AL Neelain University

Faculty of Pharmacy

Department of Pharmaceutical Chemistry

Identification of Potential Antidepressant Leads in Phoenix

Dactylifera.L Fruit: In-silico Study

A thesis submitted in partial fulfillment of the academic requirements for the

degree of Bachelor of pharmacy

Candidates

1- Batoul Abdelhafeiz Mohamed

2- Rawaa Abd Elfatah Awad Ali
3- Waad Salih Abd Elrahman Mohamed

Supervisor

Dr. Nafisa Abuobaida Osman

(B. Pharm., M. Pharm.)

Co supervior

Musab Yahia

(B. Pharm., M. Pharm.)

August, 2022
 ,

TABLE OF CONTENTS

TABLE OF CONTENTS .......................................................................................... II

LIST OF TABLES ...................................................................................................III

LIST OF FIGURES................................................................................................. IV

ABSTRACT .............................................................................................................. V

‫ المستخلص‬...................................................................................................................... VI

‫………………………………………………………………………………االية‬..VII

Acknowledgement................................................................................................... IX

1. INTRODUCTION .............................................................................................1

1.1 Introduction ...................................................................................................1

1.1.1 Mental illnesses...................................................................................1

1.1.2 Phytomedicine as source of drug discovery ....................................2

1.1.3 Problem statement .............................................................................2

1.1.4 Research question ..............................................................................3

1.1.5 hypothesis......................................... Error! Bookmark not defined.

1.1.6 Justification ........................................................................................3

1.2 Objectives ......................................................................................................4

1.2.1 General objectives ..............................................................................4

1.2.2 Specific objectives ..............................................................................4

2 LITERATURE REVIEW ..................................................................................5

 2.1 pathophysiology of depression ......................................................................5

2.2 Antidepressants: ............................................................................................6

2.2.1 MOAs inhibitor s................................................................................6

2.2.2 Tricyclic antidepressants ...................................................................7

2.2.3 Selective serotonin reuptake inhibitors ...........................................8

2.2.4 Atypical antidepressant drug bupropion ........................................9

2.2.5 Serotonin-norepinphrine reuptake inhibitors...............................10

2.2.6 serotonin partial agonist-reuptake inhibitor (SPARI):...............11

2.2.7 multimodal antidepressants : antidepressant drug vortioxetine.12

2.2.8 Antipsychotics in the treatment of depressive disorders: ............12

2.3 clinical aspect of conventional Antidepressant ...........................................13

2.4 herbal medicine and phytochemical based treatment approaches for

depression : ..........................................................................................................14

2.5 pharmacologycal effects of Phoenix dactylifera .........................................15

2.6 in-Silico Approaches in drug discovery and development .........................16

2.7 important termes in CAAD .........................................................................17

2.8 Successful Applications of In Silico Drug Design: ....................................17

3 MATERIALS AND METHODS.....................................................................18

3.1 Materials ......................................................................................................18

3.1.1 Biological targets and their PDB Codes.........................................22

3.1.2 Software,server,and database with their functions ......................22

3.2 Methodology ...............................................................................................23

II
 3.2.2 Pharmacokinetics,Drug likeness and Medicinal
chemistryfriendliness .....................................................................................25

3.2.3 Pharmacokinetic and Toxicity Prediction .....................................25

4 RESULT...........................................................................................................25

5 Discussion ........................................................................................................25

6 Conclusion and recommendations ...................................................................45

7 Reference .........................................................................................................46

LIST OF TABLES

Table 3-1 Phoenix dactylifera’s conistituents and their SMILES .....................18

Table 3-2Biological targets and their PDB Codes...............................................22
Table 3-3Software,server,and database with their functions ............................22
Table 4-1:hightest docking scores for each target ..............................................25
Table 4-2: ligands binding interaction with 5HT1a ............................................25
Table 4-3: ligands binding interaction with Seratonin Reuptake transporter 26
Table 4-4: ligands binding interaction with Alpha2 adrenergic recptor ..........28
Table 4-5: ligands binding interaction with MAO A ..........................................30

III
Table 4-6: Pharmacokinetise profile ...................................................................40
Table 4-7: Leadlikeness,druglikeness and synthetic accessibility .....................43

LIST OF FIGURES

Figure 3-1 Chemical strucures of Phoenix dactylifera constituents .................21

Figure 4-1Aripiprazole interaction with the target................................................32
Figure 4-2Epicatechin interaction with the target ................................................33
Figure 4-3 Luteolin interaction with the target..................................................33
Figure 4-4 Lutein interaction with the target .....................................................34
Figure 4-5Iproxetine interaction with the target ...............................................34
Figure 4-6:luteine intreraction with the target ..................................................35
Figure 4-7:Isofucosterol interaction with the target ..........................................35
Figure 4-8Quercetin interaction with the target ................................................36
Figure 4-9dexmedetomidine interaction with the target ...................................36
Figure 4-10Stegmasterol interaction with the target .........................................37
Figure 4-11B-sitosterol interaction with the target ...........................................38
Figure 4-12Isofucosterol interaction with the target .........................................38
Figure 4-132Phenylethylhydrazin interaction with the target ............................39
Figure 4-14B-sitosterol interaction with the target ...........................................39
Figure 4-15Campesterol interaction with the target .........................................40
Figure 4-16Isofucosterol interaction with the target .........................................40

IV
 ABSTRACT
Background: Major depressive disorder is a remarkably common and often severe
psychiatric disorder associated with high levels of morbidity and mortality patient
with major depressive disorder are prone to several comorbid psychiatric conditions
as well as medical conditions . in This study active compounds from date palm
fruits are computationally investigated looking for structurally diverse lead
compounds to contribute in Antidepressant drug Discovery.

Objectives: This study aim to identify the active compounds in date palm fruit that
contributes to its antidepressant activity computationally, and to evaluate the
pharmacokinetic properties using Swiss ADME web server, and to study the toxicity
profile of the candidate compounds using PKCSM web server.

Method: Molecular docking study was performed by Cresset Flare software on phoenix
dactylifera fruit. All Phoenix dactylifera’s constituents were docked against the target
proteins: , 5HT1a, Serotonin Reuptake transporter protein, Alpha2 adrenergic receptor,
MAO A, MAO B. Swiss ADME web server was used to predict Pharmacokinetics, Drug
likeness and Medicinal chemistry friendliness and PKCSM was used to study toxicity
profile.

Result: The top eight phytochemicals that have best scores are: Luteolin, Quercetin,
Lutein, Stigmasterol, Isofucosterol , Epicatechin , campesterol and B-sitosterol.

Conclusion: from the docking analysis result Luteolin,Quercetin,Lutein,Stigmasterol,

Isofucosterol,Epicatechin,campesterol and B-sitosterol are considerable lead compound
for antidepressant drug development.

V
 ‫المستخلص‬

‫خلفية ‪:‬يعد االضطراب االكتئابي الشديد امرا شائعا بشكل ملحوظ و في كثير من االحيان يرتبط بمستويات‬
‫عاليه من المرض و الوفيات كما ان مرضى االكتئاب معرضون للعديد من االمراض النفسيه االخري و كذلك‬
‫المراض عضويه عديده ‪.‬في هذه الدراسه تم فحص المركبات النشطه في ثمار نخيل التمر حاسوبيا بحثا عن‬
‫مركبات تجريبيه اوليه متنوعه هيكليا للمساهمه في اكتشاف ادويه مضاده لالكتئاب‬

‫أهداف‪:‬نهدف إلى التعرف على المركبات النشطة الموجودة في ثمرة نخيل التمر والتي تساهم في نشاطها‬
‫المضاد لالكتئاب حسابياً‪،‬وتقييم الخواص الدوائية باستخدام خادم الويب السويسري‪ ، ADME‬ودراسة ملف‬
‫سمية المركبات المرشحة باستخدام خادم الويب‪PKCSM.‬‬

‫الطريقه‪:‬تم إجراء دراسةةةةةةة االلتحام الجزيئي بواسةةةةةةطة برنامج ‪ Cresset Flare‬على فاكهة ‪Phoenix‬‬
‫‪dactylifera.‬تم ارسةةةةةةةاء جميع مكونةةات ‪ Phoenix dactylifera‬ضةةةةةةةد البروتينةةات المسةةةةةةتهةةدفةةة‪،‬‬
‫‪MAO ،Serotonin Reuptake transporter protein, Alpha2 adrenergic resptor, , ،5HT1a‬‬
‫‪ MAO B. ،A‬تم استخدام خادم الويب السويسري ‪ ADME‬للتنبؤ بالحركية الدوائية وتشابه الدواء ومالءمة‬
‫الكيمياء الطبية و تم استخدام ‪ PKCSM‬لدراسة ملف السمية‬

‫على أفضةةةل الدرجات هي‪:‬لوتولين‪ ،‬كيرسةةةيتين‪ ،‬لوتين‪،‬‬ ‫نتيجة‪:‬أفضةةةل ثمانية مواد كيميائية نباتية حصةةةل‬
‫ستيجماستيرول‪ ،‬إيزوفوكوسترول‪ ،‬إبيكاتشين‪ ،‬كامبستيرول و ب‪-‬سيتوستيرول‪.‬‬

‫من نتيجةةه تحةةاليةةل االلتحةةام وجةةدنةةا ان لوتولين‪ ،‬كيرسةةةةةةيتين‪ ،‬لوتين‪ ،‬سةةةةةةتيجمةةاسةةةةةةتيرول‪،‬‬ ‫االستتتتتتت تت‬
‫إيزوفوكوسةةترول‪ ،‬إبيكاتشةةين‪ ،‬كامبسةةتيرول و ب‪-‬سةةيتوسةةتيرول مركبات مرشةةحه لتطوير ادويه مضةةادات‬
‫االكتئاب‪.‬‬

‫‪VI‬‬
 ‫االيه‬

‫ٱش َربِي َو َق ِ ِّري ع َۡي ٗ ۖ َفإِ َّم تَ َريِنَّ ِمنَ ۡٱلبَش َِر َأ َحدٗ ا‬ ‫ي إ ِ َل ۡي ِك ب ِ ِج ۡذع ِ ٱل َّ ۡخ َل ِة ت ُ َٰ َ‬
‫س ِق ۡط َع َل ۡي ِك ُر َط ٗب َج ِ ٗيِّ ‪َ ٥٢‬ف ُك ِلي َو ۡ‬ ‫َو ُه ِِّز ٓ‬
‫ص ۡو ٗم َف َل ۡن ُأ َك ِِّلمَ ۡٱليَ ۡومَ إِن ِس ٗيِّ ‪٥٢‬‬ ‫َف ُقو ِل ٓ‬
‫ي إ ِ ِّنِي َن َذ ۡرتُ ِلل َّر ۡح َٰ َم ِن َ‬

‫‪VII‬‬
 Dedication

We wholeheartedly dedicate this work to our parents and beloved family members,
whose unwavering support has been a guiding light throughout our academic
journey. We extend a heartfelt shout out of dedication to our close friends and peers
in the Faculty of Pharmacy, whose camaraderie and encouragement have enriched
our learning experience.

VIII
 Acknowledgement

First and foremost, we express our gratitude to Allah. We extend our heartfelt thanks
to our supervisor, Dr. Nafisa , for her permission to conduct this research and for
providing invaluable guidance throughout the process in a highly supportive
environment. Additionally, Special recognition goes to Dr. Musab Yahia for his
dedicated efforts in simplifying the incorporation of manual tools into our work. Our
sincere appreciation also extends to all professors, faculty staff, and administrative
officers at the Faculty of Pharmacy, Al-neelain University.

IX
CHAPTER ONE

INTRODUCTION
 1. INTRODUCTION

1.1 Introduction

1.1.1 Mental illnesses

Mental disorders are serious health conditions that cause disturbances in
emotions, thinking or behaviors. They can be associated with problems that
hinder person’s life and productivity (1). The early years of the 21 st century have
witnessed a worldwide drop of mental illnesses and related disorders. In 2019,
970 million people worldwide were living with a mental disorder with anxiety
and depression being the most widespread mental health concerns (2)(3). There
is a proposed/suggested relationship between anxiety and depression as anxiety
often precedes the development of depression. This may be due to the
neurobiological link between anxiety, in particular generalized anxiety disorder,
and depression through the serotonin and norepinephrine systems activity (4)

1.1.1.1 Depression

Depression is a mental illness that adversely affects people’s feelings, thoughts,

and behaviors, as well as their physical health (5) the four most common types
of depression are major depression, persistent depressive disorder (dysthymia),
bipolar disorder, and seasonal affective disorder (6). in addition to types unique
to women ;Perinatal depression which includes major and minor depressive
episodes that occur during pregnancy or in the first 12 months after delivery
(postpartum depression)and Premenstrual disphoric disorder (6) generally The
main symptoms of depression include anhedonia, sadness,
Depressed mood, slow movements.(7) Major depressive disorder is a remarkably
common and often severe psychiatric disorder associated with high levels of
morbidity and mortality. for example the global estimated prevalence of

1
depression was 3.44%in 2017 Depression is mainly caused by the interaction of
genetic and environmental factors; however, the exact etiology and pathological
mechanisms of depression remain unclear.(8),(9)several hypotheses regarding
depression are discussed, and the widely accepted most important is monoamine
hypothesis which interpreted the mechanism of action of Antidepressants drugs .

1.1.2 Phytomedicine as source of drug discovery

In general, herbal medicines consist of tissues and unpurified plant extracts and
have some advantages, including low cost and fewer side effects.(10) For
thousands of years, hundreds of herbal medicines have been used to treat
patients with depression and have extensive clinical application.(11)These herbal
medicines, including TCM, Ayurvedic medicine, and Western herbalism, exert
therapeutic effects (clinically as monotherapy and complementary therapy) in
patients with mild-to-moderate depression. The efficacy and safety of these
herbal medicines have been demonstrated in relatively small groups of
patients.(12) Many preclinical studies have confirmed that similar to ketamine
and synthetic antidepressants, herbal medicines alleviate depression-like
behavior in animals and that the neurochemical changes in animals treated with
herbal medicines are consistent with those in animals treated with these synthetic
antidepressants.(13)

1.1.3 Problem statement

An ideal drug possesses optimal efficacy and tolerability. This is not the case for
antidepressants as the currently used drugs have suboptimal efficacy and
tolerability. In terms of efficacy they have delayed onset of action as they need
at least two weeks to produce beneficial therapeutic effect. During this period
about 2% of patients will die by suicide (14). Another drawback is that in
clinical practice, patient have to continue using relatively high doses for at least

2
2-5 years, during which they will experience side effects. In addition to the issue
of side effects, the long term use may lead to premature drug discontinuation and
failure of therapy. This, in total affects patient social, family and work quality of
life. Although current pharmaceutical treatments are often efficacious, they may
cause undesirable side effects including cognitive decrements and withdrawal
symptoms.

1.1.4 Research question

I. What is/are the active constituents of Phoenix dactylifera L. fruit that
contributes to its antidepressant activity?
II. How does Phoenix dactylifera L. fruit exert its antidepressant effect at a
molecular level?)
III. How safe are these Phytochemicals?
1.1.5 Hypothesis
On a Molecular Level Basis Phytochemicals of Phoenix dactylifera L (Date
Palm) fruit Exerts Antidepressant Effects.

1.1.6 Justification
The search for effective and safe anti-depressant has become a need so this
computational study will help to identify not only natural, novel, potentially
active and safe leads, but also structurally diverse drug candidates from Phoenix
dactylifera L. that can be further developed into ideal antidepressants with
reduced side effects for better quality of life for patients.

3
1.2 Objectives

1.2.1 General objectives

I. To identify the active compounds in date palm fruit that contributes to its
antidepressant activity computationally.
II. To evaluate the pharmacokinetic properties and toxicity of the candidate

1.2.2 Specific objectives

I. To identify the active constituents of date palm fruit computationally.
II. To suggest the mechanism of action by which the active constituents of
date palm fruit exert their effect.
III. To quantify the binding energies of the active constituents
IV. To predict the acute oral toxicity and pharmacokinetic properties of the
candidate compounds.
 CHAPTER TWO

LITERATURE REVIEW
 2 LITERATURE REVIEW

2.1 Pathophysiology of depression

as mentioned monoamine hypothesis represents the most important and most

popular hypothesis in context of depression pathology The core of the
monoamine hypothesis is that Serotonin and norepinephrine circuits arise in the
most ancient parts of the brain, in the raphe nuclei and the pons, respectively, and
send widespread projections to the forebrain, where they exert control over a wide
variety of physiological functions, many of which are awry in major depression,
including appetite, libido, concentration, and mood. In addition, dopamine
mediates the primary, perhaps pathognomonic, symptom of depression, namely,
anhedonia. Depletion of these monoamines in laboratory animals with drugs such
as reserpine or more selective agents that destroy serotonin or norepinephrine
neurons leads to depressive-like symptoms in animals. Hundreds of published
reports documented relative reductions of these neurotransmitters or their
metabolites in CSF, blood, or urine of patients with major depression, and
postmortem studies often supported these findings (15). Effective antidepressants
were shown to act primarily on these circuits as reuptake inhibitors, thereby
increasing the availability of these neurotransmitters in the synapse to further
stimulate postsynaptic receptors. These observations, coupled with results of both
depletion and provocative clinical studies such as the blunted growth hormone
response to adrenergic and dopaminergic agonists in patients with major
depression, supported these views (16). other hypothesis includes The
hypothalamic–pituitary–adrenal (HPA)axis (17),The neuroinflammation
hypothesis(18) and The neurotrophic theory (19). In addition to the above
hypotheses, the glutamate hypothesis, epigenetic theory, and circadian rhythm
play important roles in depression and the effect of antidepressants.(20)
5
According to the above mentioned hypotheses of depression, currently available
antidepressants mainly target the monoamine system to alter serotonin (5 HT),
norepinephrine, and dopamine levels in the brains of patients with depression(21).
Here most important Antidepressants class with their mechanism of action,
clinical applications and/or evaluations.

2.2 Antidepressants:

2.2.1 MOAs inhibitor s

iproniazid was the first successful pharmacological treatment for depression
and is classified as a MAO inhibitor (22). MAO is an enzyme that produces
oxidative dissemination (or break down) of biogenic amines (e.g. serotonin,
dopamine, epinephrine, and norepinephrine) and sympathomimetic amines (e.g.
tyramine, benzylamine, etc) (23), There are two isoenzymes, MAOA and
MAOB, MAOA is primarily responsible for the enzyme activity for the
deaminate of serotonin, melatonin, noradrenaline, and adrenaline (24).In
contrast, MAOB is responsible for enzyme activity for the breakdown of
phenethylamine and benzylamine (24)Interestingly, both isoenzymes deaminate
dopamine, tyramine, and tryptamine. M AOs responsible for the breakdown of
biogenic amines are located in the presynaptic terminal (25). A result of
inhibiting MAO is that monoamine neurotransmitter concentrations increase in
the presynaptic terminal and are readily available for release when action
potentials reach the nerve terminal .Iproniazid is a non-selective irreversible
MAO inhibitor, which led to safety concerns (e.g. hypertensive crises), and
ultimately led to the removal of iproniazid from the US market (26). One
example of the safety concern was termed the “cheese reaction.” The
combination of foods containing high amounts of tyramine, such as cheese or

6
dairy products, and MAO inhibitors, which increase concentrations of tyramine
and norepinephrine in the sympathetic nervous system, would lead to increased
heart rate, hypertension and sweating. It was later determined that inhibiting
MAOA was functionally involved in the antidepressant effects of MAO
inhibitors (26).In an attempt to improve the safety of MAO inhibitors, drug
development has focused on reversible and selective MAOA inhibitors (e.g.
moclobemide [Manerix®] and brofaromine [Consonar®]);a meta-analysis
revealed that the reversible inhibitor of monoamine oxidase type A (RIMAs)
moclobemide was as effective as SSRIs, nonselective MAO inhibitors and
TCAs for depressive symptom reduction. Additionally, moclobemide was
generally well tolerated with the most common side effect (27).

2.2.2 Tricyclic antidepressants

the prototype of this class is Imipramine (Tofranil®) it was approved in 1959 by
the Food and Drug Administration (FDA) for the treatment of MDD, which
established the class of drugs called tricyclic antidepressants (TCA); The
classification of TCAs was based on the three benzene ring molecular core, in
part, because the mechanism of action was unknown at the time of discovery.
Thus, the classification of TCAs differs from other classes of antidepressant
drugs, which are classified based on their mechanism of action (28).TCAs have
a diverse pharmacological profile with significant pharmacological action at two
reuptake transporters and three receptor proteins: inhibiting presynaptic
norepinephrine reuptake transporters; inhibiting presynaptic serotonin reuptake
transporters; blocking postsynaptic adrenergic α1 and α2 receptors; blocking
postsynaptic muscarinic receptors; and blocking postsynaptic histamine H1
receptors(29)(30).The inhibitions of norepinephrine and serotonin reuptake at
the transport proteins are thought to be responsible for the therapeutic effects of

7
TCAs and result in increased concentrations of norepinephrine and serotonin in
the synaptic cleft, respectively (31). The selectivity for norepinephrine or
serotonin transporters depends on the compounds; however, as most TCAs are
more selective for the norepinephrine transporter over the serotonin
transporter(32)on the other hand TCA present considerable affinity to several
neurotransmitters receptors including muscarinic cholinergic, adrenergic and
histaminergic which conferred them a side effect profile ,Thus, their affinity for
muscarinic cholinergic receptors may induce blurred vision, dry mouth,
constipation, urinary retention, seizures or memory impairment; histaminergic
receptor antagonism can produce sedation or drowsiness and the blockade of a1-
adrenergic receptors is associated with cardio toxicity effects, including
tachycardia, orthostatic hypotension and dizziness (33).

2.2.3 Selective serotonin reuptake inhibitors

Discovery and development of the selective serotonin reuptake inhibitors mark a
milestone in neuropharmacology. Drugs from this class potentiates serotonin
action through the negative allosteric modulation of its neuronal uptake by it
transporter. Fluoxetine the prototype of this class was FDA approved in 1987
it's adverse effect profile was far superior to that of any other available
antidepressant because of its selectivity for serotonin transporter (34).Other
SSRIs were soon introduced to the market although the efficacy of the SSRIs is
comparable to that of the TCAs, the SSRIs have significantly fewer side effects
(35) so improved tolerability of the SSRIs is attributable to their selectivity and
to their absence of interaction with other receptors, such as histaminic,
cholinergic, dopaminergic, and noradrenergic despite their improved side effects
profile compared to those of TCA and MAO SSRI's show delayed onset of
8
action between (4-6) weeks and only about 65% of patients respond to treatment
(36) moreover Serotonin receptors comprise at least 7 classes, which are further
divided at the sub receptor level٫ These receptors mediate a variety of functions
unrelated to mood, including sleep, appetite, and sexual function, as well as
symptoms such as pain, nausea, depression, and anxiety.(37) By increasing the
inhibition of serotonin reuptake, more of the neurotransmitter is available to
interact with any of these receptors or subtype receptors. Therefore, most SSRI
side effects are dose related and can be attributed to serotonergic effects. For
example, nausea, a common side effect of SSRI therapy, most likely results from
stimulation of 5-HT3 receptors and can usually be alleviated by reducing the
dose of the In contrast, fluoxetine-induced skin reactions are not dose related and
apparently are idiosyncratic. There are some differences in the adverse effect
profiles of the available SSRIs generally Gastrointestinal (GI) disturbances are
the most frequently reported side effects.10 Individually, post marketing
surveillance studies suggest that fluvoxamine is associated with the highest
frequency of GI disturbances, while anxiety, agitation, and insomnia are most
often reported with sertraline and fluoxetine. (38) (39)Overall, citalopram
appears to be the best-tolerated SSRI (40), followed by fluoxetine, sertraline,
paroxetine, and fluvoxamine ;The latter 2 drugs are associated with the most side
effects and the highest discontinuation rates because of side effects in clinical
trials(41) During long-term SSRI therapy, the most troubling adverse effects are
sexual dysfunction, weight gain, and sleep disturbance (42).

2.2.4 Atypical antidepressant drug bupropion

Bupropion is an “atypical” antidepressant drugs belonging to a unique chemical
class (aminoketone) and its binding profile is very different from other
antidepressant drugs (i.e. TCAs, SSRI, SNRI). it's primarily a dopamine-

9
norepinephrine reuptake inhibitor and displays its highest binding affinity for
dopamine transporters at least two fold more selective for dopamine transporters
as compared to norepinephrine transporters (43)Additionally, bupropion displays
minimal or no binding affinity for serotonin transporters or other pre- and
postsynaptic receptors (44). Clinical research has shown that bupropion is as
efficacious as other antidepressant drugs for the treatment of MDD and is well
tolerated with the three most frequent side effects of bupropion being dry mouth,
nausea, and insomnia (45). Furthermore, bupropion has the lowest risk of sexual
dysfunction (nearly half) as compared to TCAs, MAOIs, SSRIs, and SNRIs (
46).

2.2.5 Serotonin-norepinephrine reuptake inhibitors

Venlafaxine, was introduced to the United States market in 1993, and this drug
selectively targets the serotonin and norepinephrine transporters. The immediate
release form of venlafaxine (Effexor®), a serotonin norepinephrin reuptake
inhibitors (SNRI), was approved by the FDA for the treatment of MDD in 1993
and in 1997 the extended release form of venlafaxine was also approved for
MDD (47). Since the approval of venlafaxine, several other SNRIs (e.g.
duloxetine [Cymbalta®] and milnacipran [Savella®]) have been approved for
the treatment of MDD. SNRIs are similar to TCAs in that SNRIs inhibit the
reuptake of serotonin and norepinephrine at the serotonin and norepinephrine
transporters, respectively (48). Unlike TCAs, SNRIs have minimal or no
pharmacological action at adrenergic (α1, α2, and β), histamine (H1),
muscarinic, dopamine, or postsynaptic serotonin receptors (49). There is some
evidence that suggests SNRIs may be more effective for the treatment of MDD
as compared to SSRIs; however, these differences are relatively modest (50).

10
The clinical tolerability and the prevalence of sexual dysfunction of SNRIs are
comparable with other antidepressant drug treatments (51).
2.2.6 serotonin partial agonist-reuptake inhibitor (SPARI):
Vilazodone, introduced in the US in 2011, has been described as the first
member of the serotonin partial agonist-reuptake inhibitor (SPARI) class of
medications, combining serotonin-reuptake inhibition with 5-HT1A partial
agonism(52) , so It has a generally similar mechanism of action to existing
drugs as it increases 5HT concentration by two ways inhibiting reuptake and
decreasing negative feedback effects of 5HT1a auto receptors (53).vilazodone
could be useful for patients with primary anxiety-disorder diagnoses, such as
generalized anxiety disorder, social phobia, and panic disorder Also, it is
possible that some nonresponders to SSRIs and SNRIs will respond to
vilazodone: some such individuals may have abnormalities of 5-HT1A function
that are not addressed by reuptake inhibition of serotonin or norepinephrine (54).
The 5-HT1A partial agonism of vilazodone may indeed have benefits for
particular subgroups of patients, as suggested based on pharmacological
hypotheses (55)and animal data (56)However At this point, vilazodone cannot
be recommended as a first line drug for treatment of depression, primarily for
cost reasons and (57)despite theoretical advantages of SPARI drugs, such as
more rapid onset of action, more complete response (58) or fewer side effects
(59) but these actions have not been strongly supported to date in published
studies Furthermore, data for superiority in subpopulations (such as depression
with high anxiety or anxious distress) or fewer side effects (such as sexual
dysfunction) is not convincing. Therefore, there does not yet appear to be a
compelling case for use of vilazodone as a first-line antidepressant drugs (57).

11
2.2.7 Multimodal antidepressants : antidepressant drug vortioxetine
In September 2013, vortioxetine (Brintellix®) was the most recent
antidepressant drug approved by the FDA for the treatment of MDD. Belongs to
the piperazines chemical class and has been marketed as a “multi-modal” drug
because vortioxetine displays high binding affinity and complementary
mechanisms of action for several serotonin receptors (i.e. 5-HT1A, 5-HT1B, 5-
HT3A, 5-HT7, and serotonin transporters). Specifically, vortioxetine is a
serotonin 5-HT1A receptor agonist, 5-HT1B receptor partial agonist, 5-HT3A
and 5-HT7 receptor antagonist, and a potent serotonin reuptake inhibitor
(60)(61) but it has not been determined whether the antidepressant effects of
vortioxetine are related to its binding at various 5-HT receptors.,(62)
Vortioxetine has considerable receptor affinity for dopamine and norepinephrine
transporters; however, vortioxetine is approximately 3 to 12 times more selective
for serotonin transporters as compared to dopamine and norepinephrine
transporters, respectively (60). The clinical efficacy and tolerability of
vortioxetine is comparable to other antidepressants (63) with the most common
side effects being nausea and headaches(64).Vortioxetine appears to have a low
risk for sexual dysfunction and weight gain (65 )(66). It is important to note that
clinical (67) and preclinical (68) (69) studies have shown that vortioxetine may
help improve cognitive functioning.

2.2.8 Antipsychotics in the treatment of depressive disorders:

Antipsychotics have long been used in the treatment of depressive disorders. The
treatment effect of phenothiazines was found to be similar to that of tricyclic
antidepressants (70) but the side effects of using antipsychotics (extrapyramidal
symptoms [EPS], tardive dyskinesia [TD], neuroleptic malignant syndrome
[NMS], etc.) decreased interest in using monotherapy antipsychotics to treat

12
 depression. Neverth killeless, combined treatment with antidepressants and
antipsychotics became the treatment of choice for depressed patients who had
psychotic symptoms as part of their depressive disorder(71) The range of
patients given combined treatment with antidepressants and typical (first
generation) high-potency antipsychotics gradually increased to include those
whose depressive disorders were severe, intense, or accompanied with psychotic
symptoms(72) Overtime typical antipsychotics were replaced by atypical
(second generation) antipsychotics because of their lower rates of EPS and TD,
and their less severe cognitive impairment. At present, atypical antipsychotics
are used in combination with antidepressants to treat psychotic depression(70)
(71)to improve the efficacy of antidepressants for treatment-resistant depression
(73) in Pharmacological prospective atypical antipsychotics share the property
of effectively blocking 5-HT2A receptors, more potently so than D2 receptors,
by definition.(74)Although selectively blocking this receptor subtype may
contribute to a mild antidepressant action, as evidenced by the clinical action of
the 5-HT2 antagonist ritanserin,(75) (76)potent blockade of the 5-HT2A receptor
subtype in the presence of reuptake inhibition of 5-HT produced initially
unsuspected biological actions.(77) (78).

2.3 Clinical aspect of conventional Antidepressant

It has clearly been demonstrated that depressive disorders constitute a major

worldwide public health problem, with massive economic and quality-of-life
consequences and unfortunately monotherapy, even optimized by dosage and
duration, results in remissionin only a minority of patients (79) so Existing
pharmacological treatments have limited efficacy, with only about a third of
patients achieving remission on any one medication. Delayed onset of action and
variable tolerability contribute to this limited efficacy.In view of the failure of
13
monotherapy to achieve remission in the majority of patients with major
depression, a number of augmentation and combination strategies have been
applied.These include a host of atypical antipsychotics, such as olanzapine,
quetiapine, aripiprazole, brexpiprazole, risperidone, and others, some FDA-
approved for this purpose (80). Other agents have also been reported to be
effective in this regard, including thyroid hormone (T3), pimavanserin (a
serotonin inverse agonist), pramipexole (a D2/D3 agonist), ketamine and
esketamine, brexanolone, estrogen (in perimenopausal women), and an increasing
number of psychedelic drugs, such as psilocybin (81)(82)(83)(84)(85). Then of
course there are the combination therapies including SSRIs and other
antidepressants, most notably bupropion, venlafaxine, or mirtazapine (86).All of
these strategies are backed by evidence that among patients with major
depression who have failed to benefit from SSRI or SNRI monotherapy, some
percentage will respond to augmentation or combination, but the effect sizes are
relatively small.(87)Frankly, none of the augmentation or combination therapies
provide robust effects in patients who are nonresponsive or partially responsive to
SSRIs or SNRIs Moreover, many of the augmentation strategies have significant
side effects, ranging from the weight gain with certain atypical antipsychotics to
the concerns of cost, drug abuse liability, and tachyphylaxis with esketamine (88)

2.4 Herbal medicine and phytochemical based treatment

approaches for depression :

Based on clinical data, herbal medicine exert an effective anti-depressant effect,

especially in patients with mild-to-moderate depression.(89)In addition, herbal
medicines have fewer side effects compared to synthetic antidepressants. In recent
decades, herbal medicines have been prescribed worldwide as complementary and
alternative medicines to treat depression.(90) in context isolated Phytochemicals
14
derived from herbs are known to decrease the risk of some severe disorders
including autoimmune and cardiovascular diseases as well as neurodegenerative
diseases. Indeed, popular polyphenols such as curcumin (91), ferulic acid
(92),proanthocyanidin (93), quercetin (94), and resveratrol (95) have shown potent
anti-inflammatory and antioxidant properties. These phytochemicals repeatedly
have demonstrated their neuroprotective effects, strongly suggesting that they can
improve the symptoms of depression.

over the decades many plants had been investigated for antidepressant activity
some preparations have been registered as a herbal medicine product in traditional
Herbal medicine directive for this purpose like Hypericum perforatum (st John
wort)(96) and many been under investigation for examples Rhodiola rosea
(97),Lavandula angustifolia (98) ,Nelumbo nucifera (99) and Phoenix dactylifera
.the last being our research focus.

2.5 Pharmacological effects of Phoenix dactylifera

Phoenix dactylifera (date palm) fruits are a good source of energy, vitamins, and a
group of elements like phosphorus, iron, potassium, and a significant amount of
calcium.(100)Dates contain vitamins and are widely used in folk medicine for the
treatment of various disorders like, memory disturbances, fever, inflammation,
paralysis, loss of consciousness and nervous disorders.(101)Several
pharmacological studies have been conducted on P.dactylifera and it has been
reported to have anti-inflammatory ;hepatoprotective and neuroprotective
activities(102), (103)Several researchers have also documented the antioxidant
property of P. dactylifera.(104),(105),(106) ,recently researches on CNS actions
for it have been conducted a study suggests that aqueous fruit extracts of P.
15
dactylifera may prove efficacious in ameliorating mercury-induced anxiety like
behavior and memory deficit in Wistar rats the study also recommend to explore
the potential of Phoenix dactylifera in the management of reactive oxygen
species-induced neurodegenerative diseases, such as Parkinson’s and Alzheimer’s
disease (107). another study concluded that aqueous extracts of miswak and date
palm have significant antidepressant-like effects on depression-like behaviors in
CUMS model in rats. Moreover, their combination has higher antidepressant-like
effects than either extract alone (108) in this study we aim to estimate the
antidepressant effect of Phoenix dactylifera by identifying and evaluating active
constituents that may contribute to it action using computational methods.

2.6 In-Silico Approaches in drug discovery and development

The realm of drug discovery has been significantly transformed by the integration
of computational techniques into the design process. Computer-aided drug design
(CADD) has emerged as a pivotal approach that harnesses the power of
computation to expedite the identification, design, and optimization of potential
therapeutic agents it's virtually construct, analyze, and modify molecular
structures using computational algorithms and simulations. By simulating
molecular interactions, predicting binding affinities, and understanding the
influence of physicochemical properties, CADD provides valuable insights that
guide researchers in making informed decisions at every stage of the drug
discovery pipeline. From molecular modeling techniques to data-driven
approaches, from ligand-based strategies to structure-based design
innovations,(109)

16
2.7 important terms in CAAD

Molecular Docking Algorithms predicts the binding orientations and binding

affinities of ligands within the active sites of target proteins.(110)These
algorithms sample different conformations and orientations of the ligand to find
the most energetically favorable binding mode. Docking algorithms employ
scoring functions that evaluate the interactions between the ligand and protein,
(110) considering factors such as van der Waals interactions, hydrogen bonding,
electrostatics, and solvation effects and Force fields are is mathematical equations
that describe the potential energy surface of a molecule, play a pivotal role in
molecular mechanics. Force fields encompass terms for bond stretching, angle
bending, torsion rotation, and non-bonded interactions (van der Waals and
electrostatic interactions). Parameters within force fields are derived from
experimental data and quantum mechanical calculations, allowing the prediction
of molecular structures and energies.(111)

2.8 Successful Applications of In Silico Drug Design:

Real-world case studies exemplify the tangible impact of in silico drug design on
successful drug discovery efforts are many and concerning CNS drug
development taking Rivastigmine (Exelon) as example : Rivastigmine is a
medication used to treat Alzheimer's disease(112). In silico methods were
employed to optimize the binding interactions between the drug and its target,
acetylcholinesterase. Computational analysis guided the modification of the drug's
structure to enhance its binding affinity and selectivity, leading to the
development of rivastigmine potent acetylcholinesterase inhibitor.

17
 CHAPTER THREE

MATERIALS AND METHODS

 3 MATERIALS AND METHODS

3.1 Materials

Table 3-1 Phoenix dactylifera’s conistituents and their SMILES

Molecule Name SMILES

Luteolin Oc1cc(O)c2c(c1)oc(cc2=O)c1ccc(c(c1)O)O
Quercetin Oc1cc(O)c2c(c1)oc(c(c2=O)O)c1ccc(c(c1)O)O
Apigenin Oc1ccc(cc1)c1cc(=O)c2c(o1)cc(cc2O)O
Catechin Oc1cc2O[C@H](c3ccc(c(c3)O)O)[C@H](Cc2c(c1)O)O
Epicatechin Oc1cc2O[C@H](c3ccc(c(c3)O)O)[C@@H](Cc2c(c1)O)
O
P-hydroxybenzoic Oc1ccc(cc1)C(=O)O
acid
Protocatechuic acid OC(=O)c1ccc(c(c1)O)O
Vanillic acid COc1cc(ccc1O)C(=O)O
Gallic acid OC(=O)c1cc(O)c(c(c1)O)O
Syringic acid COc1cc(cc(c1O)OC)C(=O)O
Cinnamic acid OC(=O)/C=C/c1ccccc1
O-coumaric acid OC(=O)/C=C/c1ccccc1O
P-coumaric acid OC(=O)/C=C/c1ccc(cc1)O
Caffeic acid C1=CC(=C(C=C1/C=C/C(=O)O)O)O
Ferulic acid COc1cc(/C=C/C(=O)O)ccc1O
Sinapic acid COc1cc(/C=C/C(=O)O)cc(c1O)OC
5-o-caffeoylshikimic O=C(O[C@@H]1CC(=C[C@H]([C@H]1O)O)C(=O)O)/
acid C=C/c1ccc(c(c1)O)O

18
 Cholesterol CC(CCC[C@H]([C@H]1CC[C@@H]2[C@]1(C)CC[C
@H]1[C@H]2CC=C2[C@]1(C)CC[C@@H](C2)O)C)C
Campesterol O[C@H]1CC[C@]2(C(=CC[C@@H]3[C@@H]2CC[C
@]2([C@H]3CC[C@@H]2[C@@H](CC[C@H](C(C)C)
C)C)C)C1)C
Stigmasterol CC[C@@H](C(C)C)/C=C/[C@H]([C@H]1CC[C@@H]
2[C@]1(C)CC[C@H]1[C@H]2CC=C2[C@]1(C)CC[C@
@H](C2)O)C
B-sitosterol CC[C@@H](C(C)C)CC[C@H]([C@H]1CC[C@@H]2[
C@]1(C)CC[C@H]1[C@H]2CC=C2[C@]1(C)CC[C@
@H](C2)O)C
Isofucosterol C/C=C(\C(C)C)/CC[C@H]([C@H]1CC[C@@H]2[C@]1
(C)CC[C@H]1[C@H]2CC=C2[C@]1(C)CC[C@@H](C
2)O)C
B-Carotine C/C(=C/C=C/C=C(/C=C/C=C(/C=C\C1=C(C)CCCC1(C)
C)\C)\C)/C=C/C=C(\C=C\C1=C(C)CCCC1(C)C)/C
Lutein C/C(=C\C=C\C=C(\C=C\C=C(\C=C\C1=C(C)C[C@H](
CC1(C)C)O)/C)/C)/C=C/C=C(/C=C/[C@H]1C(=C[C@
@H](CC1(C)C)O)C)\C

. .

p-hydroxybenzoic acid. Protocatechuic acid. Vanillic acid

19
 . .

Gallic acid. Syringic acid Cinnamic acid

. .

O-curmaric acid P-cumaric acid. Caffeic acid

. .

Ferulic acid. Sinapic acid 5-o-caffeoylshickmic acid

. .

Cholesterol Campesterol Stigmasterol

20
 . .

B-sitosterol. Isofucosterol B-carotene

lutein. Quercetin Leuteolin

Apigenin

Figure 3-1 Chemical strucures of Phoenix dactylifera constituents

21
3.1.1 Biological targets and their PDB Codes
Table 3-2Biological targets and their PDB Codes

Target BDB ID
5-HT1A) receptor 7e2z
Serotonin reuptake receptor 6w2c
Alfa2 adrenergic receptor 7eja
MAO B 2c66
MAO A 2bxr

3.1.2 Software, server, and database with their functions

Table 3-3Software, server, and database with their functions

Cresset Flare software Molecular Docking.

RCSP protein data bank web server To get the three dimensional structure
of biological targets.
PKCSM webserver Prediction of the Pharmacokinetic
properties and Toxicity
SuprPRED webserver Target prediction
Therapeutic Target Database A database to provide information
about the known and explored
therapeutic protein and nucleic acid
targets, the targeted disease, Pathway
information and the corresponding
drugs directed at each of these targets.

22
 SWISS ADME web server Prediction of Pharmacokinetics ,Drug
likeness and Medicinal chemistry
friendliness

Pubchem database Search chemicals by name, molecular

formula, structure, and other
identifiers.
Uniprot database Resource of protein sequence and
functional information.

3.2 Methodology

The phytochemical constituents of Phoenix dactylifera were obtained from

literature sources (113). The suprPRED target prediction web server was used to
screen the exact targets for each phytochemical, and the Therapeutic Target
Database (114) was utilized to establish the link between the predicted targets and
the disease. Additional targets were selected based on their association with
conventional antidepressant medications. The protein targets were downloaded in
PDB format from the RCSP protein data bank (115). Molecular docking was
performed to further validate the selected targets via Cresset Flare software (116)

3.2.1.1 Virtual Screening

In this study, the SUPERpred target prediction tool was utilized to identify
potential protein targets for compounds that may be effective in treating
depression. The SMILE name of each compound was entered into the tool, and
the corresponding proteins for this indication were selected. To confirm the
association between the proteins and the diseases, the proteins were browsed in

23
Therapeutic Target Database (114). were Uniprot IDs were obtained for receptors
that are considered successful clinical trial target in depression disease (117),
and), and The PDB codes were chosen according to the following criteria, the 3D
structure resolution equals or more than 2.5, The method by which the 3D
structure was obtained is x-ray crystallography or Cryo-electron microscopy EM
.The protein was bound to a ligand. The selected targets were docked in Cresset
Flare software (116) .

3.2.1.2 Molecular docking

3.2.1.2.1 Ligand preparation

The SMILE name of each compound was inserted into EXCEL sheet and saved as
CSV file then the file was inserted into Cresset Flare software. The compounds
were prepared with Cresset Flare software (116) using the accurate type
calculation method.

3.2.1.2.2 Target preparation

The protein targets identified through virtual screening were prepared for docking.
The 3D protein structures were obtained from the RCSP protein data bank (115)
downloaded as pdb format .The protein structures were prepared and minimized
using the default settings in Cresset Flare software (116).

3.2.1.2.3 Docking
The prepared proteins were then docked with the compounds using the Cresset
Flare software (116). The docking protocol was set to use the normal mode and
default parameters, and the grid box was defined according to the co-crystalized
ligand which was used as a positive control. The results are listed in table (4-1)

24
3.2.2 Pharmacokinetics, Drug likeness and Medicinal chemistry
friendliness
SWISS ADME (118) web server was used as a computational tool for
predicting various aspects of drug Pharmacokinetics The chemical structures of
phytochemical constituents were entered as smile name format .the possibility of
Phoenix dactylifera components being employed as a pharmacological potential
was predicted using the Lipinski ,Ghose ,veber ,Egan and MUegge filters on the
Swiss ADME web server (118) .the friendliness of medicinal chemistry was
predicted using lead likeness and synthesis accessibility. The results are listed in
table (4-7)
3.2.3 Pharmacokinetic and Toxicity Prediction
PKCSM (119) web server was used to predict the pharmacokinetic and toxicity
properties of the compounds identified through virtual screening and molecular
docking. The SMILE name of each compound was submitted into the server,
and the predicted properties, including Intestinal absorption , Human Vd(L/Kg) ,
Total clearance(mg/kg/day), CYP2D6 and CYP3A4, CYP enzymes Inhibition,
P-glycoprotein substrate, P-Gp1 or 11 Inhibition, AMES tox., hERG 1 OR 2
inhibition, Hepatotoxicity, Skin sensitization, Carcinogenicity, Human
maximum tolerated dose (mg/kg/day)

, Oral rat acute toxicity(mol/kg), Oral rat chronic tox.(mg/kg_bw/day Oral rat
chronic tox.(mg/kg_bw/day, were analyzed.

This analysis provide valuable insight into the safety and efficacy of the
compounds, which was used to further refine the selection of potential drug
candidates. The results of pharmacokinetic and toxicity are listed in table (4-6)

25
CHAPTER FOUR

RESULT
 4 RESULT
Table 4-1:hightest docking scores for each target
PROTINE LIGAND 1 LIGAND 2 LIGAND 3 REFRANCE

NAME (LF NAME LF NAME LF LF

VSSCOR VSSCO VSSCO VSSCO
NAME
E) RE RE RE

5- STIGMASTEROL -11.891 LUTEIN -11.876 CAMPESTEROL_ -11.840 Ritanserin -13.48

HYDROXYT
RYPTAMINE

2C

5-HT1A) EPICATECHIN -11.118 LUTEOLIN -11.116 LUTEIN -11.007 Aripiprazole -10.237

RECEPTOR -

SERTONIN LUTEIN -15.397 ISOFUCOSTEROL. -11.269 QUERCETIN -10.974 IPRAOXETINE -10.836

REUPTAKE

RESPTOR

ALFA2 STIGMASTEROL -10.464 B-SITOSTEROL -10.222 ISOFUCOSTEROL -10.177 Dexmedetomidine -6.507

ADRENERGI

C RECEPTOR

BETA1 CATECHIN -10.499 EPICATECHIN -10.047 APIGENIN -9.976 epinephrine -8.206

ADRENERGI

MAOA B-SITOSTEROL -9.226 CAMPESTEROL -9.668 ISOFUCOSTEROL -9.568 2PHENYLETHYLH -6.214

YDRAZINE

MAOB QUERCETIN -10.524 CATECHIN -9.810 LUTEIN -9.746 Rasagiline -8.665

analogue

Table 4-2: ligands binding interaction with 5HT1a

25
 Tested H bond AA Hydrophobic No.of
legand length residues interaction binding site
contributing with similarity
in H-bonds to
standered
ligand

Aripiprazole 2.0 ASN R386 - All

luteolin 1.8 ASP R116 PHE R362 no match

2.2 ALA R365

2.9 SER R190

1.9 VAL R117

2.8 CYS R120

2.9 ASP R116

Epicatechin 1.9 ASP R116 PHE R362 no match

3.0 CYS R120

2.3 ALA R365

2.0 SER R190

2.1 VAL R117

lutein 1.9 LEU R394 - no match

Table 4-3: ligands binding interaction with Seratonin Reuptake transporter

26
Tested legand H bond AA Hydrophobic No.of
length residues interaction binding
contributing with site
in H-bonds similarity
to
standered
ligand

IPRAOXETINE 2.0 TYR A95 TYR A176 ALL

2.0 THR A439 PHE A441

ILE A172

Quercetin 1.8 TYR A95 TYR A95 4

2.1 TYR A95 TYR A176

2.1 THR A439 ILE A172

2.1 THR A439

1.8 THR A439

isofucosterol 1.8 TRP A103 ILE A179 2

TYR A175

TYR A176

ILE A172

27
 PHE A341

TYR A95

LEU A99

Lutein -- ---- CYS A166 1

PHE A465

VAL A469

ALA A169

PHE A341

PHE A170

LEU A443

CYS A473

ILE A172

PHE A335

ARG A104

Table 4-4: ligands binding interaction with Alpha2 adrenergic recptor

Tested legand H bond AA Hydrophobic No.of
length residues interaction binding
contributing with site
in H-bonds similarity
to

28
 standered
ligand

Dexmedetomidine 2.4 PHE R427 PHE R427 ALL

TRP R402

CYS R132

PHE R406

TYR R409

PHE R405

Stigmasterol 2.0 THR R412 PHE R423 1

GLU R109

GLU R204

ILE R205

TYR R409

Isofucosterol 1.9 THR R412 PHE R423 1

ILE R205

GLU R204

TYR R409

ASP R207

VAL R212

29
 B-Sitosterol 2.0 THP R412 PHE R423 1

GLU R09

ASN R108

PHE R427

LYS R424

GLU R204

ILE R205

VAL R212

TYR R409

ASP R207

Table 4-5: ligands binding interaction with MAO A

Tested legand H bond AA Hydrophobic No.of
length residues interaction binding
contributing with site
in H-bonds similarity
to
standered
ligand

2PHENYLETHYLHYDRAZINE 2.1 PHE A108 TRP A116 ALL

30
 2.0 LEU A97 TYR A106

2.0 TYR A106 PHE A108

ACE A115

Isofucostrol - - TYR A121 1

TYR A124

TRP A116

TRP A128

ASN A125

Campestrol - - TRP A116 2

ACE A115

TRY A124

TRP A128

ASN A125

TRY A121

B-Sitosterol - - TRP A128 4

PHE A173

TRY A124

ACE A115

31
 TRY A121

TRP A116

PHE A108

ARG A109

VAL A210

All compounds against 5HT1a

Figure 4-1Aripiprazole interaction with the target

32
Figure 4-2Epicatechin interaction with the target

Figure 4-3 Luteolin interaction with the target

33
Figure 4-4 Lutein interaction with the target
All compounds against sertoninreuptake receptor

Figure 4-5Iproxetine interaction with the target

34
Figure 4-6:luteine intreraction with the target

Figure 4-7:Isofucosterol interaction with the target

35
Figure 4-8Quercetin interaction with the target
All compounds against Alfa 2 adrenergic receptor

Figure 4-9dexmedetomidine interaction with the target

36
Figure 4-10 Stegmasterol interaction with the target

37
Figure 4-11B-sitosterol interaction with the target

Figure 4-12 Isofucosterol interaction with the target

38
All compounds against MAO A

Figure 4-132Phenylethylhydrazin interaction with the target

Figure 4-14B-sitosterol interaction with the target

39
Figure 4-15 Campesterol interaction with the target

Figure 4-16 Isofucosterol interaction with the target

Table 4-6: pharmacokinetic profile

Phytochemical Intestinal Human Vd( Total
constituents absorption(human)%absorbed logL/Kg) clearance(mg/kg/day)

Luteolin 81.13 1.153 0.495

Quercetin 77.207 1.559 0.407

40
Lutein 89.781 -0.33 0.924

Stigmasterol 94.97 0.178 0.618

Isofucosterol 94.642 0.179 0.619

Epicatechin 68.829 1.027 0.183

B-sitosterol 94.464 0.193 0.628

Campesterol 93.405 1.132 0.536

Phytochemical CYP2D6 and CYP enzymes P-glycoprotein P-gp1 or 2

constituents CYP3A4 Inhibition substrate Inhibition
substrate

Luteolin No CYP1A2 Yes Non Inhibitor

CYP2A4

Quercetin No CYP1A2 Yes Non Inhibitor

Lutein CYP3A4 Non Inhibitor Yes P-gp2

Stigmasterol CYP3A4 Non Inhibitor No P-gp1

P-gp2

Isofucosterol CYP3A4 Non Inhibitor No P-gp1

P-gp2

Epicatechin No Non Inhibitor Yes Non Inhibitor

41
B-sitisterol CYP3A4 Non Inhibitor No p-gp1

p-gp2

Campesterol CYP3A4 Non Inhibitor yes p-gp1

p-gp2

Phytochemic AMEs hERG 1 Hepatotoxici Skin Human Oral rat Oral rat
al . tox Or 2 ty sensitizatio maximum acute chronic
constituents inhibiti n tolerated toxicity Toxicit
on dose (mol//kg y
(mg/kg/day ) (mg/kg
) bw/day
)

Luteolin No No No No 0.499 2.455 2.409

Quercetin No No No No 0.499 2.4711 2.612

Lutein No hERG 2 No No -1.068 3.491 2.572

Stigmasterol No hERG 2 No No -0.664 2.454 0.872

Isofucosterol No hERG 2 No No -0.653 2.553 0.89

Epicatechin No No No No 0.438 2.428 2.5

B-sitosterol No hERG 2 No No -0.621 2.552 0.855

Campesterol No hERG2 No No 0.587 2.076 0.951

42
Table 4-7: Leadlikeness,druglikeness and synthetic accessibility
Phytochemical Lipinski Ghose #violations Leadlikeness Synthetic
constituents #violations #violations Accessibility

Luteolin 0 0 0 3.02

Quercetin 0 0 0 3.23

Epicatechin 0 0 0 3.5

Isofucosterol 1 3 2 6.15

Campesterol 1 2 2 6.17

B-sitosterol 1 3 2 6.3

Stigmasterol 1 3 2 6.21

Lutein 1 3 2 6.15

43
CHAPTER FIVE

DISCUSSION

43
 5 Discussion
Although an abundance of research has been done on the pharmacology activity of
phoenix dactelfra (102), there are still a number of significant studies required to be
done, including identifying the target that influences its activity, comprehending its
mechanism of action, and evaluating its pharmacokinetics, safety, and likelihood of
becoming a drug. In order to develop new drugs with strong therapeutic activity and
safety, these investigations are necessary to include the plant in the development of
drugs .The SUPERpred target prediction tool (120) was utilized to determine the
targets. Molecular docking study was done using Cresset Flare software (116) and
Lead finder program embedded in it (121) The lead finder program (121) on Cresset
flare software (116) is characterized by the combination of genetic algorithm and
various optimization strategies leading to great efficiency and speed of calculations
(121) Moreover, pkCSM (119)and SwissADME web servers (118) were used to
predict the pharmacokinetics (ADME: Absorption, Distribution, Metabolism, and
Elimination), toxicity, and the drug-likeness probability. The total predicted targets
form the virtual screening with the highest probability that was validated by the
molecular docking were 4 targets and for each target three ligand having the highest
affinity score were selected . regarding the 2D interaction , concerning 5HT1a
receptor Epicatechin interact with 5HT1a by 5 hydrogen bonds three bonds with
ALA R365 ,SER R190 ,VAL R117 and two weak bonds with ASP R116,CYS R120
as well as one aromatic -aromatic bond with PHE R362 Figure 5-2 .Where luteolin
interact with 5HT1a by 6 hydrogen bonds three bonds with,611 SS6 VAL
R117 and ALA R365 and three weak bonds with ASP R116, SER R190 and CYS
R120 and similar to Epicatechin luteolin forms one aromatic -aromatic bond with

25
PHE R362 Figure 5-3. on the other hand Aripiprazole the reference molecule forms
one hydrogen bond with ASN R386 and with no hydrophobic interactions involved
Figure 5-1 similarly lutein interact with 5HT1a by one hydrogen bond with LEU
R394 and no hydrophobic interactions involved with the receptor Figure 5-4.
regarding binding with serotonin reuptake receptor lutein interact with it by
extensive hydrophobic contacts involving CYS A166,PHE A465,VAL A469,ALA
A169,PHE A341,PHE A170,LEU A443,CYS A473,ILE A172 and PHE A335
Figure 5-6 where Isofucosterol makes one hydrogen bond with THR R412 and
makes multiple hydrophobic contacts with ILE A179 ,TYR A175,TYR A176 ,ILE
A172, PHE A341, TYR A95 and LEU A99 Figure 5-7. Quercetin interact with five
hydrogen bonds two strong H-bond with TYR A95 and one strong H-bond with THR
A439 and two weak bonds with THR A439 .as well as two aromatic -aromatic bond
with TYR A95 and TYR A176 and hydrophobic contacts with ILE A172 Figure 5-
8.where Iproxetine interact with sertonin reuptake receptor by two hydrogen bonds
with TYR A95 and THR A439 as well as one aromatic -aromatic bond with TYR
A176 and have two salt bridge with TYR A95 and GLU A439 Figure 5-5.

Stigmasterol interacts with Alpha2 adrenergic receptor by one hydrogen bond with
THR R412 and multiple hydrophobic contacts with PHE R423, GLU R109, PHE
R427, LYS R424, GLU R204, ILE R205, TYR R409, VAL R212 Figure 5-10. and
B-sitosterol interacts with the same target by one hydrogen bond with THR R412,
and multiple hydrophobic contacts with PHE R423, GLU R109, ASN R108, PHE
R427, LYS R424, GLU R204,ILE R205, VAL R212, TYR R409, ASP R207
Figure 5-11.also Isofucosterol interacts with alpha2 adrenergic receptor by one
hydrogen bond with THR R412 and multiple hydrophobic contacts with PHE R423,
LYS R424, GLU R109, ASN R108, PHE R427,GLU R204, ILE R205, TYR R409,
ASP R207, VAL R212 Figure 5-12.Compared with the control ,dexmedetomidine
that interact by one hydrogen bond with PHE R427, and four aromatic-aromatic

44
bonds with PHE R427, TRP R402, PHE R405, and multiple hydrophobic contacts
with CYS R132, PHE R406, TYR R409, PHE R405, PHE R427 Figure 5-9 .
Regarding the interaction with MAO A, B-sitosterol interacts by multiple
hydrophobic bonds with TRP A128,PHE A173, TYR A124, ACE A115, TYR A121,
TRP A116, PHE A108, ARG A109, VAL A210 Figure 5-14, Likewise,
Campesterol interacts by multiple hydrophobic bonds with TRP A116, ACE A115,
TYR A124, TRP A128, ASN A125, TYR A121 Figure 5-15.Isofucosterol interacts
by multiple hydrophobic bonds with TRP A116, TYR A124, TRP A128, ASN
A125, TYR A121. Compared with the control Figure 5-16, Phenylethylhyydrazine
that interacts by two hydrogen bonds with LEU A97 and PHE A108, one week
hydrogen bond with TYR A106,one aromatic -aromatic bond with TRP A116
Figure 5-13.

When Epicatechin, Lutein and Luteolin interacted with 5HT1a the three ligands
exhibit different interactions with different amino acids within the binding site
Epicatechin and Luteolin have many H-bonds and this suggest stronger binding
where Lutein show one H-bond like Aripiprazole .looking to Lutein, Quercetin and
interactions with serotonin reuptake protein where Lutein having the highest score
this maybe attributed to the large numbers of hydrophobic contacts then comes
Isofucosterol weth less hydrophobic contacts one the other hand Quercetin and
Iproxetine have many in common interactions with Quercetin having much
hydrogen and hydrophobic bonds . when Stigmasterol, B-sitosterol and
Isofucosterol interact with alfa 2 adrenergic receptor the three ligands form one
hydrogen bond as the reference molecule Dexmedetomidine but with different
amino acid residue involved in the interactions and the intensity of hydrophobic
interactions for each amino acid residue contribute to its affinity score not the
number of amino acids making those interactions .for B-sitosterol ,Campesterol and
Isofucosterol interactions with MAO A three ligand lake H-bonds that are present

45
in there reference molecule instead they make more extensive hydrophobic bonds
and this is attributed to their larger structure and their non-polar nature . the three
ligand gaive binding affinity scores -8.944,-8.068 and -8.77 when docked against
MOA B suggesting that they have affinity to MAO B but they may be more selective
to MOA A than MOA B. consedering affinity scores the result suggest that
Isofucosterol , Lutein, B-sitosterol, Quercetin, Campesterol ,Stigmasterol,
Epicatechin and Luteolin are promising leads for antidepressant. Because the
pharmacological activity depends on both the pharmacokinetic and
pharmacodynamic characteristics. Furthermore, given the importance of drug safety,
drug-likeness probability evaluation, and synthetic accessibility (122)
pharmacokinetic characteristics and drug safety, drug-likeness were investigated;
the results reveals that Luteolin, Quercetin, Epicatechin, were found to be the best
constituents with good drug likeness and synthesis accessibility , followed by
Isofucosterol,Lutein,Campesterol,Stigmasterol, and ,B-Sitosterol respectively.
Moreover Lutein, Stigmasterol, Luteolin, Quercetin, Isofucosterol , Epicatechin,B-
sitosterol ,campesterol have high volume of distribution ,are not causing skin
sensitisation , nonhepatotoxic and they are not Ames positive and hence they are not
mutagenic.

46
 CHAPTER SIX

CONCLUSION AND
RECOMMENDATIONS

44
 6 Conclusion and recommendations

According to the result of pharmacodynamics, pharmacokinetics, safety and drug-

likeness prediction collectively Luteolin, Quercetin, Lutein, Stigmasterol,
Isofucosterol , Epicatechin , campesterol and B-sitosterol are the best Phoenix
dactylifera’s phytochemical constituent ;consequentiy we recommend the use of
them as a combined drug as they affect multiple target involved in antidepressant
effect we also recommend wet lab studies to validate the result.

45
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