicts the interaction between the inhibitor and

the active site of BACE1. The nonpeptidomimetic inhibitor is colored in white. This model was

generated from PyMOL, version 1.5.

In parallel, Kiso’s group (Kyoto Pharmaceutical University) developed their own BACE1

inhibitor KMI-008 (IC50 = 413 nM). Further chemical modification of KMI-008 yielded more

potent BACE1 inhibitors KMI-420 (in vitro IC50 = 8.2 nM) and KMI-429 (in vitro IC50 = 3.9

nM). KMI-429 appears to significantly reduce brain Aβ peptide production when directly

injected into the hippocampus of both wild-type mice and APP transgenic mice.

3

In this juncture, various substrate-based peptidomimetic inhibitors were also developed by

large pharmaceutical companies and other academic research groups. Although these

peptidomimetic BACE1 inhibitors were highly potent in vitro, their poor drug properties or

pharmacokinetics (PK), i.e. high molecular weight, poor brain permeability, short half-life in

vivo, and low oral availability, have made them unsuitable drug candidates. However, using

structure-based approach as a guide, these first-generation inhibitors have laid the foundation

for the rational design of later generations of smaller, peptidomimetic BACE1 inhibitors with

better drug-like properties.

Encouragingly, GlaxoSmithKline reported the first orally available BACE1 inhibitor

GSK188909, a small peptidomimetic compound developed from substrate-based design,

displayed a IC50 value of 5 nM and showed excellent selectivity over other aspartic proteases.

When orally administered in vivo (in TASTPM mice), it effectively reduced brain Aβ peptide

levels. Subsequently, Schering-Plough also reported an orally effective 4-

phenoxypyrrolidine-based BACE1 inhibitor named compound 11 with good PK and

selectivity (Ki = 0.7 nM, cellular IC50 = 21 nM).

The most exciting news in the race of BACE1 drug discovery was the emergence of

CoMentis’ CTS-21166 (cellular IC50 = 1.2–3.6 nM), which is the only BACE1 inhibitor that

has passed Phase I clinical trial so far. It possessed excellent properties in brain penetration,

selectivity, metabolic stability, and oral availability; meeting the requirements of an ideal oral

drug candidate.

When administered via intraperitoneal injection (4 mg/kg over six weeks) into an APP

transgenic mouse, the drug reduced brain Aβ levels by over 35% and plaque load by 40%.

The data from human Phase I studies suggested that this compound appeared safe at a dose as

high as 225 mg. Following this, several companies such as Merck, Eli Lilly, and Takeda are

also considering Phase I human testing with their own BACE1 inhibitors. Interesting clinical

data will likely be available for these inhibitors in the near future (Luo and Yan, 2010).

As mentioned above, generation of nonpeptidomimetic compounds with low nanomolar IC50

potencies are being extensively studied (Durham and Shepherd, 2006). Although initial drug

development efforts with peptidomimetic BACE1 inhibitors were encouraging, BACE1 has

since proven to be a challenging medicinal chemistry target. There appears to be several

reasons for this. First, BACE1 has a large hydrophobic substrate-binding site designed to fit

4

polypeptides, thus making it difficult to inhibit the enzyme with small nonpeptidomimetic

compounds that have desirable drug-like characteristics.

Ideally, BACE1 inhibitor drugs should be of a molecular weight <500, orally bioavailable,

metabolically stable, intrinsically potent, and highly selective for BACE1 instead of other

aspartic proteases. Compounds must also be hydrophobic enough to penetrate both plasma

and intra cellular membranes to gain access to the lumen of the compartment where the

BACE1 active site is localized. Efficacious BACE1 drugs would need to efficiently cross the

blood-brain barrier (BBB) and achieve a high concentration in the cerebral parenchyma, thus

the drug molecule should not be a substrate for efflux transporters such as P-glycoproteins.

Therefore, developing a protease inhibitor, especially one that is intended to be active within

the CNS, is a challenging and time-consuming task (Silvestri, 2009).

Despite these challenges, potent nonpeptidomimetic small molecule BACE1 inhibitors have

shown success in lowering cerebral Aβ levels in mouse (Fukumoto et al., 2010),hamster

(Truong et al., 2010) and primate (Sankaranarayanan et al., 2009) models. Moreover, the

biopharmaceutical company CoMentis (South San Francisco, CA, USA) recently announced

the completion of the first human phase 1 clinical trial of a BACE1 inhibitor drug (Luo and

Yan, 2010). Other BACE1 inhibitor drug candidates will probably soon be entering into

human clinical trials. An interesting alternative to small-molecule inhibitors entails the use of

monoclonal antibodies to inhibit BACE1 enzymatic activity.

Recent reports hint at the potential of antibodies that inhibit BACE1 cleavage of APP by

either directly binding to BACE1 (Zhou et al., 2011) or by binding to the BACE cleavage site

of APP (Arbel et al., 2005). The latter has shown in vivo efficacy for decreasing Aβ in a

murine model (Rakover et al., 2007). These encouraging results suggest that therapeutic

approaches involving BACE1 inhibition for the treatment or prevention of AD may be a

reality in the future. Given recent data hinting at important physiological roles for BACE1

however, careful titration of the BACE1 drug dosage may be necessary to minimize

mechanism-based side effects.

Therefore, to further validate BACE1 as a therapeutic target for drug discovery, it is crucial

to fully understand the outcome of inhibiting the enzymatic function of BACE1 and its

substrates, aiding in the development of more efficient BACE1 inhibitors against AD (Jämsä

et al., 2011).

5

Our final year project targeted BACE1 to screen the inhibitory potencies of ten chemical

compounds bearing a similar scaffold structure which is elaborated in figure 2. These

compounds were screened in silico or virtual high throughput screening (VHTS) and they

were predicted to bind in the active site of BACE1, interacting mainly with the S4’ and S3’

sub-sites. This method has become more common in prioritizing compounds for drug

candidates because of its relative speed, less use of resources and has a higher hit rate

compared to real-world screening like high throughput screening (HTS).

The compounds vary only in the groups that interact with these sub-sites, creating a possible

structure-activity relationship (SAR) study. Therefore, a template compound of considerable

interest from previous FYP studies was used as the non-variable regions of the compounds,

which interacts with the S4, S1 and S3 subactive sites of the active site of BACE1.

Figure 2: The template compound, showing regions of it interacting with the sub-sites of BACE1’s

active site. A benzofuran, carbonyl and pyrrol group interacts with the S4, S3 and S1 subactive sites

respectively, and were left unchanged in all of the tested compounds in this study. Pro70, Tyr71,

Arg128 and Tyr198 are the amino acids that make up the S3’ sub-site, while Leu30, Tyr197, Ile126

and Glu125 make up the S4’ subactive site. This picture was generated from a docking software.

6

Figure 3: The molecular model of compound 9 and the amino acid to inhibitor interactions. Sub-site

names are in red while the interacting amino acids are in blue.

For the evaluation of SAR, ten compounds were tested for their antagonistic properties

against BACE1, using fluorescence resonance energy transfer (FRET) method where they

were first assayed for their percentage inhibition before they were assayed for their IC50

values. The compounds were nonpeptidomimetic, as opposed to peptidomimetic compounds.

Existing peptidomimetic inhibitors have low oral bioavailability, metabolic instability and

poor ability to penetrate BBB (Huang et al., 2009).

As mentioned before, problems with the potency and PK properties are one of the main

reasons why BACE1 inhibitors have not progressed well. Nonpeptidomimetic compounds are

more metabolically stable and have higher bioavailability, which reconciles with the

pharmacokinetic problems BACE1 inhibiting drugs face, and also with potency problems, as

less of the drug gets reduced in the body.

Following enzyme inhibition study, we then moved to the stage of toxicological assessment,

which is one of the major components of preclinical development in drug discovery.

2. Literature Review

2.1. Alzheimer’s disease (AD)

AD is a degenerative disease that slowly and progressively causes brain cells to deteriorate in

those who are of age 65 and older. It is caused by the formation and accumulation of two

unique structures associated within neurons known as neurofibrillary tangles and neuritic

7

plaques. These structures lead to neuronal death and thus cause atrophy on an Alzheimer’s

brain. There is a proportional correlation of the profundity of intellectual deterioration with

the severity of histological changes in the brain of a patient with AD. Apart from

neurodegenerative cognitive function, AD also causes the demise of bodily functions that

may bring about an array of psychological and behavioral changes in those afflicted by this

disease. It is neither infectious nor contagious, but it is the single most common cause of

dementia responsible for 60 to 80 percent of all episodes of dementia worldwide (Lisa et al.,

2012).

2.2. Hallmarks of AD

2.2.1. Neurofibrillary tangles

Neurofibrillary tangles are tightly linked to the degree of dementia, suggesting that the

formation of neurofibrillary tangles more directly correlates with neuronal dysfunction. The

region most affected by neurofibrillary tangle formation during the course of the disease is

found in the hippocampus, an area of the brain involved in processing experiences and the

formation of long term memory occurs. Neurofibrillary tangles are composed of the

hyperphosphorylated forms of the microtubule-associated protein called tau. Another

phenomenon observed in patients of AD is early hyperphosphorylated tau protein

accumulation in neurons, even before formation of neurofibrillary tangles, suggesting that an

imbalance between the activities of protein kinases and phosphatases acting on tau is an early

phenomenon (Brion, 1998).

Tau, a microtubule associated protein, which usually has a certain number of phosphate

molecules attached to it, binds to and stabilizes microtubules. In AD, an abnormally large

number of additional phosphate molecules attach to tau. As a result, hyperphosphorylation

occurs, which causes tau to disengage from the microtubules and begin to coalesce with

other tau threads. These tau threads form structures called paired helical filaments, which can

become enmeshed with one another, forming tangles within the cell. Microtubules

disintegrate as an aftermath, collapsing the neuron’s internal transport network. This collapse

impairs the ability of neurons to communicate and transmit signals with each other.

8

Figure 4. Image of neurofibrillary tangles in AD. Several neurofibrillary tangles can be visualized

with a silver stain in the cerebral cortex of a patient with AD (Chong, Li et al, 2005).

2.2.2. Senile plaques

Senile plaques arise from the abnormal extracellular accumulation and deposition of Aβ with

40 or 42 amino acids (Aβ40 and Aβ42), two normal byproducts of the metabolism of the APP

after its sequential cleavage by both BACE1 and gamma-secretase in neurons. Due to its high

rate of fibrillization and insolubility, Aβ42 is more abundant than Aβ40 within the plaques.

Figure 5. Production of Aβ40 and Aβ42 by enzymatic function of BACE1 and gamma-secretase on

APP. (Albert, 2009).

Unlike neurofibrillary tangles, Aβ plaques accumulate mainly in the isocortex. Although the

spatiotemporal pattern of progression of Aβ deposition is far less predictable than that of

neurofibrillary tangles, in general the allocortex (including entorhinal cortex and

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hippocampal formation), the basal ganglia, relevant nuclei of the brainstem, and the

cerebellum, are involved to a lesser extent and later than the associative isocortex.

Senile plaques can be morphologically classified into two distinct types of amyloid plaque,

which are diffuse and dense-core plaques according to their staining with dyes specific for the

β-pleated sheet conformation such as Congo Red and Thioflavin-S. This simpler

categorization is relevant to the disease because, unlike diffuse Thioflavin-S negative

plaques, Thioflavin-S positive dense-core plaques are associated with detrimental effects on

the surrounding neuropil including increased neurite curvature and dystrophic neurites,

synaptic loss, neuron loss, and recruitment and activation of both astrocytes and microglial

cells.

Indeed, diffuse Aβ plaques are commonly present in the brains of cognitively intact elderly

people, whereas dense-core plaques, particularly those with neuritic dystrophies, are most

often found in patients with AD dementia. However, the pathological boundaries between

normal aging and AD dementia are not clear-cut. It was found that even cognitively normal

elderly people exhibited substantial amyloid burden in their brains (Serrano-Pozo et al.,

2011).

Because age does not necessarily play a role in the accumulation density of senile, it is

speculated that innocuous deposits of non-aggregated, supposed non-harmful Aβ plaques,

may undergo an intricate change into mature senile plaques. This maturation process is

assumed to be carried out by butyrycholinesterase (Mackenzie, 1994).

Overall, senile plaques and neurofibrillary tangles are similar in terms of regional distribution

and chemical composition in those who are afflicted by AD and those who are aging

normally. Hence, these plaques and tangles are closely associated with dementia (Mackenzie,

1994).

10

Figure 6: Microscopic evaluation of the cerebral cortex with a silver stain in a patient with AD

demonstrating “senile plaques” with neuronal degeneration. (Chong, Li et al, 2005).

2.3. Stages of AD

The time from diagnosis to death differs amongst people with AD, the disease generally

progresses through the same stages.

Dr. Ron Petersen was the first to define a condition called mild cognitive impairment (MCI)

to describe early changes in memory. Dr. Petersen defined MCI as a condition in which a

person has memory problems greater than expected for a person that age, but who does not

have the other cognitive or personality changes that typically accompany AD.

Over time, as the plaques and tangles continue to proliferate, an individual with MCI may

progress to a clinical diagnosis of AD. This stage is called mild or early AD. More of the

cerebral cortex will be affected, so memory loss would increase, and other cognitive abilities

will diminish. An individual with mild AD may get lost in familiar places or fail to recognize

his surroundings. He may take longer to accomplish the daily tasks of living like washing,

dressing, and eating. Mood and personality changes can also occur; he may lose spontaneity

or drive, or show increased anxiety or aggression. AD is often diagnosed during this phase.

The diagnosis often helps families make sense of their loved one's behaviours (HBO, 10

January 2013).

As AD progresses and the damage spreads further in the brain, the person enters a stage

referred to as moderate AD. The brain continues to shrink and symptoms become more

pronounced as the disease reaches the areas of the cerebral cortex that control language,

reasoning, sensory processing, and conscious thought. A person with moderate AD may

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wander or become confused, anxious or agitated, engaging in angry outbursts, tearfulness,

irritability or restlessness. His attention span may shorten. He may have problems

recognizing family and friends, and difficulty with language, reading, writing, and arithmetic,

and with the logical organization of thoughts (HBO, 10 January 2013).

He may also be unable to learn new things and consequently be unable to cope with new

situations. At this stage, a person with AD might also experience hallucinations and paranoid

delusions, and lose impulse control, leading to things like inappropriate undressing or

vituperation. It is helpful for caregivers to understand the disease and be more prepared for

these behaviours before they happen.

At the last stage of this illness, severe AD, plaques and tangles are found throughout the

brain. Most areas have shrunken further, leaving only a thin ribbon of gray matter and even

larger fluid-filled ventricles. An individual at this final stage cannot communicate in any way

except moaning and grunting. He doesn't recognize loved ones and is completely dependent

on others for care. He may experience weight loss and difficulty swallowing, seizures, skin

infections, lack of bladder and bowel control, and increased sleeping. If bedridden, he is

likely to die from pneumonia as a result of having inhaled food or drink because of difficulty

swallowing (HBO, 10 January 2013).

2.4. Risk factors of AD

2.4.1. Genetics

Genetic research on AD shows that early-onset AD is rare and hereditary. Chromosomes 21,

14, and 1 became the focus of attention. It was found that some families had autosomal

dominant mutations in selected genes on these chromosomes (NIA, 14 Nov 2011).

It was found that the mutation in chromosome 21 causes an abnormal APP to be produced.

On chromosome 14, the mutation causes an abnormal protein called presenilin 1 (PS1) to be

produced. On chromosome 1, the mutation causes presenilin 2 (PS2) to be produced (NIA, 14

Nov 2011).

Mutations in these three genes do not play a role in the more common late-onset AD.

However, these findings were vital because they showed that genetics was indeed a factor in

AD, and they helped to identify some important cell pathways involved in the AD disease

process. This discovery showed that mutations in APP can cause AD, highlighting the

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putative role of Aβ in the disease. Mutational changes to PS1 and 2 also caused an increased

amount of the damaging Aβ to be formed in the brain (NIA, 14 Nov 2011).

Apart from early-onset AD, studies also unravelled that a region in chromosome 19 was

linked to late-onset AD.

2.4.2. Aging

People are exposed to more free radicals, which are oxygen or nitrogen molecules that

combine easily with other molecules, as they age. Free radicals are generated in

mitochondria, which are organelles found in all cells, including neurons.

Free radicals can help cells in certain ways, such as fighting infection. However, because they

are very active and combine easily with other molecules, free radicals also can damage the

neuron’s cell membrane or DNA. The production of free radicals can set off a chain reaction,

releasing even more free radicals that can further damage neurons. Such damage is

called oxidative damage. The brain’s unique characteristics, including its high rate of

metabolism and its long-lived cells, may make it especially susceptible to oxidative damage

over the lifespan. Furthermore, it was discovered that Aβ generates free radicals in some

plaques; this identifies aging as a factor of AD (NIA, 14 Nov 2011).

2.4.3. Vascular impairment in the brain

Aging brings changes in the brain’s blood vessels; arteries can narrow and growths of new

capillaries are maimed. Research had found that whole areas of nervous tissue are, including

their capillaries, lost due to AD. Blood flow to and from various parts of the brain can be

affected and the ability for the brain to compensate for brain damage from AD is reduced.

Poor clearance of Aβ from the brain can, combined with diminished capabilities to develop

new capillaries, lead to chemical imbalances in the brain and damage neurons’ ability to

function and communicate with each other (NIA, 14 Nov 2011).

2.4.4. Hypoxia

Hypoxia, which can be triggered through smoking and severe head injury, can result in loss

of consciousness and systolic hypertension in the elderly, which may be a cause of hypoxia

directly or indirectly via neuronal ischemia (Kawahara and Kuroda, 2000).

13

Prolonged or chronic hypoxia has been shown to alter the excitability and functional

expression of ion channels, which possibly contributes to neurodegeneration. Reduced

oxygen levels result in the formation of Aβ, leading to upregulation of native L-type calcium

channels and disruption of calcium homeostasis (Kawahara and Kuroda, 2000). Cholinergic

neurons may be especially vulnerable to Aβ toxicity. The dysregulated calcium expression

following hypoxia in central neurons may contribute to the neurotoxicity of Aβ and

subsequent development of AD (Khan and Davies, 2008).

2.4.5. Gender

Women secrete higher oestrogen levels, which has an important role in the body in

maintaining healthy neural functions as well as to safeguard the brain from damage.

Oestrogen promotes neuronal cell survival and provides protection from neurotoxins. They

facilitate axonal sprouting and neuronal repair, reduce neuronal injury and enhance synaptic

transmission and neurogenesis. These beneficial effects have led to the supposed hypothesis

that oestrogen may exert protective measures against neurodegenerative diseases, such as

AD.

A finding (Cherry et al., 1992) showed that there was an increased AD prevalence in elderly

women. This suggests that oestrogen deficiency might play a role in the development of AD.

Studies have shown the prevalence of AD is greater in women than in men of a comparable

age, with women aged 50–64 years having 1.7 times higher incidence of AD, possibly as a

result of reduction of oestrogen levels during and after menopause (Cherry et al., 1992).

2.5. AD as a major health issue

AD ranks as the sixth-leading cause of death in the United States. According to data from the

National Center for Health Statistics, AD was reported as the underlying cause of the death of

eighty-two thousand people in 2008 (Lisa et al., 2012). The prevalence of AD in 2002 was

estimated to be 2.3 million individuals over age 70, based on a US population-based sample

(Plassman et al., 2007).

Another group estimated the prevalence of AD in 2000 at 4.5 million individuals aged 65 and

older, based on a U.S. regional sample (Hebert et al., 2003). This latter figure was updated to

an estimated 5.3 million individuals with AD in 2008. This translates into about one in 8 to 10

people over the age of 65 suffering from AD. The worldwide prevalence of dementia is

14

estimated to be 35.6 million in 2010, with the number exceeding 65 million in 2030 and 115

million in 2050, making AD a pressing global health concern (Lisa et al., 2009).

Although current Alzheimer's treatments cannot stop Alzheimer's from progressing, they can

temporarily slow the worsening of dementia symptoms and improve quality of life for those

with Alzheimer's and their caregivers. Today, there is a worldwide effort under way to find

better ways to treat the disease, delay its onset and prevent it from progressing further.

2.6. Therapeutic strategies against AD

Despite unresolved questions, sufficient progress in delineating the disease using the amyloid

hypothesis cascade has now been achieved to envision several discrete targets for treatment.

Inhibitors of Aβ production, small compounds that cross the BBB and decrease but do not

eliminate either BACE1 or gamma-secretase activity, could be therapeutic in the early

clinical phases of the disease, particularly in patients with minimal cognitive impairment, and

in subjects not suffering from dementia. In the case of gamma-secretase inhibitors, drugs

could be designed to decrease Aβ production by some 30–40% or so, hopefully without

interfering in a quantitatively meaningful way with Notch processing. The fact that very

small amounts of the Notch intracellular fragment are sufficient to activate signalling in cells

(Schroeter et al., 1998) may mean that some decrease in Notch proteolysis can be tolerated.

An alternate approach would be to use small molecules to bind Aβ monomers and prevent

their assembly into potentially cytotoxic oligomers. However, if an anti-aggregating

compound solely blocked amyloid fibril formation, this could allow increased accumulation

of metastable intermediates such as oligomers and therefore theoretically aggravate the

disease. One advantage of an anti-oligomerization strategy is that drugs produced would

target a pathological event in the disease rather than interfering with normal metabolic

reactions.

A third approach administers anti-inflammatory drugs that interfere with aspects of the

microglial, astrocytic, and cytokine responses that occur in the AD brain. It has been found

that consumption of nonsteroidal anti-inflammatory drugs is correlated with a lower

likelihood of developing AD (Selkoe, 2001). However, conventional anti-inflammatory drugs

may have considerable potential toxicity especially in older patients (Selkoe, 2001).

Neurorestorative factors like neurotrophins may be used and small compounds mimicking

their actions, which might rescue synapses and cell bodies undergoing active injury.

15

However, this approach would operate in the presence of ongoing new injury from the

putative cytotoxic effects of Aβ.

An intriguing approach to lower the levels of Aβ and reduce Aβ deposits in the brain comes

from a recent study in APP transgenic mice. Parenteral immunization with synthetic human

Aβ peptide led to a strong humoral response and the apparent movement of some of the Aβ

antibodies across the BBB into the brain parenchyma (Schenk et al., 1999). Although the

mechanism remains unclear, the anti-Aβ antibody response led to enhanced clearing of Aβ

deposits in mice that already had begun to develop plaques, possibly by the recruitment of

local microglia.

Moreover, immunization of young mice before the development of Alzheimer-type

histopathology was associated with a marked inhibition of subsequent plaque formation and

the associated gliosis and neuritic dystrophy. Presumably, the very high levels of Aβ

antibodies induced peripherally in these mice led to a small fraction crossing the BBB and

acting centrally. No untoward antigen-antibody reaction ensued, i.e., the inflammatory

cytopathology in the mouse was prevented rather than worsened. The recent initiation of

human trials using this Aβ vaccination approach will be followed with great interest.

Finally, antioxidants, free radical scavengers, calcium channel blockers and modulators of

certain signal transduction pathways might protect neurons from the downstream effects of

Aβ accumulation intracellularly and/or extracellularly. The problem with this approach is that

there may be potential lack of efficacy as there may be are multiple ways in which neurons

respond to Aβ and the Aβ-associated inflammatory process. As a result, blocking one or two

of these might not significantly decrease overall neuronal dysfunction and loss.

Because the success of these strategies cannot be predicted and because two or more

approaches might ultimately be combined, all such approaches and others not reviewed here

need to be pursued. Current, largely symptomatic treatments aimed at enhancing the levels of

depleted neurotransmitters, particularly acetylcholine, may continue to be useful, even if

more specific treatments aimed at early steps in the disease are forthcoming (Selkoe, 2001).

2.7. Localization and Expression of BACE1

The majority of BACE1 is located in Golgi and endosomal compartments in brain cells.

BACE1 undergoes a complex set of posttranslational modifications during its maturation.

Pro-BACE1 is cleaved by furin and other members of the furin family of convertases to

16

remove the 24-amino-acid amino (N) - terminal region of the propeptide within the trans-

Golgi network (TGN). The 24-amino-acid prodomain is required for the efficient exit of pro-

BACE1 from the endoplasmic reticulum. Mature BACE1 has four N glycosylation sites at

Asn153, -172, -223, and -354, and the BACE1 activity is dependent on the extent of N

glycosylation. The cytoplasmic domain of BACE1 and its phosphorylation are required for

efficient maturation and its intracellular trafficking through the TGN and endosomal system.

BACE1 has a tissue-specific expression pattern. BACE1 is expressed at the highest levels in

the pancreas and also at high levels in the brain (Michelle et al., 2004).. BACE1 mRNA

(messenger ribonucleic acid) was found in neurons of all brain regions but not in glial cells.

Although BACE1 enzymatic activity is high in the central nervous system, there is a relative

low level in peripheral tissues. Studies indicate that tissue-specific expression of BACE1 is

very important for normal APP processing, and dysregulation of BACE1 expression may

play a role in AD pathogenesis (Michelle et al., 2004).

2.8. Regulation of BACE1

There are multiple physiological stress signals and pathways that play a role in the regulation

of BACE1, causing an increase or decrease in BACE1 protein levels and enzymatic activity.

It was found that a possible link between stroke, brain ischemia and AD is hypoxia in Sun et

al., 2006. In the study, hypoxia increase BACE1 expression and activity, resulting in Aβ

overproduction, as shown in vitro as well as in AD transgenic mice (Sun et al., 2006). One

mechanism of the effect of hypoxia on BACE1 up-regulation is the activation of hypoxia-

inducible factor 1 (HIF-1), a transcription factor that regulates oxygen homeostasis, and has

been shown to bind to BACE1 promoter and regulate its gene expression (Zhang et al.,

2007). Similarly, BACE1 expression can be stimulated by presenilin as a result of oxidative

stress via c-jun N-terminal kinase (JNK) pathway.

Additionally, the mitochondria have been known to generate reactive oxygen species (ROS)

that has a causative role in mediating early hypoxia-dependent up-regulation of BACE1

transcription. The release of ROS, and the consequent up-regulation of BACE1 is paralleled

by the activation of the JNK/c-jun pathway, which is quiescent in the late phase of post-

hypoxic BACE1 increase, that depends on HIF-1 activity. The early post-hypoxic up-

regulation of BACE1 recapitulates the cascade of events induced by oxidant agents and 4-

hydroxynonenal in cells and in animal models: an increase of BACE1 mRNA, protein levels,

17

and activity that is mediated by the activation of the JNK/c-jun pathway (Tamagno et al.,

2008).

Recent studies have also shown that BACE1 expression is regulated by the gamma-secretase

activity, providing evidence of positive feedback loop between the BACE1 and gamma-

secretase cleavages on APP. In this connection it is significant that ischemic and hypoxic

condition produces an increase in gamma-secretase activity (Arumugam et al., 2006).

Moreover, the expression of BACE1 is decreased by the activation of extracellular signal

regulated mitogen activated protein kinase (ERK)1/2, that inhibits the gamma-secretase

(Tamagno et al., 2008).

The regulation of BACE1 can also be coupled to the influence of post-translational

modification after studies discovered the lack of correlation of mRNA and protein levels.

Moreover, it has been shown that BACE1 protein expression was up-regulated in the brain of

some sporadic AD patients without changes in the level of the corresponding mRNA, thereby

suggesting that these mechanisms can play a pathogenic role.

The 5′ UTR of BACE1 mRNA is long, evolutionally conserved has a high GC content and

four uAUGs, all features that suggest the potential of translational regulation. Two recent

studies have demonstrated that BACE1 5′ UTR is inhibitory to translation. However, they

differ in the interpretation of the data, with one report favoring a major role of uAUGs, while

the other suggests that the GC-rich region of the 5′ UTR forms a translation barrier that

prevents the ribosome from efficiently translating the BACE1 mRNA. In addition, a third

article suggests that a shunting mechanism can overcome the translational inhibition by

BACE1 5′ UTR in a cell-specific manner. Therefore, the exact mechanism of down-

regulation of translation exerted by BACE1 5′ UTR remains elusive (Mihailovich et al.,

2007).

2.9. Active Site of BACE1

BACE1 contains two active site aspartate residues in its extracellular protein domain. BACE1

moves interconvertibly from the endosomal system to the cell surface and breaks down

Amyloid Precursor Protein (APP) when it is activated. It has been reported that BACE1

molecules are localized within endosomal system and the trans-Golgi network, where they

colocalize with APP (Capell et. al., 2000).

18

Many X-ray crystallography studies on BACE1 have been conducted as it has become a

major target in the development of drugs for AD. Studies have indicated that the active site of

BACE1 is covered by a flexible antiparallel β-hairpin, or a flap. It is believed that this flap

controls substrate access to the active site and set the substrate into the correct geometry for

the catalytic process.

It has also been observed that this flap was packed into a closed conformation in an inhibitor-

bound BACE1 while the opposite was true for the apo structure of BACE1 (Hong, 2004).

This indicated that the conformational change was an important process upon

substrate/inhibitor binding.

Aspartic proteases should have two highly conserved water molecules, the first (Wat1) is

located between Asp32 and Asp228 in the case of BACE1, which after substrate binding is

activated by the free Asp pair by forming a hydrogen bond with it. Next, the activated Wat1

attacks the scissile-bond carbonyl in a nucleophilic reaction.

The resulting geminal diol intermediate is stabilized by hydrogen bonds with the carboxyl

group of Asp. Finally, decomposition of the scissile C-N bond is accompanied by the transfer

of a proton from Asp to the leaving amino group. Kinetic studies have suggested that Wat1

inhibits inhibitor binding to active site of BACE1 (Marcinkeviciene et. al., 2001). Reticulon 3

and 4 are examples of highly conserved natural inhibitors of BACE1 (He et al., 2004).

The second water molecule (Wat2) is involved in hydrogen bonding with a tyrosine residue

located in the flap. WAt2 also participates in a Wat2-Ser35-Asp32-Wat1-Asp228 hydrogen

bonding network that is also highly conserved (Gorfe and Caflisch, 2005). The significance

of these water molecules in substrate-active site binding suggests they directly affect the

functions of BACE1.

2.10. Role of BACE1 in Aβ formation

BACE1, also known as beta-site APP cleaving enzyme 1 (beta-site amyloid precursor protein

cleaving enzyme 1), memapsin-2(membrane-bound aspartic protease 2), and aspartyl

protease 2 (ASP2) is an enzyme found in humans that is encoded by the BACE1 gene. It acts

as the first catalyst of the Alzheimer’s amyloid cascade. Another enzyme known as gamma-

secretase appears as a complex of proteins consisting of PS1 or PS2 [5, 6], nicastrin [7],

Aph1 and Pen2 [8, 9]. It catalyses the next step in the cascade.

19

The first step in Aβ generation is cleavage of APP in which BACE1 synergizes with gamma-

secretase permitting the transition into the amyloidogenic pathway as shown in Figure 7. Aβ

genesis is initiated by BACE1 cleavage of APP at the Asp+1 residue of the Aβ sequence to

form the N-terminus of the peptide. This scission frees two cleavage fragments: a secreted

APP ectodomain, APPsβ and a membrane-bound carboxyl terminal fragment (CTF), CTF99.

CTF99 is subsequently cleaved by gamma-secretase to form the C-terminus of the Aβ peptide

and an APP intracellular domain (AICD) (Cao and Sudhof, 2004).

Cleavage by the gamma-secretase complex is not accurate, mainly producing Aβ40 while

releasing some Aβ42. It is this gamma-secretase-dependent cleavage that is responsible for

the excess generation of Aβ42 which stimulates the development of extracellular plaques that

are hallmarks of AD.

Conversely, as shown in Figure 7, Aβ genesis may be avoided if APP is cleaved by alpha-

secretase within the Aβ domain that initates the non-amyloidogenic pathway instead. alpha-

secretase have been presumably identified as TNF-α converting enzyme (TACE), disintegrin

and metalloprotease domain protein-9 (ADAM) and ADAM-10. Alpha-secretase cleavage of

APP occurs within the Aβ domain at Leu+17, and produces the secreted APPsα ectodomain,

and a CTF83, which in turn is cleaved by gamma-secretase to form the non-amyloidogenic 3

kDa fragment, p3.

In many instances, an increase in non-amyloidogenic APP metabolism is coupled to a

reciprocal decrease in the amyloidogenic processing pathway, and vice-versa, this is due to α-

and BACE1competitive nature for APP as a substrate (Vassar et al., 1999).

Therefore, as BACE1 is the catalyst in Aβ peptide generation as well as a putative rate-

limiting enzyme, it is highly regarded as a prime candidate for drug inhibition in the hope of

lowering cerebral Aβ peptide levels to treat or prevent AD.

20

Figure 7: APP metabolism by the secretase enzymes: BACE1cleaves before gamma-secretase in the

amyloidogenic pathway; alpha-secretase is involved in non-amyloidogenic pathway instead (Cole and

Vassar, 2007).

2.11. Aβ peptide

Aβ peptides populating the core of senile plaques are mainly produced by neuronal cells

(Rossner et al., 2001). Aside from the amyloidgenic pathway, an alternative and slightly

different processing of APP by alpha-secretase called the non-amyloidgenic pathway that

occurs at the center of the Aβ domain of APP (Wolfe et al., 1999). According to numerous

studies, Aβ peptides at least contribute to AD pathogenesis in one way or another. Notably,

three genes encoding proteins involved in Aβ production, mainly APP, and PS1 and 2, were

found to be involved in an earlier and more serious case of AD (St George-Hyslop, 2000).

Various Aβ peptides species are found in senile deposits as well as inside cells. The nature

and length are highly variable. Genuine “full length” Aβ peptides, that are Aβ1-40 or Aβ1-42,

can undergo a variety of secondary proteolytic cleavages (Sevalle et al., 2009). Moreover,

monomeric soluble Aβ peptides could associate to form small soluble aggregates including

oligomers and protofibrils. Soluble oligomeric species apparently exhibit higher toxic

potency on cells than Aβ monomers (Di Carlo, 2010).

21

Therefore, such pathology may arise from modifications of the nature and concentration of

Aβ peptides, or an alteration of their biophysical properties that encourages aggregation,

promoting subcellular production and accumulation that leads to Aβ-associated toxicity.

APP and its proteolytic fragments are known to be involved in sophisticated networks and

several feedback loops (Hunter and Brayne, 2012). Furthermore, Aβ peptides are also known

to induce their own production. This is done by Aβ peptide, in which it activates its own

production by binding to the promoters of APP and BACE1, as Aβ has been recently shown

to display transcription factor properties (Bailey et al., 2011) Thus, the treatment of human

NT2N neurons with Aβ peptide in one study, showed increased APP processing and

production of Aβ peptides [24].

2.12. Role of blood-brain barrier (BBB)

The BBB was discovered when dyes, injected into living animals, stained all tissues except

for most of the brain and spinal cord, leading to the postulated BBB. The BBB is a

physiologic matrix of tissue that is selectively permeable and protective of the central

nervous system (CNS). The BBB is located within the endothelium of cerebral capillaries and

the choroids plexus epithelium.

The BBB preserves concentrations within the CNS through reciprocal homeostatic processes.

The rate with which substances penetrate through to the brain tissue is inversely related to

their molecular size and directly related to their lipid solubility. The factors that are

responsible for the transfer across the capillary partition include vesicular transport, diffusion,

and filtration. Diffusion is quantitatively more important in terms of exchange of nutrients

and waste materials. Filtration depends upon a balance of forces between hydrostatic and

osmotic pressure gradients.

BBB integrity can be compromised by a list of diseases such as hypertension, cerebrovascular

ischemia, histologic and metabolic changes within barrier tissue cells, vascular disease,

systemic metabolic disease, trauma, tumors, medications, noxious stimulation, infection,

irradiation, transport and permeability alterations, and aging. Common central disease states

involving BBB integrity include ischemic cerebrovascular events, hypoxia-ischemia, human

immunodeficiency virus (HIV)-induced dementia, multiple sclerosis, and AD.

Vascular dystrophy has been shown to be involved in the deposition of the amyloid beta-

protein in the brains of AD. Although the mechanism remains undiscovered, it has, however,

22

been shown that a larger quantity of Aβ40 and Aβ42 can be found in the brains of

Alzheimer's patients than in non-demented controls. Together with evidence of no difference

in the level of Aβ40 and Aβ42 in peripheral sera between AD and controls, it is suggested

that a dysfunction of the BBB could induce abnormal transport of Aβ proteins from sera, and

accumulation, into the CNS, playing a critical role in the development of AD.

The aging of the central nervous system and the development of incapacitating neurological

diseases, such as AD, is associated with a wide spectrum of histological and

pathophysiological changes eventually leading to a diminished cognitive status. Various

forms of cerebrovascular insufficiency, such as reduced blood supply to the brain or disrupted

microvascular integrity, may occupy an initiating or intermediate position in the sequence of

events ending with cognitive malfunction. Although the diverse triggers and stages of neuro-

degenerative processes are incompletely defined, the contribution of cerebrovascular

deficiencies has become recognized as an important, if not a necessary, antecedent.

It is hypothesized that the BBB dysfunction may contribute to the development of

overlapping and disabling cerebrovascular conditions that include microvascular hemorrhage

and dementia. This hypothesis could explain the link between ischemic cerebral small-vessel

disease and several apparently clinically distinct dementia syndromes. This hypothesis is

supported by pathological, epidemiological, and experimental studies in lacunar stroke and

examinations of the BBB with magnetic resonance imaging (MRI). Critics have viewed the

significance of BBB dysfunction as an early neurophysiologic cascading step leading to

disabling brain diseases has been underappreciated.

Confirmation that BBB failure plays an essential and rate-limiting step to CNS disease

processes could provide a target for new treatments to reduce the effects of vascular disease

on the brain and prevent or reduce cognitive decline and dementia (Sondecker et al., 2005).

2.13. Cytotoxicity Assay

Cytotoxicity assays are widely used in in vitro toxicology studies. The LDH leakage assay, a

protein assay, the neutral red, trypan blue assay and the 3-[4, 5-dimethylthiazol-2-yl]-2, 5-

diphenyltetrazolium bromide (MTT) assay are the most common employed for the detection

of cytotoxicity or cell viability following exposure to toxic substances.

The predictive value of in vitro cytotoxicity tests is based on the idea of basal cytotoxicity

that toxic chemicals affect basic functions of cells which are common to all cells, and that the

23

toxicity can be measured by assessing cellular damage. The development of in vitro

cytotoxicity assays has been driven by the need to rapidly evaluate the potential toxicity of

large numbers of compounds and to carry out tests with small quantities of compound. By

carrying out cytotoxic assays, the identification of toxic effects at early stages of research can

aid in the drug discovery process by providing researchers with necessary information in

identifying structural-toxicity relationship that will help reduce time and costs in the

development of the drug of interest (NoAbBioDiscoveries, 2011).

2.14. MTT Assay

The MTT assay is a measurement of cell viability and proliferation that forms the basis for

numerous in vitro assays of a cell population’s response to external factors. The reduction of

tetrazolium salts is now widely accepted as a reliable way to examine cell proliferation.

The reduction of yellow tetrazolium MTT is reduced by metabolically active cells, in part by

the action of dehydrogenase enzymes, to generate reducing equivalents such as NADH and

NADPH. The resulting intracellular purple formazan can be solubilized and quantified by

spectrophotometric means.

In MTT Cell Proliferation Assay, it measures the cell proliferation rate and conversely, when

metabolic events lead to apoptosis or necrosis, reduction in cell viability. The number of

assay steps has been minimized as much as possible to expedite sample processing. The MTT

Reagent yields low background absorbance values in the absence of cells and vice versa. For

each cell type the linear relationship between cell number and signal produced is unique, thus

allowing an accurate quantification of changes in the rate of cell proliferation to that

particular cell line.

For our experiment, we used Cayman’s MTT proliferation Assay Kit which was a convenient

tool for studying the induction and inhibition of cell proliferation of the ATCC SH-SY5Y

cells in response to the treatment of 10 different compounds (ATCC, 2013).

3. Materials and methods

3.1. Initial screening: Percentage Inhibition of compounds at 3 µM

All 10 compounds were firstly dissolved in 100% DMSO (dimethyl sulfoxide) to make a

stock at 1 mM. Next, compounds were reconstituted to 10 µM using DMSO, and 30 µL of

the diluted compounds were then added into the wells of a black 96-well plate, in triplicates.

24

BACE1 enzyme from BACE1 (β-Secretase) FRET Assay kit, Red (InVitrogen) was diluted

100 times using BACE1 assay buffer that was provided by the kit. Following that, 30 µL of

the diluted BACE1 was added into the same triplicate wells for the compounds. The positive

control was prepared in the same ways as all other compounds.

The negative control wells were prepared by adding 30 µL of BACE1 assay buffer and 30 µL

of diluted BACE1 of the same concentration. The 96-well plate was then transferred to the

Infinite F200 (Multifunctional compact microplate reader [Infinite F200] by TECAN)

machine. Finally, 30 µL of the diluted substrates (Rh-EVNLDAEFK-Quencher, in 50 mM

ammonium bicarbonate) were added into all the filled wells using a multi-channel pipette.

The reaction was monitored for 45 minutes using the Infinite F200 microplate reader with an

excitation wavelength 545 nM and emission wavelength of 585 nM.

The Infinite F200 was set to a kinetics cycle analysis. The kinetics cycle lasted 15 minutes

each, and absorbance readings were generated every minute, which makes a total of 15

different readings for each well at different timings. The resulting data were interpreted in the

statistics software GraphPad Prism.

From the data obtained, the percentages of inhibition can be calculated by taking:

100 – (Compound / Negative control) x 100 % = X % inhibition

Figure 8: Layout of the 96-well plate of the initial screening. Compounds, negative control, and

positive control wells are coloured in red, blue and yellow respectively. Ten compounds and negative

control were analyzed in triplicates.

25

3.2. IC50 assay

8 different concentrations of compounds were prepared by serial dilutions in a 1 : 2 ratio from

a starting concentration of 10 µM till a final concentration of 0.075 µM. Each compound was

diluted to obtain a range of concentrations in order for a graph to be plotted and the point

where inhibition was decreasing would be seen. All dilutions were done using BACE1 assay

buffer.

These were the final concentrations required in each well after the addition of substrate and

enzyme. In order to obtain the desired concentrations, the stock solution of 1 mM was diluted

33 times to yield approximately 30 µM, and was called the 3x concentration.

After the initial dilution, serial dilution was performed in a 1 : 2 ratio to obtain the 8 different

concentrations required. All dilution was done using the assay buffer. The 8 concentrations

obtained were 10, 5, 2.5, 1.25, 0.625, 0.313, 0.15, 0.075 µM.

The compounds were done in triplicates and the wells were loaded with equal parts

compound, substrate and enzyme. For the negative control, the addition of the compound was

substituted with an equal volume of assay buffer to eliminate the inhibitory effects of the

compounds. The percentage inhibition for the data obtained can be calculated similarly to the

kinetic assay where 100 – (compound / negative control) x 100 % = X % inhibition at the

given concentration.

The 96-well plate was then transferred to Infinite F200 machine for the IC50 value analysis.

The machine was set to 15 cycles with each cycle being a minute long. The raw data was

plotted into GraphPad Prism and the results were presented as both the IC50 value in µM and

an S-curve to show the relationship between the percentage inhibition and the compounds

from 10 µM to 0.075 µM.

As mentioned above, the enzyme-based assay took part in a 96-well plate. The compounds

were lined in a decreasing dilution order from the highest well to the bottom as shown below:

Horizontal Well Letter Concentration (µM)

A 10

B 5

C 2.5

D 1.25

26

E 0.62

F 0.31

G 0.15

H 0.08

Table 1: The positions of each concentration of the inhibitors. Triplicates were done for each

concentration.

Figure 9: The layout of the 96-well plate.

3.2.1. Positive control

The positive control was diluted the same way as the compounds were to obtain a 1 mM

stock concentration. Two different sets of serial dilution were prepared for the positive

control. The first was done in a 1 : 2 ratio from 10 µM to 0.075 µM. The second was done

from 0.30 µM to 0.0024 µM to obtain 16 different concentrations in total. The rationale for

the wider spread of data was done to ensure that the IC50 value of the positive compound

could be successfully determined as the positive compound was known to have an IC50 value

even at 15 nM concentration.

The diluted positive control compound was added into the wells at 30 µL, followed by the

addition of diluted BACE1 of similar concentration as the two previous enzyme kinetics

assays, and finally the same substrate of the same concentration as before into all the filled

wells using a multi-channel pipette. The 96-well plate was then transferred to Infinite F200

27

machine for the IC50 value analysis. The machine was set to 15 cycles with each cycle being a

minute long.

The raw data was plotted into GraphPad Prism and the results were presented as both the IC50

value in µM and an S-curve to show the relationship between the percentage inhibition and

the compounds.

3.3. Toxicological Study

3.3.1. Cell Culture

Media preparation

The media which was used for the SH-SY5Y cell line was prepared with a 1:1 ratio of Ham’s

F-12 medium to Eagle’s minimum essential medium with 10% Foetal Bovine Serum (FBS).

FBS was stored in the freezer at -20oC. Thawing of the FBS was done in the water bath set at

37oC. The mixing of the media was done in a 1 L Schott Duran Bottle.

Storage of the culture media was in a fridge with the temperature at approximately 4oC after

being wiped with ethanol and sealed with parafilm to reduce the risks of contamination.

Thawing of SH-SY5Y from liquid nitrogen

The frozen cryovial of cells were taken out from liquid nitrogen (-210oC to -196

oC) and

allowed to thaw in a 37oC water bath partially. The remaining bits of frozen cells were

thawed by holding it or rubbing it with gloved hands, to ensure that the cells do not stay in

37oC for too long. This was because DMSO which was used as a cryoprotectant is more toxic

to cells at higher temperatures.

While the cells were almost completely thawed, it was transferred into the BSC after wiping

it with 70% ethanol. The cells were pipetted up and down gently a few times to mix the cells.

1 mL of cells was taken out and placed into 10 mL of culture medium inside a 15 mL

centrifuge tube. This was to dilute the DMSO.

Cells were mixed by pipetting in the 15 mL centrifuge tube to ensure that the DMSO was

completely diluted. The cells were then centrifuged at 1500 rpm for 5 minutes. The

supernatant was carefully discarded making sure that the pellet was not disturbed. 5 mL of

fresh culture media was then added to resuspend the pellet and pipetted up and down to

ensure an even distribution of cells throughout the entire tube. The 5 mL of culture media

28

with resuspended cells was transferred into a sterile T25 flask labelled SH-SY5Y BAS and

placed in a 5% CO2 incubator set at 37oC. The morphology of the cells were observed every

24 hours.

Washing and removal of unhealthy or dead cells

The materials required for washing and removal of dead cells were trypsin, phosphate buffer

saline (PBS) and culture media. Old culture media was first removed from the flask and 3 to

5 mL of PBS was added to the flask. PBS helps in removing the factors that inhibit trypsin

found in FBS like the Serum protease inhibitor alpha -1-antitrypsin and the mechanical

removal of dead cells that remained on the surface even after removal of the old culture

media.

1 mL of trypsin was added to the flask after removing all of the PBS in the flask and

incubated at 37oC for 4 minutes to dislodge the cells adhered to the substratum. 4 mL of fresh

culture media was then added to the flask to deactivate trypsin and have a total of 5 mL in

each flask.

Cell culture observation and subculturing of cells

Cell morphology was observed 24 hourly. When cells appeared to have a round morphology

or showed an abundance of floating cells, all culture medium were removed and 1 mL of

trypsin was added to trypsinize the cells. The cells was placed in a 37oC, 5% CO2 incubator

for 4 minutes to detach the cells from the flask. The flask was tapped to ensure that most cells

wound be detached. 4 mL of culture media was added to the trypsinized cells to deactivate

the trypsin.

Each flask was changed every 2 weeks to aid in cell growth. After diluting the trypsin, all the

media were then removed from the old flask and placed in a new T25 flask.

The flask would then be rocked in a north, south, and east to west motion to help get an even

distribution of the cells in the flask.

When culture media appeared to be orange, half of the current media was removed and

topped up with the same volume of fresh media. If the media turned yellow in colour, 4.5 mL

of old media was removed and the flask was topped up to 5 mL once again. The initial media

was not completely removed to reduce the likelihood of a sudden environmental change

which may shock the cells.

29

The floating cells in the flask during a media change can be thrown away or placed into a 15

mL centrifuge tube and centrifuged at 1500rpm for 5 minutes. The pellet kept while the

supernatant was discarded and resuspended with 1 mL of fresh culture media. The

resuspended pellet was then transferred to the original or new flask and topped up to 5 mL

with fresh culture media.

Microscopic observation of the cells was done on an Olympus IX51S8F Microscope.

Cell seeding and cell counting

Cell seeding was done in a 96 well plate and was required for the testing of compound

toxicity and cell viability by using the MTT assay. Prior to cell seeding, cell counting was

done using a haemocytometer to seed the desired number of cells per well.

The amount of cells seeded per well was at 5x104 to 1x10

5. 5x10

4 cells was the preferred

amount per well for compound treatment and MTT assay.

A haemocytometer is a specialized microscope slide used for cell counting. It is thicker in

comparison to a standard microscope slide and it has a rectangular indentation which creates

the counting chambers. The centre portion of the slide has etched grids with precisely spaced

lines which aids in the counting process.

Preparation of the haemocytometer

The haemocytometer was first cleaned using 70% ethanol. The coverslip was placed onto the

haemocytometer with a tiny amount of water, ensuring that the coverslip was adhered to the

haemocytometer by looking for the Newton’s rings.

Preparation of the cell suspensions

For the preparation for the cell suspension to be used for cell seeding and counting, the BSC

was UV sterilised and wiped clean with 70% ethanol. All equipment and flasks were wiped

with 70% ethanol before entering the BSC. A T25 flask with a confluency above 70% was

removed from the incubator and placed into the BSC. A 10 mL serological pipette was used

to remove all existing media in the flask. All spent media were discarded into a waste beaker.

1 mL of trypsin was then introduced into the flask to detach cells adhered to the base of the

flask and was placed back into the incubator set at 37oC and 5% CO2 for 4 minutes.

30

After incubation, the flask was tapped gently to agitate and ensure that all cells has detached

itself from the flask and was transferred back into the BSC after wiping with 70% ethanol.

In the BSC, an appropriate amount of culture media added to the flask to deactivate the

trypsin. The flask was homogenised by pipetting up and down a couple of times before

removing 1 mL of the cells and placing it into a 15 mL centrifuge tube to be used for dilution.

Another 10 µL of the cells was removed and placed in an Eppendorf tube. An equal volume

of trypan blue was added to the Eppendorf tube and mixed thoroughly by pipetting up and

down gently a few times. This mixture was ready to be loaded into the haemocytometer.

Cell counting

Using a P20 pipette, 10 µL of trypan blue and the cell suspension was pipetted out and

carefully loaded into each chamber of the haemocytometer. This was done by carefully

resting the tip of the pipette on the edge of the coverslip. The chamber was filled by capillary

action. A constant loading rate was maintained to avoid under or over filling of the two

chambers.

The cells were then left to settle for about 5 minutes before viewing the cells under a

microscope using the 10x objective lens. If there were too many clumps seen under the

microscope, mix the suspension again and repeat the counting procedure.

The corner gird of each chamber which comprises of 16 squares each was focused under the

microscope and the number of cells in these squares was counted. The cells that were counted

were the cells that were not stained by trypan blue. Unstained cells were viable cells whereas

stained cells were dead cells. Cells that touch the boundary on the bottom or the right hand

side were not counted. This process was repeated for all 4 corners of the grid. The stained

cells were counted separately for a cell viability count. The average number of cells of the

corner grid was taken to be equal to the number of cells x 104 per mL.

31

Figure 10: A schematic of the proportions of the guide lines used to determine the cell count and

therefore the cell number per millilitre. The picture was adapted from PK Group (1999) Grid patterns

of improved Neubauer ruled haemocytometer.

3.3.2. 3-[4, 5-dimethylthiazol-2-yl]-2, 5-diphenyltetrazolium bromide (MTT) assay

3.3.2.1. Preparation of MTT assay reagent and assay buffer

The MTT assay buffer was prepared by dissolving the cell based assay buffer tablet in 100

mL of diluted water. The MTT assay buffer was used to reconstitute the MTT reagent. 5 mL

amount of water was first added to the container containing the tablet and mixed around

ensuring that everything was dissolved before transferring to a 100 mL flask and topping up

to 100 mL.

For the MTT reagent, 125 mg of MTT reagent in powder form was reconstituted first using 5

mL of MTT assay buffer. The reconstituted MTT reagent was then transferred to a 50 mL

tube wrapped in aluminium foil as the reagent was light sensitive. Another 20 mL of MTT

assay buffer was added to the tube to reach the final volume of 25 mL.

32

5 mL of the MTT reagent was aliquoted into a 15 mL centrifuge tube wrapped in aluminium

foil to prevent repeated freeze thawing of the master MTT assay reagent.

3.3.2.2. The determination of Cell Number required for MTT Assay

The ATCC cell line SH-SY5Y cells were resuspended using the steps mentioned previously

in Preparation of the cell suspensions (3.3.1.), counted and diluted to the respective starting

cell counts by the methods listed in Cell counting (3.3.1.). The MTT reagent was prepared

using the methods stated in 3.3.2.1. The resuspended cells were then loaded into a 96-well

plate in eight 90 µL replicates and left for 3 days under 37oC and 5% CO2.

After three days, the wells were drained of all the 90 µL cell media through micro-pipetting.

100 µL of crystal dissolving solution was added into the wells and left for an hour, before the

plate was read at 570 nm in the Spectramax 190 plate reader. The results were presented as a

mean value.

3.3.2.3. Toxicological Assay

In this experiment, the human neuroblastoma SH-SY5Y cell line used was subjected to 10

different types of compounds in 10, 5 and 2.5 µM.

The cells were first seeded into two 96 well plates with a density of 5 x 105 cells per well in a

total of 90 µL of culture medium and incubated in a 5% CO2 incubator set at 37oC for 24

hours.

10 µL of the compounds were added to the 90 µL of cells on the 2nd

day to give a final

volume of 100 µL with the compound to cell ratio at 1 : 10. For the negative control wells 10

µL of fresh culture media was added to the wells instead. After the addition of compounds

and culture media, the plate was then incubated for another 24 hours.

On the 3rd

day after the total 48 hours of incubation, 10 µL MTT reagent was added to the

wells and left on the orbital shaker for 1 minute. The plate was then wrapped in aluminium

foil and left in the incubator for 4 hours because the MTT reagent was light sensitive. If there

were viable cells in the well after compound treatment, the cells would change the MTT

reagent into dark purple coloured formazan crystals found at the bottom of each well.

After the 4 hour incubation, the culture media was carefully aspirated to prevent the

disruption of the cell monolayer from each well. 100 µL of crystal dissolving solution was

33

then added to each well while pipetting up and down multiple times to ensure that all the

crystals were dissolved.

The dissolved crystals should yield different intensities of purple colour depending on the

compounds treated and their concentrations. The plate was read by the microplate reader at a

wavelength of 570 nanometers.

4. Results

All compounds were subjected to two stage of bioassays in vitro, viz. Enzyme and cell based

assays. Two enzyme kinetics experiments (initial screening & IC50 tests) were conducted to

explore their relationships with the inhibitory potency of the compounds. Such study,

commonly known as structure-activity relationships (SAR) study, provides us a better

understanding in enzyme-inhibitor interactions. On the other hand, cell based studies

involving MTT toxicological tests revealed the potential cytotoxic effects on SH-SY5Y cells.

Here, we further detail our results accordingly.

4.1. Enzyme Kinetics Assay

4.1.1. Initial Screening: Percentage Inhibition of compounds at 3 µM

Table 2 shows the initial screening results. Six compounds (1, 4, 7, 8, 9, and 10) showed a

percentage inhibition greater than 50% when there were assayed in initial screening.

Compounds 9 and 10 showed the strongest inhibition against BACE1. 2, 3, 5 and 6 showed

less than 50% inhibition at 3 µM.

34

Compo

und

Molecula

r Weight

R X %

Inhibition at

3 µM

IC50 (µM)

1 509.54

60.63 ±

2.40

5.65

2 553.59

16.56 ±

3.66

N.A.

3 549.63

29.96 ±

0.94

N.A.

35

4 589.62

53.05 ±

3.59

6.43

5 585.68

20.19 ±

0.72

N.A.

6 573.62

30.35 ±

2.60

N.A.

7 559.60

72.27 ±

1.21

4.49

8 575.67

55.93 ±

0.81

12.02

9 545.66

85.02 ±

1.93

3.97

10 594.50

84.34 ±

4.00

11.08

36

Table 2: The SAR of substitution patterns of R and X. The data of % inhibition at 3µM were

presented as means ± SEM, n = 3. IC50 values are presented as µM concentration. Models were drawn

using CambridgeSoft ChemDraw. N.A.: Not determined.

Figure 11: BACE1 initial screening results of compounds at 3 µM. Results are presented as the mean

± SEM calculated from GraphPad Prism. Non-parametric, unpaired t-test at 99% confidence interval

was used for statistical analysis. *: compounds showing non-significant difference compared to

negative control (p>0.01). *** and ****: compounds showing significant difference compared to

negative control (p<0.01). Pos represents 100% inhibition and neg represents 0% inhibition.

4.1.2 IC50 assay

From initial screening, we then further investigated the IC50 values of 6 compounds (1, 4, 7,

8, 9, 10). Data from IC50 measurement is summarised in Table 3 and the results interpreted

into IC50 values and an S-curve in table 4. Among them, 9 exhibited the most potent IC50

value of 3.97 µM. The positive control was expected to have an IC50 of 0.015 µM

(Calbiochem®, 2013); the IC50 that was derived in this screening was 0.028 µM.

Concentration

(µM)

7 8 1 4 10 9

10 103.80 ± 77.16 ± 94.72 ± 95.98 ± 98.95 ± 99.75 ±

37

3.67 22.64 1.70 0.76 0.84 2.01

5 73.85 ±

1.98

69.05 ±

2.48

64.07 ±

5.57

81.81 ±

1.33

68.24 ±

3.00

84.22 ±

1.24

2.5 53.87 ±

4.01

31.18 ±

4.52

42.17 ±

3.11

47.72 ±

3.90

33.09 ±

4.80

54.12 ±

5.44

1.25 9.44 ±

6.01

2.12 ±

6.37

-10.96 ±

8.83

15.35 ±

5.49

4.33 ±

5.60

28.48 ±

6.29

0.62 -27.60 ±

8.64

6.90 ±

6.55

-25.15 ±

7.16

-1.25 ±

9.65

-7.12 ±

4.91

-9.58 ±

4.62

0.31 -20.26 ±

7.87

9.30 ±

6.97

-21.94 ±

5.85

2.43 ±

8.36

3.43 ±

12.14

-10.08 ±

5.48

0.15 -29.81 ±

7.99

7.73 ±

5.74

-12.97 ±

6.17

4.90 ±

9.10

-7.89 ±

3.19

'-5.27 ±

5.70

0.08 -10.44 ±

4.78

12.94 ±

5.24

-36.80 ±

14.00

5.93 ±

9.44

-8.78 ±

9.58

0.88 ±

7.53

Table 3: Percentage inhibition values from 10 to 0.08 µM of compounds 1, 4, 7, 8, 9 and 10 on

BACE1. Data presented as means ± SEM. Non-parametric, unpaired t-test was used for statistical

analysis in GraphPad Prism.

Compounds IC50 Value (µM) Dose-dependent S-curve of the compounds

Positive

Control

0.028

38

1 5.65

4 6.43

7 4.49

39

Table 4. The IC50 values of the compounds tested, arranged by the most potent compound in terms of

IC50 from top to bottom. Semi-log S-curves graphically represents the relationship between

percentage inhibition of BACE1 and log10 of compound concentration. Both sets of data were

obtained from GraphPad Prism using one site – fit logIC50 nonlinear regression analysis.

4.1.3. Structure-activity relationship (SAR) study

IC50 values listed in this section refer to the IC50 values tabulated in Table 2. Compound 9,

with an IC50 of 3.97 µM was identified as the most potent compound from our study.

8 12.02

9 3.97

10 11.08

40

Compounds 9 and 3 shared a thienyl at the R position, but differed in the X position. Their

initial screening results were also very different. Compounds 1 and 2 shared a methyl at the X

position but were not similar at R. Their initial screening results were also disparate; 1 at

60.63 ± 2.399%, 2 at 16.56 ± 3.657%.

Compounds 3, 4, 5, 6 and 7 shared the same group at X, but their initial screening and IC50

results were highly varied. Compound 7 exhibited the strongest potency amongst all of them

(IC50 = 4.49 µM, initial screening = 72.27 ± 1.217%).

4.2. Toxicological study

4.2.1. The determination of Cell Number required for MTT Assay

The results obtained showed that wells seeded with 5 x 104 cells resulted in a slightly higher

absorbance at 570 nm (0.358) than the wells seeded with 1 x 105 cells (0.338).

Undifferentiated cells were observed in culture while more will be elaborated in 5.2.1.

Replicates 5x104 cells / mL, Initial Cell

Number

1x105

cells / mL, Initial Cell

Number

1 0.414 0.441

2 0.415 0.35

3 0.449 0.29

4 0.387 0.377

5 0.307 0.355

6 0.389 0.296

7 0.249 0.34

8 0.254 0.256

Average 0.358 0.338

Table 5: Comparisons between the cell number after 3 days of the two experimental initial cell

number of 5 x 104 cells and 10

5 cells. Absorbances were measured using a Spectramax 190 plate

reader.

41

4.2.2. MTT assay

Based on the results of the previous experiment, 5 x 104 cells were seeded into the wells and

were treated. Compound 9 was expected to show low cell viability because it contains a toxic

toluene group at the X.

Taking the mean values of cell viability, SH-SY5Y cells treated with 10 µM and 5 µM of 7

retained the highest cell viability, while cells treated with 2.5 µM of 9 retained the highest

cell viability. This conflicts with our prediction. However, SH-SY5Y treated with 10 µM of

9, 5 µM of 1 and 2.5 µM of 10 showed the lowest percentage viability. Results were

presented as means ± SEM, and were calculated using negative control representing 100%

viability. Compound 7 did not show any cytotoxic effects on SH-SY5Y at all concentrations.

Compound 10 µM 5 µM 2.5 µM

1 48.50 ± 11.41 40.71 ± 3.432 70.36 ± 12.65

2 97.27 ± 40.74 75.82 ± 21.23 69.81 ± 12.66

3 66.53 ± 9.888 72.40 ± 12.84 87.70 ± 3.549

4 64.89 ± 17.36 64.62 ± 13.96 68.85 ± 15.40

5 59.56 ± 8.933 51.37 ± 7.104 71.04 ± 23.43

6 72.81 ± 14.87 95.36 ± 23.29 85.52 ± 20.01

7 111.2 ± 16.46 104.4 ± 31.66 113.4 ± 30.96

8 56.42 ± 5.646 68.85 ± 7.335 78.96 ± 12.67

9 30.46 ± 8.565 46.17 ± 1.744 157.4 ± 15.81

10 50.00 ± 17.53 61.75 ± 18.24 64.75 ± 2.257

Table 6. The relationship between the compounds at concentrations of 10, 5 and 2.5 µM and SH-

SY5Y percentage viability with an initial cell concentration of 5 x 104 cells per well. Data is presented

as means ± SEM, n = 3. Non-parametric, unpaired t-test was used for statistical analysis in GraphPad

Prism.

42

Figure 12: The % viability of SH-SY5Y against compounds at 10, 5 and 2.5 µM. The error bar was

presented on top of all bars except for negative control, which represents 100% viability. Non-

parametric, unpaired t-test and column statistics were used for statistical analysis in GraphPad Prism.

5. Discussion

5.1. Enzyme-based assay

The purpose of the enzyme-based assay was to determine which of the ten compounds

exhibited more than 50% inhibition of BACE1 initial screening, so that an IC50 assay would

be conducted to measure their IC50 values, which was indicative of an inhibitor’s potency.

The compounds tested in this final year project varied only in the groups that interacted with

the S3’ and S4’ sub-sites of BACE1 enzyme (as shown in Table 2).

The enzyme-based assay was structured so that each compound was treated to BACE1 in

triplicates, enabling the results to be well presented statistically. The enzyme-based assays

consisted of an initial screening followed by an IC50 assay. The reason why the IC50 assay

was not conducted on all the compounds was because of the limited supply of BACE1 and

the enzyme’s substrate. Most importantly the objective of this report was to source out the

best molecular structures for a potent BACE1 inhibitor. The experiment was carried out in

three phases. During each phase, two compounds were tested.

The FRET assay was used as the method to measure the potencies of the compounds on

BACE1. Fluorescence generated by a substrate modelled after a Swedish mutant APP protein

was measured and compared with the negative control, which then produces the percentage

43

inhibition. The substrate was light-sensitive, so therefore it was added last into the wells of

the 96-well plate.

The inhibitor that attracted the most interest was 9, with the lowest IC50 value of 3.97 µM,

which also shows that it was the most potent. The initial screening also shows that it was

amongst the most potent inhibitors, inhibiting at 85.02%, showing the consistency of both

experiments. The difference of this compound from others was that it contains a 4-

sulfanyltoluene interacting with the S3’ sub-site and a thienyl interacting with the S4’ sub-

site.

Compounds 9 and 3 shared a thienyl at the R position, but differed to the X position. Their

initial screening results was also very different (3 = 29.96 ± 0.9394%), with 9 being more

potent. Their only difference was that 9 had a methyl residue as substitute for the fluorine

attached to the benzene at the X position. This is evidence that a methyl residue was more

effective at increasing the potency of the compounds than a fluorine as a residue attached to a

4-sulfanylbenzene at the area interacting with the S3’ sub-site.

Compounds 1 and 2 shared a methyl at the X position but were not similar at R. Their initial

screening results were also very different; 1 at 60.63 ± 2.399% and 2 at 16.56 ± 3.657%.

Compound 1 had a 3-phenoxyphenyl on the R position while 2 had a 4-(benzyloxy)-3-

methoxyphenyl instead, so the proposition was that since 1 possessed more potency in the

initial screening, the 3-phenoxyphenyl was more effective at inhibiting BACE1 at that

concentration than the bulky residue possessed by 2. Assuming that the inability of inhibitors

into the enzyme sub-sites correlates to lower potency, it may be said that the S4’ sub-site is of

limited size. This form of proposition was also used in another research report (Bäck, 2008).

Since 1 also has a much lower molecular weight (509.54) compared to 2 (553.59), it was

more likely to make it through the BBB (Clarke et al., 2008) and therefore be developed into

a drug lead. A PSA test (Swahn et al., 2012) and a MDR1 – MDCK assay (Lerchner et al.,

2010) could be done in a future research to measure the permeability of the compounds

across the BBB.

Compound 10 also has the highest molecular weight of all the compounds, which makes it

hardest to penetrate the BBB. Its IC50 was 11.08 µM, which shows that it was one of the least

potent inhibitors. The combination of both high molecular weight and low IC50 value is proof

that 10 is not an effective drug to be developed into a drug lead. Upon reviewing the residues

44

of 10 attached at the R (4-chlorophenyl) and X ([2-chlorobenzyl]sulfanyl), these residues

contains chlorine. Thus it may be hypothesised that the chlorine lowers BACE1 inhibitor

potency if both the s3’ and S4’ sub-sites contains it.

Compounds 3, 4, 5, 6 and 7 shared the same residue at X, but their initial screening and IC50

results were highly varied, with 7 exhibiting the strongest potency amongst all of them (IC50

= 4.49 µM, initial screening = 72.27 ± 1.217%), which was evidence that an 3-hydroxyphenyl

at the R position increases potency much better than a 4-methoxyphenyl (6), 4-

isopropylphenyl (5), 4-hydroxy-3-methoxyphenyl (4) and 2-theinyl (3). Amongst them,

compound 5 was measured to have the weakest potency in the initial screening (20.19 ±

0.7211%), so therefore a 4-isopropylphenyl residue at the R position was the least effective at

binding with the S3’ sub-site compared to other residues.

Compounds 3, 4, 5, 6 and 7 shared a similar residue at X. Only 7 showed more than 50%

potency in the initial screening, but the other compounds except for 4 was below 50%.

Compound 3 shared the same thienyl as 9, a compound which was measured to have a potent

IC50 value. This shows the single fluorine that was the difference between these compounds

was a significant impact on potency. This phenomenon was reported in literature (Lerchner et

al., 2010), but not against the S3’ sub-site. In that study, they concluded that fluorinated

alkyl groups interacting with the S2 sub-site led to a major reduction in potency on BACE1.

However, it improved permeability of the compounds across the BBB, which is an important

drug property for a brain-targeting drug.

Comparing the IC50 values of 4 and 7, which were similar at the X position as both contained

a fluorobenzene connected with the rest via a sulfanyl residue, 7 was more potent with an

IC50 value of 4.49 µM while 4 had an IC50 value of 6.43 µM. The initial screening also

determined that 7 could inhibit BACE1 more at 3 µM. The only structural difference between

them is an extra oxygen and methyl at the R position of 4 (R interacts with the S4’ sub-site of

BACE1). This suggests that the presence of a methyl decreased the potency of the inhibitor in

the S4’, contrary to the S3’ sub-site. However, the extra oxygen on the R position of 4 may

have been the contributor of the decreased potency of 4.

Compound 8 was unique for bearing only aromatic rings at both R and X. The IC50 of this

compound was found to be 12.02 µM. This ranks this compound as the least inhibiting

amongst all other compounds in terms of IC50. A limited conclusion may be made, which was

the absence of elements such as oxygen or halogens would limit the IC50 result of the

45

compound and therefore reduce its potency. However, this does not take into the account of

the orientation of the atoms in the residues, which may also affect potency.

Compound 1 has one of the highest potential amongst the compounds to be developed into a

drug lead using just inference from the enzyme-based assay. Although producing slightly

weaker results in the initial screening (60.63 ± 2.399%), and its IC50 value (5.65 µM) was

slightly lower than 9, it has the lowest molecular weight of all the compounds, which was a

highly-sought property for a non-peptidomimetic compound as a low molecular weight

makes the drug pass the BBB easier, and thus more can enter the brain, although non-

peptidomimetic compounds generally have a larger molecular weight than their

peptidomimetic counterparts.

SAR studies revealed that the low molecular weight of 1 was due to the light methyl group

that is attached to X, without the unnecessarily heavy residue at the R position of 2.

Compound 9, which has an even more potent IC50 value, also has a methyl at its X position.

This shows that there may be a correlation between the methyl group at the S3’ sub-site and

higher potencies of the compound, but referencing from the discussion between both 1 and 9,

the methyl group may also have contributed to the detrimental cytotoxic effects on SH-SY5Y

cells.

Compounds 8 and 10 have very bulky residues at X, and residues projecting from it

interacted with the S3’ sub-site of BACE1. These two compounds exhibited the lowest IC50

values amongst all other compounds, so it may be hypothesised that the S3’ sub-site was of

limited size (Bäck et al., 2008). Compound 2 also had a bulky sub-site, but at the R position

(S4’ interacting). It was measured to have the least potency in the initial screening, so it may

also be hypothesised that the size of the S4’ sub-site was also of limited size.

Notably, before the measurement of IC50 of the ten compounds, a positive control was run to

ensure that the BACE1 FRET Assay Kit’s reagents are working as intended. The positive

control was a compound with a known structure and IC50 value which can be used to

determine if our kit has is able to reproduce the results that were listed on the compound.

The positive control was done as a way to test the beta-secretase enzyme activity and rule out

other inhibiting factors such as enzyme degradation and contamination. The expected values

to be obtained from the positive control compound were approximately 15 nM, as reported in

the provider’s website (Calbiochem®, 2013). The positive control was measured in our

46

project to have an IC50 value of 28 nM, which was arguably a very close result as FRET

assays have less sensitivity at nano-molar concentrations (Pietrak et al., 2005).

However, the structure of the positive compound does not share the same main chains and

side chains of the 10 compounds we are testing. This tells us that the inhibitory properties of

our compounds will not be similar to that of the positive control due to the different

interactions of compounds to the sub domains of the active site; therefore a detailed SAR

study was not conducted.

Both the initial screening and the IC50 assay resulted in 9 being the most potent of the ten

nonpeptidomimetic compounds. As raised in the Introduction, problems with the potency

and PK properties are one of the main reasons why BACE1 inhibitors have not progressed

well. Looking at the results of the enzyme-based assays, 9 and 7 has the most potential to be

developed into a drug lead for AD treatment. Compounds 3, 4, 5, 6 and 7 shared a similar

residue at X, but all compounds except for 4 and 7 did not show more than 50% inhibition in

the initial screening. It may be hypothesised that the fluorine in the 4-sulfanylfluorobenzene

decreased the potency of the compounds.

Compounds 9 and 7 scored amongst the highest in both the initial screening and the IC50

assay, showing its ability to be a potent compound against BACE1. However, enzyme-based

tests are insufficient to provide evidence for the compounds as possessing good PK

properties. Absorption through the BBB could be determined through molecular weight could

be used to prove their ease to pass the BBB, however, a PSA test (Swahn et al., 2012) and a

MDR1 – MDCK assay (Lerchner et al., 2010) is more effective at measuring the efficiency of

the compounds to pass the BBB. For evidence of the cytotoxicity of the compounds on neural

cells, the cell-based toxicological assay was conducted immediately after the enzyme-based

assay.

5.2. Toxicological Assay

5.2.1. Cell Culture

This section of the project was included because of the need for a healthy neural cell line for

the toxicological assay, and it covers the difficulties faced during cell culture over a period of

1-63 days and the methods that could have been done or was done in order to solve the

difficulties. The cell line used was the ATCC SH-SY5Y neuroblastoma cell line. The reason

47

why a specialised cell line was used was because normal adult human neural cells do not

undergo cell division.

SH-SY5Y was a neuroblastoma cell obtained from cells lines extracted from the bone

marrow of a four-year old girl suffering from neuroblastoma and was appropriate for our

investigation in the effects of cell proliferation and viability on neural cells by the

compounds. Detailed discussion of MTT assay results are in 5.2.4.

Figure 13: 200X microscopic view of SH-SY5Y cells. Day 1. Image taken with Olympus IX51S8F

Microscope.

As seen in Figure 13, the cells were thawed and cultured in the T25 flask, which showed a

variation in the types of morphology the cells had conformed to. One half of the cells

appeared to have a round morphology which indicated that they were undifferentiated and

was unable to attach to the base of the T25 flask, while the other half of cells that appeared to

have a neuronal morphology and taken on a spindle-like shape, suggesting that they had

adhered to the base of the T25 flask and undergone differentiation.

48

The distinct round morphology of some of the cells can be explained by the lag phase using a

growth curve. During this time, the cells are "conditioning" themselves to the media,

undergoing internal cytoskeletal and enzyme changes and adjusting to the new media.

The cells are also seen far apart from each other which would mean that there would be

minimal contact inhibition and more space is available for the cells to extend the neurites and

differentiate.

Figure 14: 100X microscopic view of SH-SY5Y. Day 4.

As seen in Figure 14, majority of the cells were growing healthily because of their spindle-

like conformation due to differentiation. This suggested that the cells had adapted well with

their environment and were able to utilize the nutrients in the culture medium at an optimal

rate for their healthy proliferation.

49

Figure 15: 100X microscopic view of SH-SY5Y. Day 38.

As seen in Figure 15, the cells showed an unhealthy morphology as the cells were clumping

together and were floating which showed cells were undergoing apoptosis. This abnormal

morphology could be attributed to the depletion of nutrients, growth factors and inability to

adapt to the culture environment. Another possible reason that could explain this

phenomenon was that repeated passaging of cells and the multiple usage of trypsin in the cell

detachment step of subculturing. Trypsin could have caused the substratum to become

smoother in the T25 flask and reduced the ability of the cells of attaching. This is because

adherent cells adhere to a rough substratum better than a smooth substratum.

50

Figure 16: 100X microscopic view of SH-SY5Y. Day 59.

As seen in Figure 16, the cells had regained their healthy looking morphology were able to

differentiate efficiently as compared to the cells in Figure 15 after changing to a new T25

flask. Cells in this new T25 flask were able to produce and receive sufficient growth and

adhesion factors to promote their proliferation. Furthermore, with the replenishment of

culture medium, it improved the nutrient content and diluted any accumulation of toxic

products, waste materials and metabolites that may inhibit cell growth. Hence, the cells were

able to reach a high confluency of 100% eventually as they were provided with an ideal

environment for healthy growth in the log phase as it can be observed in Figure 17.

51

Figure 17: 100X microscopic view of SH-SY5Y. Day 63.

5.2.2. Challenges faced during culturing SH-SY5Y

5.2.2.1 Fungal Contamination

It was observed that there was fungal growth as there was white spots and mould-like

appearance that was growing within the T25 flask. Hence, from the appearance of such

contamination, the conclusion is that it was a fungal contamination. The source of the fungal

contamination was narrowed down to the incubator. The T25 flask containing the

contaminated culture was discarded. A disinfection was done to the entire incubator by

washing the insides of the incubator with soap and water, followed by sterilizing the

incubator by swabbing it with 70% ethanol to thoroughly decontaminate the incubator.

5.2.2.2 Unusual morphological conformations of SH-SY5Y cells

During the entire process of cell culturing, there were the inevitable and unpredictable

changes in the cells’ morphology encountered. In order to rectify such abnormal cell

conformations, consistent and regular renewal of culture medium was performed to provide

sufficient nutrients, growth factors and adherent factors to the cells. The renewal of medium

52

also allowed metabolites from accumulating alongside waste products that would be

inhibitory to healthy proliferation of the cells. Hence, it became apparent that an unhealthy

appearance and clumping of cells did not necessarily indicate the cells had undergone

apoptosis, but rather suggests renewal of medium was needed for healthy propagation of cells

instead.

5.2.2.3 High confluence

As cells divide and proliferate, they tend to utilize nutrients at a much faster rate for their

healthy growth and require more space to grow in the T25 flask. Thus, rapid depletion of

nutrients would curtail cell proliferation. At the same time, when there is not enough space

for the cells to grow, cells tend to crowd together, a phenomenon known as contact inhibition

may occur. Contact inhibition is a natural process of cell growth arrest when two or more

cells come into contact with one another. The arrest in the cell cycle would bring about

detrimental effects to the process culturing of healthy cells, and instead cause the cells to

undergo apoptosis ultimately. Hence, to overcome this problem, repeated sub culturing of the

cells were performed on flasks that reached confluence of 75% to 100%.

5.2.2.4 Enumeration of cells

During cell counting, it was observed at one point, in which the sample of cells being loaded

into the upper and lower hemocytometer chamber had a large variation. This may be due to

insufficient mixing of the sample of cells with trypan blue in the tube that resulted in a less

homogenized suspension. Hence, thorough mixing of cell suspension was performed before

loading the sample into the chambers to avoid future errors.

Other errors such as improper filling of chambers which could lead to inaccurate cell

counting were avoided by scrupulously cleaning the haemocytometer chamber and the cover

slip. The chamber and cover slip were cleaned first with distilled water, then by 70% ethanol

and wiped dry with a Kimwipe.

5.2.3. The determination of Cell Number required for MTT Assay

Since a higher MTT absorbance relates to higher cell viability, and higher viability relates to

more accurate results in subsequent MTT assays with BACE1 inhibitor compounds, an initial

cell seeding of 5x105 cells was more suitable than 1 x 10

6 cells. However, undifferentiated

cells were observed in culture.

53

This could be due to a multitude of factors. Firstly, there could have been a problem with the

process from cell culture to cryopreservation. It was possible that the cells provided had

compromised proliferation, perhaps because unhealthy or senescent cells were chosen for

cryopreservation. Not freezing the cells at a rate of -1oC per minute and rough handling of

cells could have had been the problem.

The effects of the compromised proliferation may not be visible in culture inside the T-25

flasks, which has a larger surface area and more media volume, but may have been more

profound while growing inside the 96-well plate, which had a much smaller surface area to

grow and had less media volume. The increased stress may have exerted pressure on the

growth of the cells and may have led to lower cell proliferation.

Secondly, there could have been a problem with the process from cryopreservation to

thawing. The techniques that were used in the first thaw (Frozen vial A) was impeached by

repeating the thawing procedures for two more vials of cryopreserved cells (Vials B and C),

while following protocols given by Invitrogen (Invitrogen, 2012). The cells thawed from the

two vials were shown below.

Figures 18 and 19: The photo in the left shows the cells from the first vial (Vial B) of the two inside a

T-25 flask with 5 mL of media in 5% CO2 while the one on the right show the second vial (Vial C),

also in similar conditions. Both images were taken at approximately the similar time after thawing

before subculturing was done.

The images show very low confluence, suggesting sparse growth, and masses of

undifferentiated cells, which already suggests senescence of cells prior to cryopreservation

(HPA, 2012). Media was changed every two to three days and was the exact same media

composition as the cells thawed from vial A. Since the methods were kept consistent with the

sparse growth of the cells thawed from vials B and C, the chances of the low negative control

54

absorbance faced in the MTT assay being connected with the thawing procedures were

unlikely.

As for comparison, the image below shows cells from vial A, which were growing healthily

in the same incubator and media at an earlier date, before it began to cease in differentiating.

A probable reason to explain why vial A had better morphology in the earlier stages of its

growth was probably because vial A was of better quality during cryopreservation compared

to vials B and C.

Figure 20: The cells from vial A, taken approximately at the same time as vials B and C after thawing.

The presence of neuronal morphology, fine cell processes and clear media suggests healthy cell

growth.

5.2.4. MTT assay

The MTT assay is a cell proliferation and viability assay and was used for the following

toxicological testing. The rate of tetrazolium reduction was proportional to the rate of cell

proliferation, and tetrazolium reduction produces a violet hue which can be determined

through fluorescence analysis, at the absorbance of 570nm. Higher violet hue equals to more

cell proliferation and viability.

55

MTT assay was done on all ten compounds to check for toxic effects on ATCC SH-SY5Y

cell viability after compound treatment and incubation for 24 hours. This was done to

investigate the cytotoxic effect of the compounds on the SH-SY5Y neuroblastoma cell line. If

any compounds exhibits high cytotoxic effects, the MTT assay would be able to identify and

visually see a range of concentrations where the cell would experience the toxic effects.

The test used to analyse the cell proliferation was the MTT assay. The rate of tetrazolium

reduction was proportional to the number of viable cells and tetrazolium reduction produces a

violet hue which can be determined through fluorescence analysis, at the absorbance of 570

nm. Higher violet hue equals to more cell proliferation and viability. This toxicological assay

aims to discover compounds that still retain 100% cell viability at their respective IC50

values.

5 x 104 cells were used as the initial SH-SY5Y cell number for the MTT assay, as the results

tabulated in 4.2.1. showed that the wells seeded with 5 x 104 cells produced more absorbance

at 570 nm than the wells seeded with 1 x 105 cells. This relates to more viable cells, and

therefore translates to more accurate results.

The inhibitor that had attracted the most interest in the enzyme-based assay was 9, with the

lowest IC50 value of 3.97 µM, which also shows that it was the most potent. SH-SY5Y seeded

as 5 x 104 cells exposed to 2.5 µM of 9 exhibited 100% viability in the toxicological assay.

However, the cells exposed to 10 and 5 µM of 9 showed 30.46 ± 8.565% and 46.17 ± 1.744%

viability respectively, which were both below 50% viability. This shows that 9 had safety

issues at these concentrations, but the safety at 3.97 µM, which was the IC50 of 9, cannot be

determined by these results alone.

If 9 was used as an AD treatment, it should not be used at a concentration greater than 5 µM.

The sudden drop in cell viability from 10 to 5 µM also suggests that could be a threshold

concentration which needs to be crossed for 9 before would be considered toxic to cells. As

stated in Results, the methyl at the X position of 9 formed a toluene with a benzene ring,

which was a toxic group. This could provide an explanation to the high cytotoxicity of 9 on

SH-SY5Y at 2.5 and 5 µM.

Few comparisons can be made between 3 and 9, which has similar groups at R but differed at

X. Compound 3 appeared to exert less cytotoxic effects on the SH-SY5Y cells at 10 and 5

µM according to table 6, but did not reach 100% viability at all concentrations. This confirms

56

our prediction that a toluene attached to the inhibitor is toxic to SH-SY5Y. However,

compound 3 also did not achieve sufficient potency in the initial screening to have its IC50

value measured.

As mentioned in Results, 1 has a much lower molecular weight (509.54) compared to 2

(553.59), so it was more likely to make it through the BBB. However, the toxicological assay

revealed that 1 was reducing cell viability of SH-SY5Y cells to about 50% at 10, 5 and 2.5

µM. This shows that 1, although it proved to be a relatively potent inhibitor compared to the

other compounds tested (IC50 = 5.65) together with a low molecular weight, it had a low

compatibility with a neural cell line like SH-SY5Y. This compound has potential safety

issues even at 2.5 µM, the lowest concentration and also presumably the safest on the cells.

Since 2.5 µM is lower than its IC50, it can be inferred that 1 can never achieve more than 50%

inhibition of BACE1 while showing no cytotoxic effects on SH-SY5Y.

Compound 10 also has the highest molecular weight of all the compounds, which makes it

hardest to penetrate the BBB, and was shown to have a high IC50, which correlates to a

weaker inhibitor. This compound was also shown to be cytotoxic to SH-SY5Y as it reduced

their viability to 50.00 ± 17.53% at 10 µM, which was very near its IC50 value (11.08 µM).

Therefore, this compound requires rectification in terms of safety, molecular weight and

potency to raise its potential to be developed into a drug lead.

Amongst compounds 3, 4, 5, 6 and 7, compound 7 had the strongest potency amongst all of

them (IC50 = 4.49 µM, initial screening = 72.27 ± 1.217%). Cells treated with 7 retained

100% cell viability even at 10 µM, which was much higher than its IC50. This was contrary to

9, which could not have its concentration increased beyond its IC50 value because it would

have not achieved 0% cytotoxicity. However, it can be said that although 9 cannot increase

its dose further than 2.5 µM in order to retain 100% cell viability, it is possible to increase the

concentration of 7 in order to reach inhibition levels much higher than its IC50. Compound 7

inhibits BACE1 at 103.80 ± 3.67% at 10 µM according to Table 3. This shows that 7 is a safe

and potent inhibitor.

However, the molecular weight of 7 was relatively high compared to 1, and therefore may

have problems passing the BBB. To test its ability to pass the BBB, polar surface area (PSA)

testing may be performed in future research and a value of less than 60 angstroms would be

required (Swahn et al., 2012). Another method that may be used is the MDR1 – MDCK assay

57

(Lerchner et al., 2010). Lipinski’s Rule of Five (ROF) method may be used in future research

to predict drug-like properties of this compound.

Amongst 3, 4, 5, 6 and 7, compound 5 had the weakest potency at % inhibition of 20.19 ±

0.7211%, and its effect on SH-SY5Y cell viability at 10, 5 and 2.5 µM were all under 100%.

Since the IC50 of 5 was not determined, the effect of cell viability at 50% BACE1 inhibition

cannot be determined reliably. However the only information that may be obtained here is

that at 3 µM, there was about 20% inhibition of BACE1, so at that level of inhibition, the cell

viability was not 100%. Assuming that cell viability decreases as more concentrations of 5

were exposed to them, and more of 5 equals to higher inhibition values, this compound would

never reach the level of 100% in vitro SH-SY5Y cell viability at its IC50 value, so therefore

has amongst the lowest possibility of being developed into a lead compound.

Compound 8 was unique for not having any elements present on the residues other than

aromatic rings at both R and X. The IC50 of this compound was found to be 12.02 µM, which

was relatively high and therefore not potent compared to other tested compounds. Cells

treated with 10, 5 and 2.5 µM of 8 did not retain 100% cell viability. Since the IC50 value of 8

was not in the range measured in the toxicological assay, the percentage of cell viability at its

IC50 cannot be determined reliably. However, assuming that an increase of its concentration

equals to both higher BACE1 inhibition levels and lower cell viability, it may also be

assumed that 8 cannot attain 50% inhibition at 100% in vitro SH-SY5Y cell viability. This is

also evidence that having only aromatic rings at both R and X is detrimental to the potency of

inhibitors against BACE1.

In conclusion, it was found that compound 7 shows no apparent cytotoxicity in the MTT

method on SH-SY5Y while at its IC50, while an increase to 10 µM increases its inhibition on

BACE1 to 100% while still not producing any visible cytotoxicity. Compound 9 shows a low

and potent IC50 but could not attain 100% inhibition of BACE1 at higher concentrations

because of cytotoxic effects measured in the MTT assay. Based on the correlation of low

potencies of compounds 8, 10 and 2 against BACE1 with large S3’ and S4’ sub-site binding

residues, it was hypothesised that both these sub-sites were of limited size while increasing

the size of the residues further would be detrimental to the inhibitor’s potency.

Compound 1 was slightly behind in terms of IC50 but its low molecular weight could have

advantages such as passing the BBB more efficiently, which is an important feature for a

brain-targeting drug. Upon cross-examination of both 9 and 1, the methyl group present at the

58

X position may be the cause of the high potency and high cytotoxicity based on comparisons

between these two compounds alone. Future researchers may consider the addition of methyl

at the S3’ interacting residue on the compound for potency improvements. Based on the

relationship between the low potency of 8 with the presence of only aromatic residues

interacting with both the S3’ and S4’ sub-sites, it was also hypothesised that having aromatic

rings alone in an inhibitor of BACE1 was detrimental to its potency.

A possible way to improve the binding efficiency of the compounds with BACE1 is the usage

of molecular docking softwares to increase their potency into the nanomolar range. PSA and

drug-like properties may be predicted by the ROF method in the future. Enzyme-linked

immunoabsorbent assay (ELISA) could be used to monitor the cleavage of APP by BACE1

in SH-SY5Y cells transfected with mammalian expression vectors (eg. pcDNA3.1)

containing APP genes (eg. APPwt or APPswe genes) (Jämsä, 2011).

6. Conclusion

AD incidences are predicted to increase along with the rise in the amount of people reaching

above 65 years old. Accumulation of Aβ in plaques is one of the main pathological features

of AD and is produced by BACE1 through sequential cleavage of amyloid precursor protein

(APP). The prevention of the plaque formation is believed to slow the progression of AD, and

therefore BACE1 is an attractive target for AD drug development. However, BACE1

inhibitors normally lack the potency and PK properties and are amongst the reasons for the

absence of BACE1 inhibitors in the market.

BACE 1 was treated with ten potential non-peptidomimetic inhibitors using FRET method,

and their initial screening results was obtained, followed by an IC50 assay to determine their

IC50 values, while a positive control compound was also assayed for its IC50 value for

comparison. A toxicology assay using the MTT method was conducted on all compounds to

test their effects on cell viability on a neuroblastoma cell line SH-SY5Y. The SAR of the

compounds was also studied.

Compound 9 showed the most potent IC50 value of 3.97 µM and subsequent SAR analysis

revealed that thienyl and toluene groups in the S4’ and S3’ sub-sites respectively were

responsible for the high potency of 9 but could increase cytotoxicity. Compound 7 is both a

safe and potent inhibitor compared to other compounds tested, with the next potent IC50 value

of 4.49 µM and SH-SY5Y cells retained 100% viability after treatment at 10 µM. Compound

59

1 has low molecular weight has been linked to the light methyl group found at the S3’ sub-

site, and has also been correlated in this study with high potencies of the inhibitor against

BACE1. However, it may also have led to the detrimental cytotoxic effects on SH-SY5Y

cells that both compounds 1 and 9 exhibited in the MTT assay.

Based on SAR studies on individual compounds, it also was hypothesised that the sub-sites

S3’ and S4’ were of limited size and increasing the size of the residues further would be

detrimental to the inhibitor’s potency. The presence of only aromatic residues interacting

with both the S3’ and S4’ sub-sites was also hypothesised to reduce the potency of the

inhibitor.

Compound 7 was the likeliest to be a drug lead for AD treatment because of its high potency

and diminutive cytotoxicity. Further studies on the SAR of the compounds would further

elucidate its potential as a potent inhibitor with even higher potency. A possible approach is

to improve the binding efficiency of the residues with BACE1 by utilising molecular docking

softwares and thereby, lowering the IC50 from micromolar to nanomolar range. In order to

confirm the correlation of its enzyme-based assay results with Aβ reduction, ELISA could be

used to monitor the cleavage of APP that results in an increase in the production of

Alzheimer causing Aβ peptides.

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8. Appendix

8.1. Compounds analysed in initial screening and IC50 assay

Compound Molecular Weight Molecular Formula

1 509.54 C28 H19 N3 O 5 S

2 553.59 C30 H23 N3 O6 S

3 549.63 C26 H16 F N3 O4 S3

4 589.62 C29 H20 F N3 O6 S2

5 585.68 C31 H24 F N3 O4 S2

6 573.62 C29 H20 F N3 O5 S2

7 559.60 C28 H18 F N3 O5 S2

8 575.67 C32 H21 N3 O4 S2

9 545.66 C27 H19 N3 O4 S3

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10 594.50 C28 H17 Cl2 N3 O4 S2

Table 7: The experimental numerical designations of the individual compounds tested in this

experiment.