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ANTIDEPRESSANT EFFECT AND THE POSSIBLE MECHANISM(S) OF 
ACTION OF SECONDARY METABOLITES FROM TRICHILIA 
MONADELPHA IN MURINE MODELS 
 
BY 
 
 
MENSAH JEFFREY AMOAKO 
(10281708) 
 
 
THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, 
LEGON IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR 
THE AWARD OF MPHIL PHARMACOLOGY DEGREE 
 
DEPARTMENT OF PHARMACOLOGY AND TOXICOLOGY 
JULY, 2016 
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DECLARATION
DECLARATION BY THE CANDIDATE
I hereby declare that this is the product of my own research undertaken under supervision and
has neither been presented in whole nor in part for another degree elsewhere. I am solely
responsible for any residual flaws in the work.
Signature……………………….. Date……/……/………….
Mensah Jeffrey Amoako (10281708)
DECLARATION BY SUPERVISORS
We hereby declare that the principal work and presentation of the thesis were supervised by
us in accordance with guidelines on supervision of thesis laid down by the University of
Ghana.
Principal supervisor
Signature…………………… Date……/……/………………
(Dr. Isaac J. Asiedu-Gyekye)
Co-supervisor
Signature…………………… Date……/……/………………
(Dr.  Kennedy E. Kukuia)
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ABSTRACT
Background: Current conventional antidepressant drugs have delayed onset of action,
significant adverse effects, are costly and about 30-40% of patients are non-responsive,
underscoring the need for alternative therapies for depression. Presently, no known scientific
evidence exists to support the efficacy of Trichilia monadelpha in depression treatment,
though used in Ghana in managing psychosis, epilepsy and mood disorders.
Aim: This study investigated the antidepressant effect of secondary metabolites extracted
from the stem bark of T. monadelpha and the possible mechanism(s) of action of the most
efficacious metabolite in murine models of depression.
Method: Powdered stem bark of T. monadelpha (4 kg) was sequentially extracted with
petroleum ether, ethyl acetate and 70% (v/v) ethanol and the extracts screened for
phytochemical constituents. A preliminary investigation using the Irwin test was conducted
before the antidepressant effect of the three extracts were investigated using the forced
swimming test (FST) and tail suspension test (TST). In a separate experiment, antidepressant
effect of the extracted secondary metabolites [alkaloids (ALK), flavonoids (FLV), saponins
(SAP), terpenoids (TER), tannins (TAN)] from the most efficacious extract was evaluated.
Furthermore, the most efficacious metabolite was assessed for rapid-onset of antidepressant
effect using the open space swim test and its mechanism(s) of action were investigated.
Results: The LD50 of all the three extracts was above 3000 mg kg
-1 in mice. All three
extracts (30-300 mg kg-1 p.o) showed dose dependent antidepressant activity in both FST
and TST (P< 0.001) with the hydroethanolic extract (HEE) showing the highest efficacy
(Emax = 80.55). The FLV, ALK and SAP (dose for the metabolites: 30-300 mg kg
-1 p.o)
extracted from HEE showed significant antidepressant effect (P < 0.001) in the FST and
TST with the ALK being the most efficacious (Emax = 76.40). The ALK (30-300 mg kg
-1
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p.o) exhibited rapid-onset of antidepressant effect  on day two of  treatment  and  sustained
it  throughout the  period  of  drug  treatment in the open space swim test. Pre-treatment
with para-chlorophenylalanine (a tryptophan hydroxylase inhibitor; 200 mg kg-1 i.p)
reversed the antidepressant effect of the ALK (30-300 mg kg-1 p.o) and cyproheptadine (a
5-HT2 receptor antagonist; 80 mg kg
-1, i.p) diminished its antidepressant effect, suggesting
possible allosteric enhancement of serotoninergic activity. Similarly, pre-treatment with α-
methyldopa (200 mg kg-1, i.p) and/or reserpine (1 mg kg-1 s.c) abolished the antidepressant
effect of the ALK indicating enhancement of noradrenergic activity. Pre-treatment with
-1
yohimbine (a selective α2-receptor antagonist; 3 mg kg , p.o) potentiated the antidepressant
effect of the ALK, suggesting inhibitory effect on α2-receptors. Pre-treatment with prazosin
1
(a selective α1- receptor antagonist; 3 mg kg
- , p.o) failed to reverse the effect of the ALK.
-1
Pre-treatment with D- serine (glycine/NMDA receptor agonist; 600 mg kg ,i.p) reversed the
antidepressant effect of the ALK while D-cycloserine (glycine/NMDA receptor partial
agonist) potentiated the anti-immobility effect of the ALK, suggesting inhibitory effect on
glycine/NMDA receptor complex. Antidepressant effect of the ALK was attenuated by pre-
-1
treatment with L-arginine (NOS substrate; 750 mg kg , i.p), however, a synergistic effect
was observed with the pre-treatment of L-NAME (a non-selective NOS inhibitor; 30 mg
-1 -1
kg ,i.p) and methylene blue (direct inhibitor of both NOS and sGC; 10 mg kg ,i.p)
implicating the involvement of L-arginine-NO-cGMP pathway. The ALK significantly
increased curling score in TST suggestive of enhancement of opioidergic activity.
Conclusion: The study showed that all three extracts had potent antidepressant activity. The
ALK extracted from HEE exhibited a rapid and sustained antidepressant effect and may act
via an interplay of noradrenergic, serotoninergic, glycine/NMDA receptor, L-arginine-NO-
cGMP nitric oxide and opioidergic pathways.
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DEDICATIONS
This work is dedicated to the Almighty God and to Department of Pharmacology and
Toxicology, University of Ghana, School of Pharmacy especially, my M.Phil colleagues Dr.
Mrs. Simstewa Nana Adjoa Agyapong and Miss Audrey Serwaa Bonsu.
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ACKNOWLEDGEMENTS
My sincere gratitude goes to the Almighty God for giving me the grace and strength to go
through this programme successfully.
I am also grateful to my family for the support and encouragement they gave me during the
period of study. The emotional, psychological and moral support from my parents, sister and
brother cannot be overlooked. May the good Lord richly bless you.
I also thank the Department of Pharmacology and Toxicology, School of Pharmacy,
University of Ghana, for the training, exposure and experience they offered me during my
postgraduate studies. I am exceptionally grateful to Dr. I. J. Asiedu-Gyekye and Dr. Kennedy
E. Kukuia for their excellent supervision, patience and dedication towards my training in
scientific research. To Dr. Mrs. Dorcas Osei-Sarfo, I say a very big thank you for guiding me
through the extraction and isolation aspects of my laboratory work. I also want to thank all
the teaching and non-teaching staff at the Department of Pharmacology and Toxicology and
other departments.
Finally, I appreciate the assistance of Madam Doris of the Centre for Plant Medicinal
Research –Mampong, for being there whenever I needed her. Thank you all very much. May
the good Lord continue to bless you.
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TABLE OF CONTENTS
Contents
DECLARATION ........................................................................................................................i
DEDICATIONS.........................................................................................................................ii
ACKNOWLEDGEMENTS..................................................................................................... iii
TABLE OF CONTENTS.........................................................................................................ivi
LIST OF FIGURES .................................................................................................................xii
LIST OF TABLES.....................................................................................................................ii
LIST OF ABREVIATIONS ...................................................................................................xvi
ABSTRACT ...........................................................................................................................xvi
CHAPTER 1 ..............................................................................................................................1
INTRODUCTION .....................................................................................................................1
1.1 BACKGROUND .............................................................................................................1
1.2 PROBLEM STATEMENT..............................................................................................5
1.3 JUSTIFICATION ............................................................................................................6
1.4 HYPOTHESIS .................................................................................................................7
1.5 AIM .................................................................................................................................7
1.6 SPECIFIC OBJECTIVES................................................................................................8
CHAPTER 2 ..............................................................................................................................9
LITERATURE REVIEW ..........................................................................................................9
2.1 Depression.......................................................................................................................9
2.1.1 Background ......................................................................................................................9
2.1.2 Classification of depresion.............................................................................................10
2.1.2.1   Severity ....................................................................................................................11
2.1.2.2 Duration ....................................................................................................................11
2.1.2.3 Course ......................................................................................................................12
2.1.3 Types of depression ....................................................................................................12
2.1.3.1 Bipolar depression .....................................................................................................13
2.1.3.2 Dysthymic disorder ....................................................................................................13
2.1.3.3 Disruptive mood regulation disorder ..........................................................................13
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2.1.3.4 Major depression ......................................................................................................14
2.1.3.4.1 Seasonal depression ................................................................................................14
2.1.3.4.2 Melancholic depression ...........................................................................................15
2.1.2.4.3 Atypical depression .................................................................................................15
2.1.4 Epidemeology of depression ....................................................................................15
2.1.5     Comorbidity of depression ........................................................................................17
2.2 Theoritical models of depression ................................................................................18
2.2.1 Biopsychosocial .........................................................................................................18
2.1.2.1  Biological ...................................................................................................................19
2.1.2.2 Psychological .............................................................................................................19
2.1.2.3 Social ..........................................................................................................................20
2.2.2 Psychodynamic ............................................................................................................20
2.2.3 Behavioural .................................................................................................................21
2.2.3.1 Behavioural activation ................................................................................................22
2.2.3.2 Social skills ..................................................................................................................22
2.2.3.3 Reinforcement contingency .........................................................................................22
2.3 Biological basis of depression ....................................................................................23
2.3.1 Neurochemical factors .................................................................................................23
2.3.1.1 Monoamine hypothesis ...............................................................................................23
2.3.1.2 Modification in GABA and glutamate neurotransmission ..........................................25
2.3.1.3 Nitric oxide and NMDA receptor complex ..................................................................27
2.3.2    Neuroplasticity and neurotrophic factors ....................................................................27
2.3.3 Neuroendocrine factors................................................................................................29
2.4 Antidepressant drugs ..................................................................................................30
2.4.1 History ........................................................................................................................30
2.4.2     Antidepressants and their mechanism of action..........................................................32
2.4.2.1 Monoamine oxidase inhibitors ....................................................................................32
2.4.2.2 Monoamine receptor antagonists.................................................................................33
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2.4.2.3 Monoamine reuptake inhibitors ..................................................................................34
2.4.2.4 Modulators and/or stimulators of monoamines ..........................................................37
2.4.2.5 NMDA receptor antagonists ........................................................................................37
2.4.2.6 Melatonin receptor agonists ........................................................................................38
2.4.2.7 L-arginine-NO-cGMP pathway ...................................................................................39
2.4.2.8 Opioid receptor agonists .............................................................................................39
2.5 Non-pharmacological treatment of depression ..........................................................40
2.5.1 Psychotherapy ................................................................................................................40
2.5.2 Electroconvulsive therapy ..............................................................................................41
2.5.3 Light therapy  .................................................................................................................42
2.6 Therapeutic benefits of some plant secondary metabolites .......................................42
2.6.1 Background ...................................................................................................................42
2.6.2 Antidepressant properties of some secondary metabolites of medicinal plants..............44
2.7 Animal models of depression .......................................................................................47
2.7.1 Acute models ..................................................................................................................47
2.7.1.1 Forced swimming test ..................................................................................................47
2.7.1.2 Tail suspension test .....................................................................................................47
2.7.2 Chronic model .............................................................................................................48
2.7.2.1 Open space swim test .................................................................................................48
2.8 Trichilia monadelpha ..................................................................................................49
2.8.1 Plant morphology .........................................................................................................49
2.8.2 Geographical profiling ................................................................................................50
2.8.3 Traditional uses ............................................................................................................50
2.8.3.1      Medicinal ...............................................................................................................50
2.8.3.2      Non-medicinal ........................................................................................................51
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2.8.4     Plant phytochemistry ..................................................................................................51
CHAPTER 3 ............................................................................................................................52
MATERIALS AND METHODS.............................................................................................52
3.1 Study design...................................................................................................................52
3.2 Plant acquisition and extraction ..................................................................................52
3.2.1 Plant acquisition and authentication ...............................................................................52
3.2.2 Preparation of stem bark extracts ..................................................................................52
3.3 Qualitative phytochemical analysis ...............................................................................53
3.3.1 Test for tannins ...............................................................................................................53
3.3.2 Test for glycosides .........................................................................................................53
3.3.3 Test for saponins ............................................................................................................53
3.3.4 Test for alkaloids ............................................................................................................53
3.3.5 Test for flavonoids .........................................................................................................54
3.3.6 Test for sterols ................................................................................................................54
3.3.7 Test for terpenoids ..........................................................................................................54
3.4 Animal husbandary ......................................................................................................54
3.5 Primary observation test .............................................................................................55
3. 6 Acute antidepressant models ......................................................................................55
3. 6.1 Tail suspension test ......................................................................................................55
3. 6.2 Forced swimming test ..................................................................................................56
3.7    Extraction of some secondary metabolites from the (hydroethanolic) most
effacious crude extract ..........................................................................................................57
3.7.1 Saponins .........................................................................................................................57
3.7.2 Alkaloids .......................................................................................................................57
3.7.3 Flavonoids ....................................................................................................................58
3.7.4 Terpenoids ....................................................................................................................58
3.7.5 Tannins .........................................................................................................................58
3.8 Acute antidepressant effect of the extracted secondary metabolites from the
hydroethanolic extract ..........................................................................................................59
3.8.1      Tail suspension test ...................................................................................................59
3.8.2      Forced swimming test  ..............................................................................................59
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3.9 Chronic antidepressant effect of the (total alkaloids) most efficacious secondary
metabolite .............................................................................................................................. 60
3.9.1 Open space swim test  .................................................................................................. 60
3.10 Possible mechanism of action of extracted total alkaloids .......................................60
3.10.1 Involvement of noradrenergic system .........................................................................60
3.10.2 Involvement of serotoninergic system ........................................................................62
3.10.3 Involvement of glycine/NMDA receptor complex .....................................................63
3.10.4 Involvement of L-arginine-NO-cGMP pathway .........................................................63
3.11    Statistical analysis ..................................................................................................... 64
CHAPTER 4 ............................................................................................................................65
RESULTS ................................................................................................................................65
4.1 Quantitative and qualitative analysis of crude extracts .........................................65
4.1.1 Yield of crude extracts ...................................................................................................65
4.1.2 Phytochemical test ........................................................................................................66
4.2 Irwin test ......................................................................................................................67
4.3 Acute antidepressant effect of crude extracts ...........................................................69
4.3.1 Tail suspension test .......................................................................................................69
4.3.2 Forced swimming test ...................................................................................................72
4.4 Qualitative analysis of extracted secondary metabolites ..........................................75
4.4.1 Yield of extracted secondary metabolites ......................................................................75
4.5 Acute antidepressant effects of extracted secondary metabolites ...........................76
4.5. Tail suspension test .......................................................................................................76
4.5.2 Forced swimming test ...................................................................................................80
4.6 Chronic antidepressant effect of extracted total alkaloids ........................................84
4.6.1 Open space swim test ....................................................................................................84
4.7 Mechanisms of action of extracted total alkaloids ....................................................87
4.7.1 Involvement of noradrenergic system ............................................................................87
4.7.2 Involvement of serotoninergic system ...........................................................................95
4.7.3 Involvement of glycine/NMDA receptor complex ........................................................98
4.7.4 Involvement of L-arginine-NO-cGMP pathway ..........................................................102
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CHAPTER 5 ..........................................................................................................................105
DISCUSSION, CONCLUSION AND RECOMMENDATION
5.1 Discussion....................................................................................................................105
5.2 Conclusion ..................................................................................................................122
5.3 Recommendations ......................................................................................................123
5.4 Limitation ...................................................................................................................123
REFERENCES ......................................................................................................................124
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LIST OF FIGURES
Figure 2.1: Trichilia monadelpha plant ...................................................................................49
Figure 4.1: Effects of extracts, fluoxetine and imipramine on the duration of immobility in
TST...........................................................................................................................................69
Figure 4.2: Effects of extracts, fluoxetine and imipramine on swinging scores in TST..........70
Figure 4.3: Effects of extracts, fluoxetine and imipramine on curling scores in TST ............71
Figure 4.4: Log dose-response curve of the extracts, fluoxetine and imipramine showing a %
decrease in immobility in TST in mice....................................................................................72
Figure 4.5: Effects of extracts, fluoxetine and imipramine on the duration of immobility in
FST...........................................................................................................................................73
Figure 4.6: Effects of extracts, fluoxetine and imipramine on swimming scores in FST........74
Figure 4.7: Effects of extracts, fluoxetine and imipramine on climbing scores in FST……...75
Figure 4.8: Log dose-response curve of the extracts, fluoxetine and imipramineshowing a %
decrease in immobility in FST in mice....................................................................................76
Figure 4.9: Effects of secondary metabolites, fluoxetine and imipramine on the duration of
immobility in TST....................................................................................................................78
Figure 4.10: Effects ofsecondary metabolites, fluoxetine and imipramine on swinging scores
in TST.......................................................................................................................................79
Figure 4.11: Effects of secondary metabolites, fluoxetine and imipramine on curling scores in
TST...........................................................................................................................................80
Figure 4.12: Log dose-response curve of the secondary metabolites, fluoxetine and
imipramine showing a % decrease in immobility in TST in mice...........................................81
Figure 4.13: Effects of secondary metabolites, fluoxetine and imipramine on the duration of
immobility in FST....................................................................................................................82
Figure 4.14: Effects of secondary metabolites, fluoxetine and imipramine on swimming
scores in FST............................................................................................................................83
Figure 4.15: Effects of secondary metabolites, fluoxetine and imipramine on climbing scores
in FST.......................................................................................................................................84
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Figure 4.16: Log dose-response curve of the secondary metabolites, fluoxetine and
imipramine showing a % decrease in immobility in FST in mice ..........................................85
Figure 4.17: Effects of alkaloid treatment on the duration of immobility and distance travelled
in the open space swim test .....................................................................................................86
Figure 4.18: Effects of fluoxetine treatment on the duration of immobility and distance
travelled in the open space swim test ......................................................................................87
Figure 4.19: Effects of bupropion treatment on the duration of immobility and distance
travelled in the open space swim test ......................................................................................87
Figure 4.20: Dose–response curves showing the effect of extract, fluoxetine and bupropion on
%  decrease  in  immobility  time  and %  increase  in  distance  travelled  in  the  open  space
swim test in mice......................................................................................................................88
Figure 4.21: Effects of pre-treatment of mice with α-MD on immobility scores of ALK, FLX
and IMI in TST and FST..........................................................................................................89
Figure 4.22 Effects of pre-treatment of mice with reserpine alone on immobility scores of
ALK, FLX and IMI in TST and FST ......................................................................................90
Figure 4.23 Effects of pre-treatment of mice with a combination of α-MD and reserpine on
immobility scores of ALK, FLX and IMI in TST and FST ....................................................91
Figure 4.24 Effects of pre-treatment of mice with a combination of α-MD and reserpine on
swimming and climbing scores of ALK, FLX and IMI in TST and FST ...............................92
Figure 4.25: Effect of pre-treatment of mice with prazosin on ALK, ATO and IMI induced
reduction in immobility time in the TST and FST...................................................................93
Figure 4.26: Effect of pre-treatment of mice with yohimbine on ALK, ATO and IMI induced
reduction in immobility time in the TST and FST...................................................................94
Figure 4.27: Effect of pre-treatment of mice with pCPA on ALK, FLX and IMI on
immobility score in the TST and FST .....................................................................................95
Figure 4.28: Effect of pre-treatment of mice with pCPA on ALK, FLX and IMI swimming
and climbing score in the TST and FST ..................................................................................96
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Figure 4.29: Effect of pre-treatment of mice with cyproheptadine on ALK, FLX and IMI
immobility score in the TST and FST .....................................................................................97
Figure 4.30: Effect of pre-treatment of mice with D-serine on ALK, FLX and IMI immobility
score in the TST and FST ........................................................................................................98
Figure 4.31: Effect of pre-treatment of mice with D-serine on ALK, FLX and IMI swimming
and climbing score in FST.......................................................................................................99
Figure 4.32: Effect of pre-treatment of mice with D-cycloserine on ALK, FLX and IMI
immobility score in the TST and FST....................................................................................100
Figure 4.33: Effect of pre-treatment of mice with D-cycloserine on ALK, FLX and IMI
swimming and climbing score in FST ...................................................................................101
Figure 4.34: Effects of pre-treatment of mice with L-arginine on ALK immobility time in the
TST and FST .........................................................................................................................102
Figure 4.35: Effects of pre-treatment of mice with L-NAME on ALK immobility time in the
TST and FST .........................................................................................................................103
Figure 4.36: Effects of pre-treatment of mice with methylene blue on ALK immobility time
in the TST and FST ...............................................................................................................104
Figure 4.37: Effects of pre-treatment of mice with sildenafil on ALK immobility time in the
TST and FST .........................................................................................................................105
Figure 5.1: A schematic representation of the proposed mechanism of action of ALK isolated
from HEE of the stem bark of T. monadelpha ..................................................................... 121
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LIST OF TABLES
Table 4.1. Percentage yield of crude HEE, EAE and PEE from the stem bark of Trichilia
monadelpha plant ....................................................................................................................65
Table 4.2. Preliminary phytochemical screening crude HEE, EAE and PEE from the stem
bark of Trichilia monadelpha ..................................................................................................66
Table 4.3. Observations in the acute toxicity test after oral administration of PEE, EAE and
HEE of Trichilia monadelpha in mice....................................................................................67
Table 4.4. ED50 and Emax values of extracts and test drugs used in TST and FST.................76
Table 4.5. Phytochemical screening and percentage yield of various secondary metabolites
extracted from crude HEE from the stem bark of Trichilia monadelpha................................77
Table 4.6. ED50 and Emax values of secondary metabolites and test drugs used in TST and
FST  .........................................................................................................................................85
Table 4.7. ED50 and Emax values of secondary metabolites and test drugs used in the open
space swim test ........................................................................................................................88
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LIST OF ABBREVIATIONS
ABBREVIATION DEFINITION
AC-cAMP-CREB Adenylate cyclase-cyclic adenosine monophsphate- cAMP
response element binding protein
ADHD Attention deficit hyperactivity disorder
ALK Alkaloids
AMPA Alpha-3-Hydroxy-5-Methoxy-4-Isoxazole Propionic Acid
ATO Atomoxetine
BDNF Brain derived neurotrophic factor
BUP Bupropion
CNS Central nervous system
CBT Cognitive behaviour therapy
CHD Coronary heart disease
cGMP Cyclic guanosine monophosphate
CRH 1 Corticotrophin releasing hormone 1
DNA Deoxyribonucleic acid
DMN Default mode network
DSM - IV Diagnostic and Statistical Manual for Mental Disorders
DMDD Disruptive mood dysregulation disorder
DA Dopamine
DAT Dopamine transporter
ECT Electroconvulsive therapy
EAE Ethyl acetate extract
FLV Flavonoids
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FLX Fluoxetine
FST Forced swimming test
GABA Gamma Amino Butyric Acid
GDNF Glial cell-line derived neurotrophic factor (GDNF)
HEE Hydroethanolic extract
5-HT 5-Hydroxytryptamine
HPA Hypothalamic-pituitary-adrenal
ICD - 10 International Statistical Classification of Diseases and Related
Health Problems
ICR Imprinting Control Region
IMI Imipramine
i.p Intraperitoneal
IPT Interpersonal psychotherapy
L-arg L- arginine
LDL-C Lipoprotein-cholesterol
L-NAME NG-nitro-L-arginine methyl ester
MRI Magnetic resonance imaging
mRNA micro Ribonucleotide acid
MDD Major depressive disorder
MAO Monoamine oxidase
MAOIs Monoamine oxidase inhibitors
MT Melatonin
NMDA N-methyl-D-aspartate
NO Nitric oxide
NOS Nitric oxide synthase
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NA Noradrenaline
NET Noradrenaline transporter
ODD Oppositional defiant disorder
pCPA Para-chlorophenylalanine
PEE Petroleum ether extract
PET Positron emission tomography
p.o Per os
SAP Saponins
s.c Subcutaneous
sGC Soluble guanylate cyclase
SNRI Selective noradrenaline reuptake inhibitors
SNDRI Serotonin–norepinephrine–dopamine reuptake inhibitors
SSRIs Serotonin reuptake inhibitors
SERT Serotonin transporter
SZS Semen Zizyphi sponosae
TAN Tannins
TCAs Tricyclic antidepressants
TER Terpenoids
TRIs Triple reuptake inhibitors
TST Tail suspension test
XBXT Xiao Bu Xin Tang
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CHAPTER ONE 
INTRODUCTION 
1.1 BACKGROUND 
Over the years, traditional medicines have been widely used throughout the world in disease 
prevention and treatment. Traditional medicine is the totality of knowledge, skills, and practices 
based on the theories, beliefs, and experiences native to diverse cultures that are used to avert, 
diagnose, or treat physical and mental illnesses (Mahomoodally, 2013). It is often an 
underestimated form of health delivery and may be termed complementary medicine whilst often 
practiced on empirical basis (W.H.O., 2013). Nearly 80% of the global population relies on 
traditional medicine to cater for their health needs (Buvaneswari et al., 2011), whilst close to 
70% of Africans depend on some form traditional systems of healthcare. The recent renaissance 
observed in the use of traditional medicines can be attributed to historical, socio-economic and 
cultural belief systems particularly in rural areas. 
 The most common traditional medicine in widespread practice across the Africa is the use of 
medicinal plants. Plants provide most of the effective and affordable medicines in traditional 
medicine and also remains the world`s chief source of drugs. Furthermore, medicinal plants have 
contributed immensely to the discovery of most pharmaceutically active compounds (Ngo et al., 
2013) which are been used in the commercial production of some drugs. A growing number of 
herbal medicines had been studied and discovered to provide alternative therapies for depression, 
such as Ginseng (Panax ginseng) (Dang et al., 2009), St. John`s wort (Hypericum perforatum) 
(Kukuia et al., 2014; Linde et al., 2008), Kalanchoe integra (Kukuia et al., 2015) etc. These 
plants produce diverse range of bioactive compounds that possess pharmacological and 
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toxicological effects in man and animals but do not play essential role in the metabolism of the 
plants hence referred to as secondary metabolites (Mailoa et al., 2013). These compounds can be 
considered as products of biochemical “supplements” in the plant cells and not required for daily 
functioning of the plant. Secondary metabolites from time immemorial have served as sources of 
effective medical therapies and are continuously a prime source of many essential efficacious 
drugs (Baliah and Astalakshmi, 2014). Several biologically active natural product compounds are 
secondary metabolites with complex structures. Humans use these secondary metabolites such as 
alkaloids, saponins, natural phenols, terpenoids as medicines (Baliah and Astalakshmi, 2014). 
Sufficient researches suggest that some secondary metabolites exhibit inhibitory effects on the 
central nervous system. Reports indicate that total saponins from ginseng (Dang et al., 2009), 
total alkaloids from Semen Zizyphi Sponosae  (Sun et al., 2013), total alkaloids from 
Cissampelos sympodialis  Eichler (Mendonça-Netto et al., 2008), etc. have been discovered to 
possess antidepressant effect. Recent reports view the extraction of secondary metabolites and 
their use as single chemical compounds as a better replacement and which have resulted in the 
substitution of plant extracts’ use (Mahomoodally, 2013) . 
Descriptions of depression can be found in the Bible and in some Shakespeare`s literature, but no 
formal definition existed until the third version of the American Psychiatric Association`s 
classification systems for mental disorders was published in 1989 (Dowrick and Frances, 2013). 
It is a common mental disorder characterized by low mood, loss of interest in pleasurable 
activities, reduced energy, low self-esteem, feeling of guilt, sleep disturbances and lack of 
concentration (W.H.O., 2012). The W.H.O has ranked depression the 4th leading cause of 
disability worldwide and projects that by 2020, it will be the second leading cause of disability 
(Kessler and Bromet, 2013). Although impairment of monoaminergic neurotransmission 
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especially serotonin and noradrenaline neurotransmission plays an essential role in the 
pathophysiology of the depression, recent studies shows that neurotrophic, genetic, 
psychological stress and endocrine factors play a key role in the central biology of the disease 
(Hasler, 2010). Depression is associated with significant morbidity and mortality due to physical 
disorders and suicide usually linked with the disease. Depressed individuals usually become a 
burden to society and their quality of life is greatly affected. These adversely contribute to 
financial loss to the society (Ford et al., 2010). 
Notwithstanding the treatment advances, standard medical practices and orthodox medicines 
available for treatment of depression had faced diverse limitations (Yan et al., 2013). Existing 
pharmacotherapies at the moment are costly, related toxicity and efficacy of these medications 
renders some unreliable and others prohibitive for use (Kukuia et al., 2014). High risk of 
recurrence associated with the use of medications coupled with the relatively slow onset of 
action leaves a lot to be desired about the effective treatment of depression (Kukuia et al., 2015). 
A number of newer antidepressant medications such as Fetzima (Levomilnacipran) and 
Brintellix (Vortioxetine) have been approved in 2014; however, they possess some side effects 
which are similar to current medications on the market. These limitations observed in the use of 
orthodox medicines have contributed to the increased use of natural medicinal plants in the 
management of depression.  
The recent global renaissance in the use of complementary and alternate medical systems 
especially medicinal herbs for the management of mood disorders such as depression accentuates 
the need for more research to ascertain the efficacy, safety and establish the standard criteria 
requires for the use of the therapies (Qureshi and Al-Bedah, 2013).  Active search into the 
discovery of newer antidepressant medications but more effective, more sustainable and with 
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minimal side effects are still ongoing (Ferguson, 2001).  Research into phytomedicine has been 
generating considerable amounts of new data on the chemical, pharmacological, and clinical 
aspects of various isolated promising bioactive compounds from medicinal plant sources (El-
Alfy et al., 2012; Iovieno et al., 2011).    
As investigation into the discovery of novel active compounds intensify, it is important that 
researchers develop the most promising plant therapies.  Extensive investigations are required 
into the pharmacological activities of potentially active compounds when it comes to medicinal 
plants. This will go a long way to help in the development of newer medications, provide 
information on the usage of the drug such as therapeutic doses, contraindications, potential drug-
drug interaction as well as best methods of extraction and synthesis. (Stark et al., 2013). 
Trichilia monadelpha (family Meliaceae) is a tree that is commonly found in lowland, evergreen 
and semi-deciduous forest, and mostly along rivers and in other moist localities (Lemmens, 
2008). It is locally known in Akan as “Otanduro”. Economically, the trunk wood of Trichilia 
monadelpha is used in making timber, building material, fuels etc. T. monadelpha has a number 
of medicinal uses including managing pain and inflammation, treatment of respiratory disorders, 
cardiovascular disorders etc. (Burkhill, 1997). Its stem bark decoction is also known to cause 
sedation and drowsiness (Abbiw, 1990). 
Trichilia monadelpha has a wide ethnomedical benefits in the society and have been shown to 
possess central nervous system depressant effect (Abbiw, 1990). Thus taking into accounts the 
search for safer and effective antidepressants was the huge propelling factor for the research into 
the antidepressant effect of the secondary metabolites of Trichilia monadelpha in this study. 
 
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1.2 PROBLEM STATEMENT 
There has been a resurgence of interest in neuropsychiatry research mainly depression due to the 
socio-economic burden it imposes on countries. Several hypotheses pertaining to depression and 
its treatment have been proposed. These hypotheses are based largely on the neuroplasticity, 
genetic, endocrinology, neurotransmitter, and psychoneuroimmunology etc. (Nemade et al., 
2013). Given the pervasive symptoms of depression, the pathophysiology of the disorder and the 
mechanisms by which currently available treatments reverse its symptoms are not yet well 
understood. 
 Depression is associated with increased resource utilization. It is estimated that depression is 
responsible for $ 85 billion direct and indirect cost per annum (Hollenberg, 2014). An individual 
who suffers from depression can expect on average to make 20 percent less in wages during his 
lifetime than if he were not depressed. Major depression is the second leading medical cause of 
long-term disability and fourth leading cause of global burden of disease (Kessler and Bromet, 
2013). In patients with other chronic diseases like cardiovascular disease, depression has been 
associated with increased morbidity and mortality, when compared to nondepressed patients 
(Chung et al., 2011; Junger et al., 2005).  
Notwithstanding the treatment advances, conventional treatment of depression had been faced 
with diverse limitations. Most current pharmacotherapies are expensive, efficacy of these 
medications renders them unreliable and several side effects are widespread (Kukuia et al., 
2014).  There exist a high risk of disease recurrence associated with these medications and 
possess a relatively slow onset of action. Therefore, cost effective, rapid acting, sustained and 
better-tolerated antidepressants are required. A huge literature focusing on psychoactive herbal 
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phytochemicals have been published (Kennedy and Wightman, 2011). These secondary 
metabolites may be important sources of novel antidepressant drugs and may be proven better in 
the management of stress and depression. 
1.3 JUSTIFICATION 
Addressing the burden of mental disorders mainly depression, presents enormous challenges at 
the clinical and public health levels, particularly in the context of limited resources. Over the last 
three decades a number of initiatives have been undertaken with the aim of improving the 
treatment of depression globally yet; it still remains one of the major causes of suicidal deaths 
and a leading medical cause of long-term disability. 
Current medications for depression include the tricyclic antidepressants (TCAs), selective 
serotonin reuptake inhibitors (SSRIs), selective noradrenergic reuptake inhibitors (SNRI), 
monoamine oxidase inhibitors (MAOIs) etc. Most of these drugs produce serious side effects and 
have slow onset of drug action. For example, TCA cause orthostatic hypotension and 
arrhythmias, MAOI`s causes sexual dysfunction and hypertension, SSRI`s also mediates 
gastrointestinal effects and weight gain (Katzung et al., 2012).  An estimated 40% of patients 
suffer conditions refractory to currents medications whiles some of them are expensive and not 
easily affordable. 
In most African countries including Ghana, herbal remedies are used for primary healthcare 
needs (Abu-Irmaileh and Afifi, 2003). These medicinal plants have proven to be essential 
sources of some potent bioactive compounds – one of the reasons why the W. H. O. is 
advocating for the incorporation of traditional medicines in primary healthcare of developing 
nations (Calixto, 2000; Abu-Irmaileh and Afifi, 2003). Trichilia monadelpha, is a common plant 
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used in traditional medicine in Ghana for treating a spectrum of diseases including 
schizophrenia, depression and epilepsy. Although anecdotal reports suggest herbalism and herbal 
remedies are been reported to be efficacious, there exists no scientific evidence of the 
antidepressant effectiveness of T. monadelpha. It is against this backdrop that the 
pharmacological activities of Trichilia monadelpha stem bark secondary metabolites in 
managing depression and its possible mechanism(s) of action as well as CNS effect should be 
scientifically validated using various animal models. In addition, secondary metabolites from 
medicinal plants have been shown to possess antidepressant effect (Yan et al., 2013; Mendonça-
Netto et al., 2008). Trichilia monadelpha, with a high phytochemical content could be a likely 
candidate for the treatment of depression. This will go a long way to aid in our pursuit of more 
effective agents for the management of depression. 
1.4 HYPOTHESIS 
There have been some anecdotal reports of the antidepressant effect of the stem bark of Trichilia 
monadelpha. It is with this knowledge that I hypothesize that the secondary metabolite(s) present 
in the stem bark of Trichilia monadelpha should possess antidepressant activity. 
1.5 AIM 
This research seeks to determine the antidepressant effect of extracts and secondary metabolites 
from the stem bark Trichilia monadelpha and the possible mechanism(s) of action of the most 
efficacious secondary metabolite in murine models of depression. 
 
 
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1.6 SPECIFIC OBJECTIVES 
1. To determine the antidepressant effect of the petroleum ether, ethyl acetate and 
hydroethanolic extracts of T. monadelpha using the forced swimming and tail suspension 
tests. 
2. To determine the antidepressant effect of the extracted secondary metabolites from 
Trichilia monadelpha.  
3. To determine whether the most efficacious secondary metabolite would exhibit a rapid 
and sustained antidepressant effect. 
4. To determine possible mechanism(s) of action of the most efficacious secondary 
metabolite. 
 
 
 
 
 
 
 
 
 
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CHAPTER TWO 
LITERATURE REVIEW 
2.1 DEPRESSION 
2.1.1 Background 
Depression is a complex chronic recurring illness with an important global public health 
problem. It is a heterogeneous group of illness that vary in symptomatology and most likely in 
aetiology (Duman, 2010).  The major depression syndrome is a disorder of mood implicating 
perturbation in emotional, cognitive, behavioural and somatic regulation.  It is a disorder 
whereby an individual exhibits an insistent sadness with a significant mood change which 
appears to be disproportionate to any cause (Atindanbila and Abasimi, 2011).  
Depressive illnesses are disorders of the brain. Brain-imaging technologies, such as magnetic 
resonance imaging (M.R.I.), have revealed that certain brain regions involved in mood appear 
different in people who have depression when compared to those of people without depression 
(N.I.H., 2011). Certain brain regions are known to contribute to various aspects of depression. 
The striatum and amygdala mediates anhedonia and decreased motivation that preponderates 
many patients whereas the hippocampus and neocortex are known to be implicated in the 
cognitive aspects of depression (Schlaepfer et al., 2008). The various brain regions function in a 
series of highly interacting parallel circuits, which serves to formulate a neural circuitry involved 
in depression (Nestler et al., 2002). 
Diagnosis and treatment of depression is based on relatively subjective assessments of diverse 
symptoms. Currently, no effective methods to objectively assess severity, endophenotypes, or 
response to treatment exists (Schmidt et al., 2011). The severity, frequency of depressive 
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episodes, and duration of symptoms vary depending on the individual. Although depression is 
most frequently encountered during primary healthcare, it is also most commonly under-
diagnosed. Studies done by the World Health Organization Psychological Problems in General 
Health Care reported that only 42 % of patients with major depression were appropriately 
diagnosed by their primary care physician (Lesperance and Frasure-Smith, 2003). Identification 
and proper recognition of depressive symptoms is impaired by the fact that most depressed 
patients present with non-specific physical complaints, without spontaneously revealing the 
psychological nature of their condition (Kessler et al., 1999). When depression is appropriately 
diagnosed and treated, available treatment modalities especially pharmacotherapy is often 
provided in a manner inconsistent with current evidence (Segal et al., 2001).  
2.1.2 Classification of depression 
Classification of depression is covered by both the Diagnostic and Statistical Manual for Mental 
Disorders (DSM -IV) and the International Statistical Classification of Diseases and Related 
Health Problems (ICD -10) (N.C.B.I., 2010). Despite advanced research on the aetiology of 
depression including neurobiological, genetic and psychological studies, no reliable 
classificatory system has come out that links either to the underlying aetiology or has proven 
strongly predictive of the disease (Cole et al., 2008). The categories and specifiers for mood 
disorders continue to increase with each successive edition of the DSM. Depression is currently 
classified based on pragmatic definitions that have emerged and enshrined in the classification 
system of DSM-IV-TR and ICD-10 according to the severity (mild, moderate or severe), 
duration (acute or chronic) and the course of the disorder (Klein, 2008).  
 
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2.1.2.1. Severity 
The classification of depression into severity groupings based on DSM–IV criteria is not a 
unitary dimension and it is useful to make a judgement of severity consisting, at least, of number 
of symptoms, severity of individual symptoms and functional impairment (N.C.B.I., 2010). 
Generally, symptom severity and degree of functional impairment correlate highly (Zimmerman 
et al., 2008). The various classes of depression according to its severity includes: sub-threshold 
depressive symptoms (fewer than five symptoms of depression), mild depression (few, if any, 
symptoms in excess of the five are required to make the diagnosis, and the symptoms result in 
only minor functional impairment. A patient with a mild episode may be capable of continuing 
with the majority of their activities), moderate depression (symptoms or functional impairment 
are between ‘mild’ and ‘severe’. A patient with a moderate episode may have difficulties 
continuing with their ordinary activities), severe depression (most symptoms, and the symptoms 
markedly interfere with functioning. Suicidal thoughts and acts are common, and a number of 
somatic symptoms are present and can occur with or without psychotic symptoms) (Dowrick and 
Frances, 2013). 
2.1.2.2. Duration 
The duration of a depressive episode can vary considerably among individuals. The classical 
definition of acute depression by DSM-IV is one in which a severe depressive episode lasts for a 
minimum of two weeks and not longer than two years and treatment studies report a median 
duration of about twenty weeks (Havard Medical School, 2009). Chronic pain is also defined as 
one in which severe depressive symptoms persist for two years or longer. Chronic depression 
causes more functional inefficiency, increases risk of suicide, and is more likely to be coupled 
with other psychiatric disorders (Klein, 2010). Patients with chronic depression are also more 
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likely than patients with acute depression to report childhood trauma and a family history of 
mood disorders (Kühnen et al., 2011). Reports indicate that patients with chronic depression who 
respond to treatment are likely to suffer a relapse within one to two years if they stop treatment 
and thus some type of maintenance therapy may be necessary (Torpey and Klein, 2008). 
2.1.2.3. Course 
This was not explicitly considered as a classificatory issue in the previous DSM guidelines. 
However, it has essential treatment consequences, particularly for the likelihood of 
relapse/recurrence. The course of depression is classified into two main dimensions: The number 
of lifetime depressive episodes and the interval between recent episodes. The number varies from 
a single/first episode to increasingly frequent recurrences. At least two months of full or partial 
remission is required to distinguish episodes (N.C.B.I., 2010).  There has been no broad 
unanimity as to how long a period of remission should occur in order to be able to declare 
recovery (Furukawa et al., 2008). Therefore, in practice it can be difficult to differentiate 
between relapse and recurrence, particularly when people have mild residual symptoms.  
Stage of episode refers to where an individual is in the course of their depression. It determines if 
the depression is worsening, static or improving and whether sub-threshold depressive symptoms 
may reflect partial remission from prior major depression (N.C.B.I., 2010). 
2.1.3   Types of depression 
Depression is still recognized as a distinct clinical entity, particularly in primary care. However, 
the subtyping of depression is considered critical for effective treatment. The current subtyping 
of depression is based on DSM-V criteria (American Psychiatric Association, 2013). 
 
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2.1.3.1. Bipolar depression 
 Bipolar disorder, also referred to as manic-depressive illness, is characterized by cycling mood 
changes from extreme mania to extreme depression. Useful for clinical practice, bipolar 
depression is classified into two distinct forms: bipolar I depression and bipolar II depression 
(Benazzi, 2006). The clinical feature of bipolar II depression is known to exhibit more atypical 
symptoms such as hypersomnia, overeating and more co-occurring hypomanic symptoms 
including psychomotor agitation  (Hantouche and Akiskal, 2005). Bipolar I depression on the 
other hand is  characterized by hypersomnia and psychomotor retardation (Mitchell and Malhi, 
2004). 
2.1.3.2 Dysthymic disorder 
According to DSM-IV-TR, dysthymic disorder is also referred to as neurotic depression or 
chronic depression. Its diagnostic criteria require depressed mood for at least 2 years. Clinical 
picture of dysthymic depression according to DSM-IV-TR is characterized by lowgrade, 
insomnia or hypersomnia, low energy, low self-esteem, poor concentration and persistent 
depression, causing clinically significant distress or impairment of functioning (Gilbert et al., 
2011). Dysthymia often co-occurs with other mental disorders. In the DSM-5, dysthymia is 
substituted by persistent depressive disorder (Grohol, 2013) which includes both chronic major 
depressive disorder and the previous dysthymic disorder. 
2.1.3.3. Disruptive mood regulation disorder 
Disruptive mood regulation disorder is an affective disorder characterized by chronic, 
persistently irritable or angry mood with frequent temper outburst (American Psychiatric 
Association, 2013). Disruptive mood dysregulation disorder (D.M.D.D.) is common among 
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children presenting to paediatric mental health clinics. The clinical presentations of DMDD are 
similar to those of other childhood disorders, notably attention deficit hyperactivity disorder 
(ADHD), oppositional defiant disorder (ODD), and bipolar disorder in children (Weis, 2014). 
The onset of D.M.D.D. is usually before age 10. Little is known about the course of the disorder 
and whether the condition presents only in age-delimited manner (Margulies et al., 2012).    
2.1.3.4 Major depressive disorder 
According to DSM-V, major depression disorder is characterized by persistent low mood and the 
inability to anticipate happiness or pleasure with feeling of worthlessness, self-loathing and 
suicidal thoughts been very common (American Psychiatric Association, 2013). The diagnostic 
code for major depression is dependent on whether there exist a single or recurrent episode, 
current severity, presence of psychotic features, and remission of status. Types of M.D.D. which 
have recently been the focus of most research include: mixed depression, atypical depression, 
melancholic depression, seasonal depression. 
2.1.3.4.1 Seasonal depression 
Seasonal depression, according to DSM-IV-TR is not a clearly different disorder, but a specifier 
of the major depressive episode of bipolar disorders and depressive disorders (Benazzi, 2006). 
Seasonal depressions may be also subsyndromal. Symptoms of seasonal depression are often 
atypical ones such as hypersomnia and overeating, and depressions are usually mild to moderate. 
It is more common in women and in young age. Seasonal affective disorder is thought to be 
mainly caused by less natural light mainly during the winter month may be effectively treated 
with phototherapy (Magnusson and Partonen, 2005).  
 
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2.1.2.4.2 Melancholic depression 
Melancholic depression is a DSM-IV-TR subtype of clinical depression that can be found in 
almost all mood disorders. It occurs as part of either a major depressive episode or bipolar 
disorder with the melancholic specifier (American Psychiatric Association, 2008) . Melancholic 
depression was the first form of depression studied extensively. The incidence of melancholic 
depression has been found to increase when the temperature and/or sunlight are low (Radua et 
al., 2010).  
2.1.2.4.3 Atypical depression 
Atypical depression is a form of M.D.D. which can be present in almost all mood disorders. It is 
the most common form of depression identified in outpatient departments in mental hospitals 
(Singh and Williams, 2006). Atypical depression was considered as a distinct diagnosis primarily 
because medication trials clearly showed patients responded better to monoamine oxidase 
inhibitors (MAOIs) compared to tricyclic antidepressants (Quitkin et al., 2003). According to 
DSM-IV, diagnosis of atypical depression requires mood reactivity. Reports also indicates 
depression with atypical features exhibit onset in childhood or adolescences (Stewart et al., 
2005). 
2.1.4 Epidemiology of depression 
Worldwide, depression is a leading cause of disease burden of very high prevalence (Collins et 
al., 2011; Kupfer et al., 2012). However, precise statistical data on the prevalence and other 
essential correlates of depression for most countries are not known.  Reports indicates that there 
exist wide variability in prevalence estimates, although some features of descriptive 
epidemiology such as age-of-onset, persistence are reasonably coherent (Kessler and Bromet, 
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2013).  Major depression disorder has meaningful proportions of lifetime cases starting in late 
adolescence, in early-middle adulthood and in late adulthood. The rate of diagnosed major 
depression increased proportionally with age from 2.8% in adults aged between 18-24 years to a 
peak of 4.6% for adults between 45-64 years. Thus, with the growing proportions of older 
people, the overall numbers of people with depressive symptoms are expected to rise (Nyirenda 
et al., 2013). Age-of-onset distributions suggest that depression is prevalent for the entire 
lifespan (Kessler et al., 2007).  
Recent epidemiological surveys conducted globally showed a lifetime prevalence of depression 
within the range of 10% to 15% (Lépine and Briley, 2011). Reports from studies conducted 
reveals that prevalence levels of depression are higher in developed countries (28.1%) than in 
developing countries (19.8%) (Kessler and Bromet, 2013). Research findings reports female 
superiority in prevalence, incidence and morbidity risk of depression (Piccinelli and Wilkinson, 
2000). Studies revealed that depression prevalence rates among students ranged from 10% to 
85% and are  relatively  higher than those found in the general population (Ibrahim et al., 2013). 
According to the W.H.O. (2011), more than 2 million Ghanaians experience moderate to mild 
mental disorders whereas 650,000 people suffer from severe mental illness (Asante and Andoh–
Arthur, 2014). A survey conducted on Ghanaian adults reflects a high prevalence rate of 21% for 
moderate to severe psychological distress (Canavan et al., 2013). Depression is reported to be the 
commonest psychiatry illness of Akan rural women (Read and Doku, 2012). Research conducted 
by Atindanbila and Abasimi, (2011) stated that 16.1% of students in the University of Ghana 
showed signs of mild depression. A study among university students in Ghana revealed that 
31.1% of students suffer from mild to moderate depression and 8.1% experience severe forms of 
depressive symptoms (Asante and Andoh–Arthur, 2014). However, these reported rates were 
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higher than those recorded in other West African university students. An estimated 80% of 
Ghanaians are suspected to be suffering from different forms of depression (Kintampo Medical 
Research Centre, 2012). The relatively high prevalence rate recorded among Ghanaian students 
reinforces the assertion made by the Kintampo Medical Research Centre. 
2.1.5 Comorbidity of depression 
In recognition of the full impact of depression, it is worth noting that depression mostly co-
occurs with various medical, psychiatric as well as substance abuse disorders (Kupfer and Frank, 
2003). In most cases, depression comorbids with other diseases. The association between 
depression and psychiatric disorders are more potent than that which exists between major 
depression and medical conditions (Melartin et al., 2002).  The presence of both or all conditions 
is often unidentified and unfortunately, causes deleterious consequences for patients (Kupfer and 
Frank, 2003). 
The impact of comorbid depression and anxiety is substantial. Report indicates that comorbid 
anxiety and depression may be responsible for as much as 2% to 4% of all medical disability 
worldwide and is associated with barriers to treatment and worse psychiatric outcomes (Aina and 
Susman, 2006). A strong association has been reported to exist between depression and pain, 
with atleast one pain symptom being present in 65% of depressed patients, and about 5 to 85% of 
patients with pain will be suffering from depression (Bair et al., 2003). Studies show that 13% of 
patients with panic disorder suffer from depression and depressive disorder is known to precede 
the panic disorder in about 25% of these patients with concurrent depression (Hranov, 2007). An 
estimated 50–75% of patients diagnosed of  anorexia nervosa or bulimia have a clinical history 
of major depression (N.I.M.H. Forum, 2001).  
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Substance abuse disorders have been shown to co-occur with depression at very significant 
levels. A study of 43,000 persons suffering from major depressive episodes where shown to have 
a lifetime incidence of substance abuse disorder comorbidities; alcohol abuse disorder (40.3%), 
nicotine dependence (30.0%),  drug use disorder (17.2%) (Hasin et al., 2005). 
Depression frequently co-occurs with diabetes and the course of depression in diabetic patients 
most often chronic and severe. Reports indicate that up to 80% of depressed diabetic patients 
may experience a relapse of depressive symptoms over a 5-year period (Katon, 2008). Comorbid 
psychiatric illnesses, particularly major depression have been found to be highly predictive of 
suicidal thoughts in HIV positive individuals. A recent study of HIV positive patients revealed 
that those with a history of suicide attempt showed significantly higher levels of depressive 
symptoms (Badiee et al., 2012). Depression in patients with coronary heart disease (CHD) is 
common. Patients with comorbid condition of myocardial infarction or acute coronary syndrome 
and depressive symptoms shows a point prevalence of 33% (Ziegelstein, 2001). There is a broad 
 unanimity that an estimated 25% of cancer patients suffer from major depression  (N.I.M.H. 
Forum, 2001). 
2.2   THEORETICAL MODELS OF DEPRESSION 
2.2.1    Biopsychosocial model 
The biopsychosocial model states that biological, psychological and social factors (diathesis-
stress) are all interconnected and essential with regard to promoting or causing depression 
(McLeod, 2015). It is known that the mind and the body are not independent and autonomous 
entities but rather are interlinked and interdependent (Nemade et al., 2007). The model therefore 
explains that there is no single cause of depression, however, these three key factors (biological, 
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psychological and social) have regularly played significant contributions pertaining to the onset 
of depressive symptoms in an overlapping fashion (MacDonald, 2015).  
2.2.1.1    Biological factors 
The various biological theories on depression mostly focus on diverse constituents of the overall 
pathophysiology of depression. A depressed patient is vulnerable to developing a wide variety of 
physical disorders, in the same way that a person suffering from a physical disorder is often more 
likely to be depressed (Nemade et al., 2007). This is most likely because a depressed patient is 
often significantly unbalanced with regard to hormonal, immunological, genetic and 
neurotransmitter system functioning (Nemade et al., 2007). 
Studies show that genetic, hypothalamic-pituitary-adrenal axes, brain structure integrity, 
cytokine hypothesis, macrophage theory of depression, monoamine theory of depression among 
others play very crucial roles and act as key components of the body’s vital stress response 
system (Roy and Campbell, 2013). These distinct biological theories however, have a 
considerable overlap between them and function at the inter-face between psychosocial stress 
and the physiological changes associated with depression (Papageorgiou, 2010; Roy and 
Campbell, 2013). 
2.2.1.2    Psychological factors 
Psychological theories to some extent can be influenced by some biological vulnerabilities which 
affects biologically-based personality characteristics such as people`s innate temperament and by 
social factors such as stress which induces depressive symptoms (Garcia-Toro and Aguirre, 
2007).  
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Several psychological theories have been proposed to mediate the aetiology of depression. 
Psychological models reported to make an individual vulnerable to depression include, negative 
cognitive schemas, poor self-esteem, pessimism and poor coping skills (McLeod, 2015). Others 
include negative childhood experiences, past trauma, judgment problems, and impaired 
emotional intelligence (the ability to perceive, understand, and express emotions) (McLeod, 
2015). 
2.2.1.3    Social factors 
The sociological facets of depression are influenced by and also influence biological and 
psychological aspects of depression (Nemade et al., 2007). Reports indicate that stress, lifestyle 
factors, poor social skills, low social support, and sociocultural context are the main social and 
environmental risk models associated with the occurrence of depression (Keller et al., 2007; Roy 
and Campbell, 2013).  
2.2.2    Psychodynamic model 
Psychodynamic theory of depression was the prevalent model within clinical psychiatry during 
the early part of the 20th century. Historically, psychodynamic theories were widely critiqued for 
their lack of empiricism (Nemade et al., 2007). However, recent models of psychodynamic 
theories of depression have been derived and are therefore influencing a transition to the initial 
resistance on the existing psychodynamic theories in the scientific world.  
 Freud (1971) explained that depression is a phenomenon which is produced as a result of 
conflict between the conscious and unconscious parts of the mind. This then results in a state 
where one becomes unaware of his/her troubling motives, desires, and wishes but is negatively 
influenced by these conditions simultaneously (Freud, 1917). Freud`s ideas showed that early 
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loss can make an individual more susceptible to depression in later life. Children who lose their 
mother are more likely to develop depression in adult life (Bifulco et al., 2002). Wade (2011) 
also explained that psychodynamic theory of depression states that depression is a result of anger 
from imbalanced cognitions which usually results in self hatred. Children of over anxious or 
neurotic parents are more prone to experiencing exaggerated anxiety and/or depression feelings  
(Nemade et al., 2007; Wade, 2011).  
A contemporary psychodynamic theory, known as object relations theory, is focused on how 
relationships are understood and mentally represented. According to this theory, moods, 
emotions and various aspects of a personality can only be properly apprehended against the 
backdrop of the relationships that one has experienced (Luyten and Blatt, 2013). The object 
relations theory describes depression as caused by difficulties in promoting representations of 
healthy relationships. Depression is an outcome of an existing strife to develop and maintain 
emotional relationships (desired objects) (Nemade et al., 2007). 
Coyne's interpersonal theory of depression is a modern derivative of psychodynamic theory 
which states that depressed patients` negative interpersonal behaviours influence their rejection 
by society (Nemade et al., 2007). Symptoms of depression begin to manifest and worsen due to 
the lack of reassurance, feeling of rejection and stigmatization (Joiner and Metalsky, 1995; 
Nemade et al., 2007). 
2.2.3       Behavioural model 
Behavioural theories of depression betone the influence of inadequate adaptation to a situation in 
the development and maintenance of depression. The model originated from the principles of 
learning and conditioning. The theories significantly emphasize the reactions individuals have to 
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new environment and how they develop adaptive or maladaptive coping strategies (Ainsworth, 
2000). According to the behavioural theory, depression was described to occur when a person 
develops a narrow repertoire of passive behaviour and efficiently avoids aversive stimuli (Veale, 
2008).  
2.2.3.1    Behavioural Activation 
Behavioural activation is a development of activity scheduling and functional approach to 
depression which is a constituent of cognitive therapy (Veale, 2008). It focuses on two main 
arguments; people with depression use avoidance activities that maintain their depression and 
determine the origin of depressive episodes in the environment (Jacobson et al., 2001). 
Behavioural activation is centred on learning theory and contextual functionalism. Behavioural 
activation theories address biological factors that contribute to depression, but do not focus on an 
internal cause of depression such as thoughts, inner conflicts or serotoninergic dysfunction 
(Veale, 2008). 
2.2.3.2    Social Skills 
Lack of social skills and poor social interactions have been empirically proven to contribute to 
the development and maintenance of depression (Oltmanns and Emery, 2014). Studies show that 
social skills reflect the absence of social interaction acquiring behaviours shown off by the 
depressed individual (Everett-Haynes, 2010). The deficit in social conversation and exchange 
results in social isolation that facilitates the development of isolation and negative self-concept 
(Steger and Kashdan, 2009).  
 
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2.2.3.3   Reinforcement contingencies 
Reinforcement contingencies theory states that depression is the outcome of lack of adequate 
environmental reward contingencies and punishment in healthy behaviours (Carvalho and 
Hopko, 2011). Cognitions and open behaviours that act as avoidant function are thought to be 
essential precursors to the diminished reward and positive reinforcement that predispose people 
to depression (Martell et al., 2001).  
 Learned helplessness is defined as a sense of having no control over outcomes, irrespective of 
your actions (Carlson, 2010). Learned helplessness theory illustrates that clinical depression and 
associated psychiatric conditions results from lack of control over a condition (Nolen, 2014). 
2.3 BIOLOGICAL BASIS OF DEPRESSION 
In addition to genetic pre-dispositions, various environmental factors are also well-established to 
contribute to the pathogenesis of depressive disorders. 
2.3.1.     Neurochemical factors 
2.3.1.1      Monoamine hypothesis 
The monoamine hypothesis has dominated study into the pathophysiology and pharmacotherapy 
of depression over the last decade. The monoamine hypothesis of depression proposes that 
depression is associated with the reduced levels of monoamines such as noradrenalin, serotonin 
and dopamine in the anterior cingulated cortex, raphe nuclei, ventral tegmentum and Brodmann 
area 25 regions of the brain (Amthor, 2014). The evidence of this hypothesis has predominantly 
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come to light from the apparent efficacy and success of antidepressant medications that increase 
the concentration of these neurotransmitters (Rodger, 2014).  
Several agents are known to be implicated in such kinds of effects including the nonselective 
inhibitor of the 5-hydroxytryptamine (5-HT) and NA, drugs that inhibit monoamine oxidase, 
tricyclic antidepressants, enzymes involved in monoamine metabolism, and tranylcypromine. 
Earlier evidence reported that reserpine which cause depletion of monoamines by disrupting 
monoamine vesicles storage, could cause depression, although recent studies were unsuccessful 
in consistently replicating this findings (Duman, 2013). Iproniazid is known to nullify psychotic 
depression that a drug used to treat hypertension can educe (Potter, 2006). Several studies have 
also provided the evidence that serotonin and norepinephrine were responsible for sustained 
therapeutic effects to antidepressant drug, as reduction of monoamine levels resulted in relapse in 
patients being treated with selective 5-HT or NA reuptake inhibitor (Jacobsen et al., 2012). 
Depressed patients responsive to drugs that act via the 5-HT pathway such as fluoxetine 
frequently suffer relapse when given diets free of tryptophan, a serotonin synthesis precursor 
(Jacobsen et al., 2012; Yamada and Higuchi, 2002). However, relapse is less likely to occur in 
depressed patients responsive to NA antidepressants (Yamada and Higuchi, 2002).  
The diversity of depression is known to have several origins, including genetic polymorphism. 
Scientific evidence suggests that polymorphisms of the gene for tryptophan hydroxylase are 
linked depression in some patients (Jacobsen et al., 2012) . The low, short variant of the 
serotonin transporter gene are more vulnerable to developing depression, anxiety-related traits 
and suicidal behaviour in response to stress or trauma (Caspi and Hariri, 2010). Research 
supports the evidence that suicide and depressed patients often expressed reduced numbers of 
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NA (α2), 5-HT1A, 5-HT1B and 5-HT2A receptors and diminished binding affinity of  5-HT1A 
receptors following demonstration using post mortem studies as well as PET scanning analysis 
(Savitz et al., 2009). 
Recent studies on depressed patients have discovered no significant modification in the function 
and levels of monoamines, with some novel antidepressant drugs known to act via other 
pathways and not directly via the monoaminergic pathway (Boerkamp and Wijnberger, 2011). 
This is supported by a study done by Duman (2012) which demonstrates that newer 
antidepressants acting via glutamate neurotransmission, particularly ketamine, exhibits rapid 
antidepressant effect in hard-to-treat depressed patients. Reports also suggest that pre-existing 
deficits in mood regulating neural circuits predispose vulnerable individuals to react abnormally 
to monoamine deficits in the pathophysiology of depression (Cowen et al., 2012). Therefore, 
monoamine functions are considered to be an essential contributor but not an absolute or 
exclusive factor in the pathophysiology of depression. 
2.3.1.2     Modification in GABA and glutamate neurotransmission 
A paradigm shift from a monoamine hypothesis of depression to functions of glutamate and 
GABAergic neurotransmission may represent a considerable advancement in the working 
hypothesis that motivates the search for new antidepressant drugs. Essentially, notwithstanding 
the availability of diverse classes of drugs with monoamine-based mechanisms of action, there 
remain a huge proportion of depressed patients who fail to achieve a sustained remission of 
depressive symptoms (Sanacora et al., 2012).  
Clinical and preclinical evidence strongly associate GABAergic dysfunction in mood disorders 
including depression (Brambilla et al., 2003). A report by Duman (2012) showed that reduced 
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GABA detected by magnetic resonance spectroscopy was reversed by antidepressant treatments.  
Research suggest GABAB receptor antagonism may serve as a basis for the development of novel 
antidepressants (Mombereau et al., 2004). Studies of the cerebral spinal fluid and with the use of 
proton magnetic resonance spectroscopy provided a direct evidence for in vivo reductions of 
GABA functional levels in cortical brain regions of depressed patients (Sanacora and Saricicek, 
2007).  Dorsal lateral PFC of depressed patients demonstrated a deficit in GABAergic 
interneurons during a post-mortem studies (Maciag and Hughes, 2009). Levinson and Fitzgerald 
(2010), in an imaging study, detected functional loss of GABA inhibition in the cortical regions 
of the brain. A post-mortem investigation revealed decreased levels of glutamic acid 
decarboxylase,  a primary GABA synthesizing enzyme (Karolewicz and Maciag, 2010).  
There is substantial evidence which implicates glutamate alteration or dysregulation in the 
pathophysiology of depression. Several studies have suggested the presence of increased 
functional levels of glutamate as well as decreased plasma glutamine/glutamate ratios in the 
plasma of depressed patients compared to healthy individuals (Küçükibrahimoğlu et al., 2009). 
A post-mortem investigation of the frontal cortex demonstrated a significant increase in tissue 
glutamate levels in patients with major depressive and bipolar disorders (Hashimoto et al., 2007). 
Sanacora et al., (2012) reported that altered platelet glutamate uptake recorded in depressed 
patients could contribute to the pathophysiology of the disease since platelets possess 
significantly high affinity to glutamate uptake system and are to express the same glutamate 
transporters in the brain. The need for functional balance glutamate signalling is highlighted by 
therapeutic efficacy of novel antidepressant which act via a transient burst of glutamate 
neurotransmission (Duman, 2012). Scientific evidence showed that significantly higher 
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glutamate metabolite levels were reported in the frontal cortex of subjects experiencing post-
stroke depression and late life depression (Wang et al., 2012). 
2.3.1.3    Nitric oxide and NMDA receptor complex 
Nitric oxide (NO) has been shown to play an essential role in the nervous system including 
processes being associated to major psychiatric disorders (Knott and Bossy-Wetzel, 2009). Lee 
et al., (2006) demonstrated that samples obtained from depressed suicide attempters had elevated 
levels of NO metabolites. Reduced number of nitric oxide synthase (the enzyme responsible for 
the synthesis of NO) containing neurons in the hypothalamus (Bernstein et al., 2005) and 
hippocampus (Oliviera et al., 2008) was recorded in depressed patients. Studies on human 
genetic association have consistently linked NO signalling and bipolar disorder (Reis et al., 
2006). Several preclinical investigations have shown that impairment of nitric oxide synthase 
activity produces antidepressant-like effects in various animal models (Wegener and Volke, 
2010).  
It has been shown that N-methyl-D-aspartate (NMDA) receptor complex is strongly linked to the 
pathogenesis of depression (Mantovani et al., 2003b). Several recent clinical and preclinical 
studies have shown that NMDA receptor antagonists such as ketamine or Ro25-6981 binding at  
N2B specific subunit, exert an antidepressant-like effect and also counteracts depressive-like 
behaviours in chronically stressed rodents (Li et al., 2010).  
2.3.2      Neuroplasticity and neurotrophic factors 
Substantial evidence indicates that disruption of neuroplasticity in the brain region is strongly 
associated with depression, including reductions of hippocampal neurogenesis and cortical 
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synaptogenesis (Hayley and Litteljohn, 2013). Deteriorated trophic maintenance stemming from 
stressor-induced reductions of growth factors, mainly brain derived neurotrophic factor (BDNF) 
is likely to influence such aberrant neuroplasticity. In this respect, significant substantiation has 
supported the contention that protracted disturbances of neuroplasticity is implicated in the 
pathophysiology of depression (Sacher et al., 2012). 
Essentially, reduced hippocampal volume has been observed in patients diagnosed with major 
depression (Colla et al., 2007). Recent reports have focused on the possibility that continued 
alterations of neuroplasticity could be responsible for the faulty communication between anterior 
cingulate cortex, hippocampal, and amygdaloid regions, therefore resulting in the disordered 
processing of emotionally salient information observed in depressed individuals (Carballedo et 
al., 2011). According to Scheidegger et al., (2012) ketamine treatment targets the default mode 
network (D.M.N.) within the cingulate and prefrontal cortices to help “re-wire” faulty circuitry 
and reduce DMN metabolic activity. Changes in glial cell density, the composition and 
complexity of dendritic arbors have been reported to contribute to the brain volumetric changes 
in depression (Gittins and Harrison, 2011). Other findings have also revealed decrease in cortical 
and/or hippocampal astrocytes in depressed patients (Liu et al., 2011). It is essential to note that 
in addition to reductions of neuroplasticity, increased neuroplasticity in some case may also 
contribute to depressive symptomology and relapse (Hayley and Litteljohn, 2013). 
Scientific evidence reports that platelet and serum BDNF protein concentrations are diminished 
in depressed patients, with a positive correlation between the levels of the growth factor and  
symptom severity (Yoshida et al., 2012). Reduced BDNF mRNA expression was recorded in the 
leukocytes of depressed individuals (Cattaneo et al., 2010). Several clinically beneficial 
therapies, including selective serotonin reuptake inhibitors (SSRIs), tricyclics, and 
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electroconvulsive therapy (ECT), were reported to boost hippocampal BDNF expression and 
increase neurogenesis in animal models (Voleti and Duman, 2012). 
Irrespective of the fact that BDNF has been the centre of focus about the role growth factors in 
depression, emerging and recent evidence indicates that other growth factors, particularly glial 
cell-line derived neurotrophic factor (GDNF) (a member of the transforming growth factor beta 
family) is also likely to be associated with the pathogenesis of depression (Tsenga et al., 2013). 
A study by Diniz et al., (2012) recorded reduced levels of GDNF protein and mRNA in the 
blood of depressed patients. However, effective antidepressant therapies including SSRIs and 
ECT caused a return to normal levels (Zhang et al., 2009). Other neurotrophic/growth factors 
that have been associated with depression include vascular endothelial growth factor, fibroblast 
growth factor 2 and insulin-like growth factor 1 (Duman, 2012).   
Stressors have been implicated in the inhibitory actions on dendritic branching (Son et al., 2012), 
suggesting the likelihood that grey matter shrinkage may partly be associated to the considerable 
stress experienced by depressed individuals (Hayley and Litteljohn, 2013). Moreover, studies on 
depressed human subjects appear to substantiate the animal data on the effect of neurotrophic 
factors in stress states (Zhang et al., 2015). In this regard, neuroplasticity and neurotrophic 
factors continue to be passionately researched into and continue to yield new and novel potential 
treatment targets of major depressive disorder (Duman and Li, 2012; Voleti and Duman, 2012).  
2.3.3      Neuroendocrine factors 
Considerable research findings have been documented over the few decades regarding the role of 
hormones in the pathophysiology depression (Hatzinger, 2000). Several clinical and preclinical 
studies have provided substantial evidence that abnormalities in the hypothalamic-pituitary-
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adrenal (HPA) axis is implicated in depression (Gotlib et al., 2008). Research showed that an 
estimated 73% of depressed patients had increased cortisol levels compared to non-depressed 
individuals (Stetler and Miller, 2011). Preliminary evidence suggests that corticotrophin 
releasing hormone 1 (CRH1) receptor antagonists decrease symptoms of depression (Holsboer 
and Ising, 2008). Scientific findings shows that the elevation of both endogenous cortisol and 
exogenous glucocorticoids are implicated in cognitive deficits and affective disorders such as 
major depression (Markopoulou et al., 2009). Research suggests that some antidepressants exert 
their pharmacological action via enhancement of type II glucocorticoids receptor function with a 
subsequent restoration of HPA axis via negative feedback  (Barden, 2004). Thyroid hormone 
dysregulation has been reported in depressed patients (Engum et al., 2002). Therapeutic effect of 
standard antidepressant medications have been shown to be intensified when they are used 
concurrently with thyroid hormones in the treatment of depression (Engum et al., 2002). Several 
research findings have also linked dysregulation of steroidal sex hormones to the 
pathophysiology of depression (Almeida et al., 2004). Postpartum and postmenopausal periods 
which are usually characterized by estrogen deficiencies have been implicated in the aetiology of 
depression in women (Kessler, 2003). Similarly, acute testosterone deficiency has been reported 
to play a role in depressive symptoms observed in men (Kessler, 2003).    
2.4 ANTIDEPRESSANT DRUGS 
2.4.1 History 
Earlier in time to the introduction of the first clinical antidepressants, the therapeutic tools in use 
in treating mood disorders were tremendously limited (Lopez-Munoz and Alamo, 2009). During 
the early periods of the 20th century, insulin comas, electrical shock therapy or the famed “sleep 
cures” had a widespread use in the treatment depressive symptoms (Lopez-Munoz and Alamo, 
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2009). The few chemical products at hand to physicians were non-specific ones, including 
malonic nitrite, succinic dinitrite and lactic acid  (Lopez-Munoz and Alamo, 2009).  
The fields of psychiatry and psychopharmacology witnessed an absolute transformation in the 
1950s with the introduction of clinical psychoactive drugs used today. Reports indicates that 
serendipity played an essential role in the finding of the majority of the psychotropic medications 
(Judd, 1998). 
From 1957-1980, the first generation antidepressant drugs which includes tricyclic 
antidepressants such as imipramine and maprotiline which act via 5-HT and NA reuptake 
inhibition with blocking action on diverse receptors were discovered (Kuhn, 1958). The 
irreversible MAO inhibitors including phenelzine and iproniazid were also introduced within the 
periods of 1960 -1965 (López-Muñoz et al., 2007). Drugs which act as antagonist of α2 auto-
receptors such as mianserine also came into the existence within 1970-1980 (Schulz and 
Remschmidt, 2001).  Moclobemide and other drugs that acts as reversible MAO inhibitors were 
introduced from 1980-1995 (Lopez-Munoz and Alamo, 2009). 
The second generation of antidepressant drugs such as fluoxetine, paroxetine and setraline acting 
via selective 5-HT inhibition were also introduced between 1980-1990 (Domino, 1999). Within 
the same time period, selective dopamine reuptake inhibitors such as bupropion were discovered 
(Lopez-Munoz and Alamo, 2009).  
Between 1975 and 2000, a third generation of antidepressant medications generally called 
atypical antidepressants were also introduced. These include mirtazapine,(a drug which acts as 
an antagonist of α2 auto- and hetero-receptors and 5HT2 and 5-HT3 receptors) reboxetine, 
(selective NA reuptake inhibitors) and venlafaxine, (a NA and 5-HT reuptake inhibitor) (Lopez-
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Munoz and Alamo, 2009). Over the last decade, a number of clinical studies have shown that 
ketamine, acting via non-competitive NMDA receptor antagonism exhibits antidepressant effects 
(Hillhouse and Porter, 2015).   
2.4.2 Antidepressant drugs and their mechanisms of action  
Antidepressant effects are produced by drugs that inhibit monoamine oxidase action, inhibit 
monoamine reuptake, stimulate and/or modulate monoamine, antagonize monoamines at their 
receptors sites and antagonism at the α2 auto – and hetero – receptors (Hughes et al., 2005; 
Lopez-Munoz and Alamo, 2009). In addition, blockade of the glycone site of the NMDA 
receptor, agonism of melatonin receptor, and inhibition of L-arginine-NO-cGMP pathway can 
also protect against the occurrence of depressed state in animal models (Adongo et al., 2015; 
Laudon and Frydman-Maron, 2014).  In principle, antidepressant drugs act by targeting one or a 
combination of these systems (Yildiz et al., 2002).   
2.4.2.1    Monoamine oxidase inhibitors 
Monoamine oxidase inhibitors (MAOI) are chemicals that inhibit the conversion or metabolism 
of monoamines into inactive products via the impairment of the activity of the monoamine 
oxidase enzyme family (Lehne, 2004). Thus, they increase the concentration of monoamine 
transmitters; 5-HT, NA, and DA. Two subtypes of MAO have been discovered and are located in 
both neuronal cells like the brain and non-neuronal cells such as liver and intestines within the 
body (Lovatt, 2011). Therefore the functional levels of neurotransmitters are potentiated by 
inhibiting MOA and thus relieving the symptoms of depression. 
The classical MAOIs such as tranylcypromine, phenelzine and isocarboxazid are irreversible and 
nonselective. Following their oxidation to reactive intermediates by MAO, these "suicide" 
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substrates interacts irreversibly to inactivate the  flavin prosthetic  group of the MAO  enzyme 
(Krishnan, 2007). This group of nonselective and irreversible MOAIs in addition, also inhibit the 
biotransformation of dietary tyramine leading to symptoms of ‘the cheese effect’ often associated 
with the usage of these drugs (Brent et al., 2005). This adverse effect resulted in the MAOIs 
becoming a last choice in the pharmacological management of depression (Lovatt, 2011). 
Several reversible, short-acting, selective MAO-A inhibitors such as moclobemide, had been 
developed. Studies indicates that the ‘cheese effect’ is less likely to occur with this group of 
drugs due to their limited and reversible duration of action (Yamada and Yasuhara, 2004).  
2.4.2.2    Monoamine receptor antagonists 
5-HT receptor antagonists have been shown to accelerate and perhaps augment the clinical 
effects of most antidepressants and as well alleviate and prevent several adverse effects 
associated with the use of other antidepressant medications (Artigas et al., 1996). Several reports 
also indicates that a combination of SSRI drugs treatment with the mixed 5-HT1A/ β-
adrenoceptor antagonist pindolol, caused a marked decline in the latency of the antidepressant 
response and additionally intensified the clinical response in previously untreated patients with 
depression (Whale et al., 2010).  Scientific research suggests that co-administration of the 
selective 5-HT 1A antagonist WAY-100635 and the 5-HT 1B receptor antagonist SB-224289 acts 
additively to potentiate the neurochemical actions of the SSRI, fluoxetine (Artigas, 2013). This 
co-administration could elevate serotonin and therefore potentially be an effective strategy to 
treat depression (Artigas, 2013). Nefazodone and trazodone are both 5-HT2 receptor blockers, 
however, unlike SSRIs, they do not produce some of the side effects that SSRIs may cause such as 
the short-term increase in anxiety or insomnia, akathisia, and sexual dysfunction (Yildiz et al., 
2002).   
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Mirtazapine is a noradrenergic and specific serotoninergic  antidepressant which posses a dual 
mechanism of action that increases the concentration of 5-HT and noradrenalin in the synaptic 
cleft (Stahl, 1997). It is known to block noradrenaline α2-autoreceptors and noradrenaline α2-
heteroeceptors in addition to possessing a selective blockade effect on 5-HT1A receptors (Yildiz 
et al., 2002). Etoperidone exhibits its antidepressant effect by acting primarily as an antagonist of 
5-HT2A, α1-adrenergic, 5-HT1A, and α2-adrenergic receptors has very weak affinity and hence 
blockade effect on D2 receptors (Index Nominum, 2000) . 
2.4.2.3   Monoamine reuptake inhibitors 
Serotonin–norepinephrine–dopamine reuptake inhibitors (SNDRI), popularly referred to as triple 
reuptake inhibitors (TRI), consist of a class of drugs that concomitantly acts as reuptake 
inhibitors for the monoamine neurotransmitters serotonin (5-HT), noradrenaline (NA) and 
dopamine (DA) (Shao et al., 2011). These effects are mediated by blocking the action of the 
serotonin transporter (SERT), noradrenalin transporter (NET), and dopamine transporter (DAT). 
This results in elevated functional levels of extracellular concentrations of these monoamine 
neurotransmitters and, therefore, an increase in their neurotransmission (Marks et al., 2008). 
Amitifadine, is an antidepressant drug  with a typical serotonin-norepinephrine-dopamine 
reuptake inhibition effect (Skolnick et al., 2003).  GSK1360707F is a novel and potent selective 
triple reuptake inhibitor structurally related to amitifadine which is still under clinical trials and 
has shown to be effective in the treatment of major depressive disorder (Comley et al., 2013). 
Serotonin noradrenalin reuptake inhibitors (SNRIs) are a class of antidepressant that selectively 
bind to 5-HT and NA transporters to block their reuptake from the synaptic clefts (Stahl et al., 
2005). SNRI`s possess a “dual mode of action” by inhibiting the action of 5-HT transporters 
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(SERT) and NA transporters (NAT) in a way similar to tricyclic antidepressants (TCAs), but 
differ from TCAs in that SNRIs exhibit lesser affinity for other receptors. Studies have shown 
that SNRIs also contribute to the elevation of functional levels of dopamine in the prefrontal 
cortex via NAT inhibition (Ipek et al., 2012) . Most SNRIs show varying selectivity to the 
reuptake of both 5-HT and NA. Milnacipran inhibits serotonin and noradrenalin reuptake with 
equal affinity, duloxetine shows a 10-fold greater selectivity for 5-HT reuptake inhibition whiles 
venlafaxine exhibits a 30-fold greater selectivity for 5-HT (Celikyurt et al., 2012). 
Desvenlafaxine, a synthetic form of the isolated major active metabolite of venlafaxine, is 
approximately 10 times more effective at blocking 5-HT uptake than NA uptake (Septien-Velez 
et al., 2007; Stahl et al., 2005). 
The first Tricyclic antidepressant (TCA), imipramine was originally derived from the 
antipsychotic drug phenothiazine (López-Muñoz and Alamo, 2009). TCAs typically block the 
reuptake of serotonin or norepinephrine. In addition to their effects on amine uptake, most TCAs 
interact with several other types of neurotransmitter receptor, including alpha adrenergic (α1) 
receptor blockade, muscarinic acetylcholine receptors, histamine receptors and 5-HT receptors. 
The outcome of TCAs interaction with most of these receptors do not contribute to the 
antidepressant effect but  are responsible for the various adverse effects associated with the use 
of TCAs. A modest overdose of TCA has been reported to be lethal due to the narrow gap 
between their ability to inhibit the biogenic amine uptake pumps and the blocking effect of fast 
sodium channels (Preskorn, 2010). Tricyclic antidepressants also can desensitize D2 dopamine 
autoreceptors through uncertain mechanisms and with uncertain behavioural contributions 
(Brown and Bottomley, 1990). TCAs with secondary-amine side chains or the N-demethylated 
(nor) metabolites of agents with tertiary-amine moieties such as amoxapine, desipramine, 
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maprotiline, and nortriptyline are moderately selective inhibitors of norepinephrine transport. 
However, most tertiary-amine TCAs also block the reuptake of 5-HT. Among  the  tricyclic  
antidepressants, trimipramine has been reported to possess exceptional features  in  that,  it  lacks 
conspicuous blockade  effects  at  monoamine  transport,  and  its  clinical  actions  remain 
elusive (Cohen, 2003). 
The selective serotonin reuptake inhibitors (SSRIs) are the most commonly prescribed class of 
antidepressants. These drugs inhibit the neuronal uptake of serotonin both immediately or 
chronologically by blocking the SERT, thus increasing its synaptic concentration (Moltzen and 
Bang-Andersen, 2006). Citalopram and fluoxetine have been shown to be racemic mixtures 
whereas sertraline and paroxetine are also two distinct enantiomers. Escitalopram is the (S)-
enantiomer of citalopram. Studies have shown that elevated synaptic serotonin level stimulates a 
large number of postsynaptic serotonin receptor types. Stimulation of 5-HT3 receptors is 
suspected to mediate the  common  side  effects associated with the use of  SSRIs, such as 
gastrointestinal effects  (nausea  and  vomiting)  and  delayed  or  impaired  orgasm. Moreover, 
stimulation of 5-HT2C receptors have been reported to contribute to the agitation  or  restlessness 
characteristic of SSRIs (Azmitia et al., 1995). Thus novel SSRIs under discovery have been 
reported to exhibit auxiliary interactions with other receptors, most notably additional antagonist 
activity at 5-HT receptors located pre-synaptically as well as post-synaptically  (Moltzen and 
Bang-Andersen, 2006). 
Selective noradrenalin reuptake inhibitors selectively and significantly block NA reuptake 
(Frazer, 2000). Recent clinical evidence shows that NA neurotransmission is augmented in 
depressed patients treated with NA reuptake inhibitors (Miller et al., 1996). The therapeutic 
effects of NA reuptake inhibitors such as reboxetine and mazindol are reversed by catecholamine 
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depletion in depressed patients, indicating that euthymia is sustained by elevation of NA 
neurotransmission (Miller et al., 1996). 
2.4.2.4   Modulators and/or stimulants of monoamines  
Antidepressant drugs that acts as modulators and /or stimulators of monoamines mainly elevates 
serotoninergic, noradrenergic, dopaminergic, and at times cholinergic, histaminergic and 
glutamatergic neurotransmission in brain structures (Sancheza et al., 2014). They are also known 
to  augment SSRI effects on extracellular 5-HT functions in the rodent brain (Blier and Rueter, 
1999). One of such drug is vortioxetine, a novel antidepressant which act as a 5-HT1B receptor 
partial agonist, 5-HT1A receptor agonist and serotonin (5-HT) transporter (SERT) inhibitor as 
well as a 5-HT1D receptor antagonist, a 5-HT3, and a 5-HT7 receptor antagonist (Guilloux et al., 
2013; Westricha et al., 2015). Vilazodone is also another drug which act as a serotonin reuptake 
inhibitor and 5-HT1A receptor partial agonist (Wang et al., 2013). 
2.4.2.5    NMDA receptor antagonists 
Glutamate plays an important role as an excitatory neurotransmitter in diverse physiological 
functions, and its release results in activation of NMDA receptors, an underlying cause of 
depression  (Sanacora and Schatzberg, 2015). Several studies with NMDA receptor antagonists 
of mGluR1 and mGluR5 receptors have been shown to possess antidepressant activity in a 
variety of animal models (Lemke and Williams, 2012). NMDA antagonists block the Ca2+ 
channels within NMDA receptors and thus inhibit the influx of excessive Ca2+ which mostly 
characterized the pathophysiology of depression (Ates-Alagoz and Adeboye, 2013). The 
antidepressant therapeutic effects of NMDA antagonists have been reported to be mediated by 
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increased AMPA-to-NMDA glutamate receptor throughput in critical neural circuits (Lemke and 
Williams, 2012).  
Ketamine, a non-competitive NMDA antagonist is known to produce rapid, robust and persistent 
antidepressant effects clinically (Owen, 2012). Several antidepressant compounds under clinical 
trial including CGP 37849 and CGP 40116, a noncompetitive, non-subunit selective NMDA 
receptor antagonist MK-801 have been reported to effectively block NMDA receptor activity 
(Autry et al., 2011; Lima-Ojeda et al., 2013). The NR2B selective antagonist RO-25-6981 
(Adongo et al., 2015; Lima-Ojeda et al., 2013) has consistently been shown to exhibit 
antidepressant-like properties in rodent models. 
2.4.2.6    Melatonin receptor agonists  
Melatonin agonists are analogs of melatonin. Melatonin is the primary neurohormone produced 
by the pineal gland in the brain responsible for the regulation of the body`s circadian rhythm 
(Lemke and Williams, 2012). An antidepressant effect of melatonin receptor agonist markedly 
differs from other classes of antidepressant drugs: its primary molecular targets in vivo are the 
melatonin MT1 and MT2 receptors, where it acts as a potent agonist. The antidepressant potential 
of agomelatine is as a result of a synergistic or a complementary action on MT receptors as well 
as its antagonistic effect on 5-HT2C receptors (Bourin and Prica, 2009). Studies show that 
agomelatine has no affinity for histaminergic, dopaminergic, cholinergic benzodiazepine, α-
adrenergic or β-adrenergic receptors. Activation of MT1 and MT2 receptors by agomelatine triger 
the release of melatonin causing the induction of sleep, and rezynchronisation of the irregular 
sleep/wake circadian rhythm of depressed individuals by delaying the sleep phase rhythm 
(Lemke and Williams, 2012). Through the antagonism at 5-HT2C receptors, agomelatine 
stimulate the release of DA and NA in the frontal cortex of the brain which may contribute to its 
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antidepressant efficacy (Dawoodi et al., 2012). Other melatonin receptor agonists approved for 
use in humans include ramelteon and tasimelteon.   
2.4.2.7  L-arginine-NO-cGMP pathway 
L-arginine-nitric oxide (NO)-cyclic guanosine monophosphate (cGMP) is an essential signalling 
pathway known to be implicated in the pathogenesis of depression (Mantovani et al., 2003a). 
Nitric oxide is synthesized from L-arginine by nitric oxide synthase (NOS) and has been reported 
to play a role in neurotransmission, learning, perception of pain, aggression, synaptic plasticity 
and depression (Esplugues, 2002). Several scientific evidences have shown that decrease of NO 
levels within the hippocampus stimulates antidepressant-like effects (Joca and Guimaraes, 2006). 
A number of physiological effects of NO are facilitated via its association with the heme iron of 
soluble guanylate cyclase leading to enzyme activation and subsequent increase in cGMP (Kaster 
et al., 2005). NOS inhibitors such as L-NNA (L-NG-nitroarginine), L–NMMA (L-NG-
monomethylarginine) and NG-propyl-L-arginine have been shown to be effective in enhancing 
the antidepressant effect of various drugs in animal models (Wegener and Volke, 2010). MK-
801(dizocilpine) has been reported to exhibit its antidepressant effect via the involvement of NO 
signalling pathway in mice (Dhir and Kulkarni, 2008).  
2.4.2.8 Opioid receptor agonists 
Central opioid systems are also known to influence the pathophysiology of depression 
(Berrocoso et al., 2013). Endogenous opioid peptides co-expressed in brain areas have been 
reported to be implicated in affective disorders and in the action of antidepressant drugs via three 
receptor subtypes (mu, delta and kappa). Moreover, antidepressants which act via increase the 
inhibition of the reuptake of monoamines lead to the enhancement of the opioid pathway 
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(Berrocoso et al., 2009; Jutkiewicz and Roques, 2012). The role of opioid as recognized 
antidepressants is butressed by the clinical effectiveness of  μ‑opioid receptor agonists such as 
tramadol, oxycodone, oxymorphone, etc., in the treatment of refractory depression (Shapira et 
al., 2001; Hegadoren et al., 2009). 
2.5 NON-PHARMACOLOGICAL TREATMENTS OF DEPRESSION 
2.5.1 Psychotherapy 
It is satisfactorily recognized that psychological interventions are effective in the treatment of 
depression (Cuijpers et al., 2014). Even though psychiatric medication is the often prescribed 
therapy for depression (Carson, 2000), psychotherapy may be useful, either alone or in 
combination with pharmacological intervention. However, combining psychotherapy and 
antidepressant medications may prevent a "slight advantage” (Cuijpers et al., 2014). 
Cognitive behaviour therapy (CBT) is the most examined form of psychotherapy considered to 
be effective. In this therapy, patients are taught to study a set of cognitive and behavioural skills, 
which they utilize on their own. A recent investigation by Roth and Fonagy (2006) indicates that 
CBT is equally effective in treating patients with moderate to severe depression. A study 
reported that CBT and fluoxetine outperformed treatment with only fluoxetine (March et al., 
2004).                                                            
Interpersonal psychotherapy (IPT) emphasize on the social and interpersonal sparks that may 
mediate depression. Substantial evidence has shown that (IPT) is an effective treatment for 
depression. IPT undertakes a well designed course with a set number of weekly sessions (usually 
12) similar to CBT. However, the focus is on relationships with others. IPT is essential to 
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improve interpersonal skills, build a more effective communication and reduce stress (Weissman 
et al., 2000). 
Introduced by Martell et al., (2001) behavioural activation therapy emphasize on the 
improvement of activity scheduling. This form of therapy inspire patients to approach activities 
that they are staying away from and focus on analyzing the function of cognitive processes that 
serve as a form of avoidance (Martell et al., 2001). Patients are therefore repositioned on their 
ambitions and valued directions in life. A core merit of behavioural activation over customary 
cognitive–behavioural therapy for depression is that it makes it easier to train staff in it and is 
applied to both in-patient and out-patient settings (Veale, 2007). 
2.5.2 Electroconvulsive therapy 
Electroconvulsive therapy (ECT) is a standard psychiatric treatment in which spasm are 
electrically stimulated in patients to provide relief from psychiatric illnesses (Rudorfer et al., 
2003). An informed consent is always required when ECT is to be used which is usually 
considered as a last line of intervention for major depressive disorder (Beloucif, 2013). Reports 
have shown that a cycle of ECT is effective in 50% of patients with treatment-resistant major 
depressive disorder (Dierckx et al., 2012), however, studies have also revealed that about half of 
patients who respond, relapse with twelve months (Jelovac, 2013). The most common effects on 
the brain are confusion and memory loss (American Psychiatric Association, 2001). Nonetheless, 
ECT is regarded as one of the least harmful treatment options available for severely depressed 
pregnant women (Pompili, 2014). Drug therapy is usually continued after ECT, yet, some 
patients receive maintenance ECT (Dierckx et al., 2012).  
 
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2.5.3 Light therapy 
Light therapy or heliotherapy comprises of exposure to daylight or to specific and precise 
wavelengths of light using polychromatic polarized light, lasers, dichroic lamps, full-spectrum 
light or light-emitting diodes. The rays strike the retina of the eye. Light therapy is used to treat 
circadian rhythm disorders and seasonal affective disorder. A meta-analysis of bright light 
therapy revealed a significant decrease in the severity of depression symptom (Tuunainen et al., 
2004).  
2.6 THERAPEUTIC BENEFITS OF SOME PLANT SECONDARY METABOLITES 
2.6.1 Background 
The utilization of several medicinal herbs has a protracted history. Since ancient times, medicinal 
plants are being used especially in oriental countries.  However, the introduction of synthetic 
compounds and antibiotics in early 20th century influenced the regression in the usage of 
medicinal herbs and diminished interest in proving the scientific bases to their pharmacological 
effects (Cowan, 1999).  Interestingly, the  hostile adverse  effects  associated with  usage of 
antibiotics  and several other synthetic compounds have  reignited  interest  in  the  disciplines  of  
phyto-chemistry,  phyto-pharmacology and  phyto-medicine (Makkar et al., 2009). 
The past decade has witnessed a remarkable renaissance in the interest and use of medicinal plant 
products due to their rich phytochemical constituents. The beneficial medicinal effects of plant 
materials typically result from the combinations of secondary products present in the plant 
(Briskin, 2000). Several studies report that the therapeutic actions of medicinal plants are 
inimitable to peculiar plant species and these are coherent with the view that combination of 
secondary metabolites in a particular plant are usually taxonomically unique (Wink, 1999).  
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Polyphenols are naturally occurring secondary metabolites of plants. The most studied classes 
are the flavonoids, tannins, stilbenes, and lignans. A number of studies have demonstrated that 
polyphenols have cardio-protective effects (García-Lafuente et al., 2009), anticancer potentials 
(Yang et al., 2001), neuro-protective effects (Letenneur et al., 2007), anti-aging (Pandey and 
Rizvi, 2009), and anti-diabetic effects (Rizvi and Zaid, 2005) among others. 
Triterpene saponins collectively known as ginsenosides are the major phytochemicals present in 
ginseng and have been reported to heavily contribute to its vast health benefits which include 
reduction of levels of cholesterol, low-density lipoprotein-cholesterol (LDL-C), serum 
triglycerides, and atherogenic indices (Song et al., 2012) According to a study by Tsai et al., 
(2010) soy saponins may be effective in preventing colon cancer by affecting cell morphology, 
cell proliferation enzymes, and cell growth. Research findings indicate that soybean saponins 
possess not only a significant antimutagenic activity but also a strong inhibitory action against 
carcinogen-induced DNA damages (Jun et al., 2002). Platyconic acid, a saponin from Platycodi 
radix, improves glucose homeostasis by enhancing insulin sensitivity in vitro and in vivo (Kwon 
et al., 2012). 
Alkaloids are known to create extreme physiological action in humans and are commonly used 
as therapeutic agents. Several alkaloidal drugs have been identified to stimulate the central 
nervous system either as depressants (e.g.: morphine) or stimulants (e.g.: caffeine). Other known 
alkaloids have an effect on the autonomic nervous system and are been used as anticholinergics 
(e.g.: atropine), ganglioplegics (e.g.: nicotine) sympathomimetics (e.g. ephedrine), 
sympatholytics (e.g.: yohimbine), and parasympathomimetics (e.g.: pilocarpine). Some local 
anaesthetics such as cocaine and other alkaloidal agents are used to treat fibrillation, (e.g.: 
quinidine) as analgesics, (e.g.: codeine and morphine) anti-tumor agents, (e.g.: vinblastine) anti-
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malarials, (e.g.: quinine) antibacterials, (e.g.: berberine)  and amoebicides (e.g.: emetine) 
(Roberts and Wink, 1998). 
Phyto sterols and stanols have been recognized to lower serum cholesterol level via the reduction 
of cholesterol from the gut (Law, 2000). A study conducted by Gylling et al., (1997) showed that 
plant sterol or stanols added to a daily portion of margarine decreases serum levels of low-
density-lipoprotein cholesterol in the aged causes a reduction in the risk of heart disease of about 
25%. 
2.6.2   Antidepressant properties of secondary metabolites of some medicinal plants 
Discovery of novel sources of natural products for depression treatment will continue to be an 
essential field of research. Despite the great advances in our understanding of depression, not 
much is known about the antidepressant mechanisms of many plant phytochemicals. However, 
some advantages of plant secondary metabolites with regards to the discovery of antidepressants 
have been reported and the antidepressant activity of plant phytochemical in particular has 
attracted tremendous attention in recent years (Gong et al., 2014). 
The total flavonoids of Hypericum perforatum, also known as St. John’s wort used to treat 
depression have shorten  the motionless time of FST mice in a dose-dependent manner (Shi and 
Wang, 2006). Studies by  Nöldner and Schötz, (2002) revealed that the antidepressant activity of 
quercetin-3-O-glucuronide exhibits the  same  efficacy  as  imipramine. The extract of total 
flavonoids (XBXT-2) from Xiao Bu Xin Tang showed antidepressant potential in mice and a 
prolong intake of XBXT-2 helped despairing mice to recover their behaviour and increase the 
adrenaline content in their serum (An et al., 2008).  Han et al., (2007) showed that apigenin, 
luteolin (flavone), and quercetin (flavonol)  could  regulate the activity of MAO  activity  with  
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their  IC50  values at  6.5,  22.6  and  31.6  μmol/L  respectively (Han et al., 2007) .  (Wang et al., 
2007) found that flavanones showed a potential structure for antidepressant activity. High-
density Hypericum  monogynum  flavonoids  may  exert  its  antidepressant  properties by 
building up  the levels  of  5-HT,  DA  and NA  in  both  hypophysis  cerebri  and  brainstern 
(Zhen et al., 2012). The antidepressant effect of general flavonoids of cotton seed is known to be 
mediated by increasing the neurological function of 5-HT in the brain and improving the nutrient 
level and plasticity by enhancing the access function of AC-cAMP-CREB and its associated 
neurotrophic factor with 5-HT receptors (Y. F. Li et al., 2006). 
Work done by (Martínez-Vázquez et al., 2012) revealed that alkaloid extract (1,2-dimethoxy-5, 
6,6a,7-tetrahydro-4H-dibenzoquinoline-3,8,9,10-tetraol,anonaine, liriodenine, and nornuciferine) 
from the aerial parts of Annona cherimola produces an antidepressant-like action from a 
generalized increase in monoaminergic turnover. The total tertiary alkaloids extract of 
Cissampelos sympodialis Eichler (Menispermaceae) possess a significant antidepressant effect in 
two animal models of depression; forced swim test and reserpine test in mice (Mendonça-Netto 
et al., 2008). A study undertaken to investigate the antidepressant potential of total alkaloids 
isolated from Semen Zizyphi Sponosae (SZS) showed that total alkaloids of SZS significantly 
reduced immobility time compared with the control group in the TST and FST in mice and 
remarkably inhibited the decrease of hypothermia in reserpine-induced-hypothermia (Qiao et al., 
2011). Experimental data reported that diterpene alkaloids of Aconitum baicalensis exhibit 
antidepressant effects possibly via the modulation of sensitivity to serotonin (Nesterova et al., 
2011). 
Several literatures had reported numerous preclinical outcomes supporting the role of saponins as 
natural cure for depression and warranted their inclusion in antidepressant drug discovery 
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programs (Abbas et al., 2015). Saponins have been demonstrated to modulate various 
neurochemical pathways attributed to the onset of depression (Chen et al., 2014). Scientific 
evidence revealed that saponins possesses neuroprotective effect via the inhibition of apoptosis 
and intraneuronal calcium dynamics (Xiang et al., 2011). The orthodox antidepressants together 
with saponins have been reported to reduce oxidative stress (Xu et al., 2010). Total saponins 
from Areca catechu nut (Abbas et al., 2015), Asparagus racemosus (Singh et al., 2009), 
Bupleurum falcatum (Sun et al., 2012), Panax ginseng (Dang et al., 2009), Panax notoginseng 
(Xiang et al., 2011) and Trichopus zeylanicus (Rishikesh et al., 2012)  have been shown to 
exhibit antidepressant potentials in rodents using various behavioural paradigms. Moreover, 
numerous bioactive saponins including bacopasides (bacopaside I, bacopaside II and 
bacopasaponsin C) derived from Bacopa monnieri (Liu et al., 2013; Rauf et al., 2013), 
ginsenosides Rb3 (P. notoginseng) (Cui et al., 2012) and Yuanzhi-1 (a triterpenoid saponin 
isolated from dried root of Polygala tenuifolia) had demonstrated potent antidepressant activity 
in rodents using various animal models of depression (Jin et al., 2014).  
Cannabis terpenoids such as linalool, citronellol, and α-terpinen have been shown to possess 
significant antidepressant effect by causing a reduction in the duration of immobility in mice 
(Mander and Lui, 2010). The effective anxiolytic and antidepressant potential of Valerian 
officinalis L. extracts have long been attributed to the presence of a wide range of monoterpenes 
and sesquiterpenes (Kennedy and Wightman, 2011). 
 
 
 
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2.7 ANIMAL MODELS OF DEPRESSION 
2.7.1 Acute Models 
2.7.1.1 Forced Swimming Test (FST) 
The forced swimming test, a behavioural model originally described by Porsolt et al., (1977) has 
been designed to be “a primary screening test for antidepressant” (Petit-Demouliere et al., 2005). 
This to a large extent is as a result of its strong predictive validity, good reliability, some face 
validity, poor construct validity and its capacity to meet the high through-put demands of the 
pharmaceutical industry (Rupniak, 2003). The assumption of a state of immobility when rodents 
are introduced into an inexorable cylinder of water, is thought to cease struggling and remain 
floating motionless in the water making only movements necessary to keep its head above water. 
The FST models a very precise cluster of stress-induced behaviours and is exquisitely sensitive 
to monoaminergic manipulations (Holmes, 2003).  In an effort to enhance the sensitivity of the 
traditional FST in rodents, a modified forced swimming test has been developed. These 
alterations enabled investigators to distinguish specific behavioural components of active 
behaviours, namely; climbing and swimming (Cryan et al., 2002; Lucki, 1997). The major 
advancement of the modified FST over its traditional counterpart is that demonstrates that 
catecholaminergic agents diminish immobility with a parallel increase in climbing behaviour, 
whereas serotonin related drugs causes decline in immobility but increase swimming behaviour 
(Rénéric et al., 2001). 
2.7.1.2   Tail Suspension Test (TST) 
The tail suspension test is a rodent behavioural test suitable for the assessment of potential broad 
spectrum antidepressant drugs, and evaluation of other alteration that is expected to affect 
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depression related behaviours (Can et al., 2012). Mice are suspended by their tails and after 
initial escape-oriented movement, develop an immobile posture in such an inescapable stressful 
situation. The stressful situation is associated with the haemodynamic stress of being hung by 
their tail (Thierry et al., 1986). Acute antidepressant treatment decreases immobility scores. TST 
is a valuable tool in drug discovery for high-throughput screening of prospective antidepressant 
and to evaluate the effects of environmental, neurobiological, and genetic manipulations linked 
with depression (Crowley et al., 2005).  
2.7.2 Chronic Model 
2.7.2.1 Open space swim test 
The open space swim test model originally developed by  Sun and Alkon, (2003) was based on 
the   use   of  continual   sessions   of   the   forced   swim test   (FST) where rodents gradually 
build up a generalized impassive behaviour of low   distance   swum   and   long   duration   of   
immobility. This behaviour stabilizes with   the   repetition of   swimming sessions   over   
periods of weeks (Stone and Lin, 2011). The model exhibits strong predictive, face and 
constructs validity in that it is sensitive to chronic antidepressants but not receptive to anxiolytics 
or antipsychotics (Stone et al., 2008). The model is known to employs a wider swimming area 
than the traditional FST and thus can be useful in studying interactions of depressive behaviour 
with behavioural flexibility and perseveration. The model represents an inescapable stress 
accompanied by changes in neural activity and brain cell proliferation that are characteristic of 
depression, but less effective in producing anhedonia (Stone and Lin, 2011).  
 
 
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2.8 TRICHILIA MONADELPHA 
 
 
Figure 2.1   Trichilia monadelpha plant  
Botanical name:  Trichilia monadelpha (Thonn.) J.J. de Wilde 
Family:   Meliaceae  
Local names:   Twi: Tanduro (Ghana),   Nzema: Tenuba (Ghana), Yoruba: ako rere (Nigeria) 
Commercial status: Class IV 
2.8.1    Plant morphology 
Trichilia monadelpha is a small evergreen, fast growing hairless tree with a large open spreading 
crown. It can grow to about 20-60 feet tall; bole straight and cylindrical, usually low-branching, 
up to 40–60 cm in diameter and lacks buttresses. The plant stem is woody, asymmetrically 
twisted and with a characteristic knobby twigs. The stem bark appears pale greenish with its 
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surface showing some slight exudates of whitish latex with a pale brown slashes. The leaves are 
compound, imparipinnate, opposite sporadically curled about 50 cm long with 3-7 pairs of 
leaflets. Each leaflet is borne on a petiole which is about 4-13 cm long. It has a dense, terminal 
inflorescence with an axillary panicle 12-21 cm long. The flowers which are unisexual appear 
tubular in shape and greenish-yellow in colour. Its fruits are obovoid to globose in shape, 
pendulous, and dotted with glands that are attractive to insects (Abbiw, 1990; Lemmens, 2008). 
2.8.2    Geographical profiling  
Trichilia monadelpha is an African tropical under storey tree that dwells in lowland semi-
deciduous secondary jungle and often found along river banks and in other moist areas. It is 
found from Guinea to DR Congo, and south to north Angola. In Ghana, it is located throughout 
the Brong-Ahafo and Ashanti Regions (Lemmens, 2008). 
2.8.3    Traditional uses     
Trichilia monadelpha is being used traditionally for managing diverse medical conditions 
whereas other parts of the tree is also utilised for several domestic and agricultural purposes.  
2.8.3.1    Medicinal 
In Ghana and Nigeria, the stem is chewed for treating cough (Burkhill, 1997; Burkill, 1985). A 
bark decoction is also taken to sooth cough (Lemmens, 2008). A decoction of its stem bark is 
known to possess some sedative effects and occasionally used as an alcoholic beverage and 
stimulant  (Burkill, 1985). Herbal preparation from the root is used for treating diarrhoea, 
dysentery, gout, ulcers and other gastrointestinal complaints (Busia, 2007; Lemmens, 2008). The 
roots and stem barks can be utilised as genital arousal and usually considered as aphrodisiac 
(Lemmens, 2008). Decoctions of the leaf is used to manage heart troubles and palpitations 
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(Burkhill, 1997). The stem bark of the plant can be milled into powder and applied on skin 
infections, wounds, etc. The stem bark decoctions can be taken to treat syphilis and gonorrhoea 
(Abbiw, 1990). 
2.8.3.2    Non-medicinal     
The tree is beneficial for soil improvement and soil fortification. A reddish brown dye obtained 
from the bark can be used for dyeing cloth and hides. The woof from the trunk is useful in 
producing timber, construction materials, designing wooden musical instruments, firewood etc. 
The wood is moderately durable and resist water thus it is been used in making canoes and boats.  
The seed oil is also used in cooking (Burkill, 1985; Lemmens, 2008).  
2.8.4    Plant photochemistry  
Busia, (2007) reported that chemical constituents identified in T. monadelpha in Ghana include 
tannins (protocatechuic acid), reducing sugars, and limonoids (dregeanin, heudelobin, etc). 
Alkaloids and tannins have been identified from the stem bark (Lemmens, 2008). However, there 
exists little information on scientific investigation on these phytochemical constituents of T. 
monadelpha. 
 
 
 
 
 
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CHAPTER THREE 
MATERIALS AND METHODS 
3.1 STUDY DESIGN 
The study design was experimental. 
3.2 PLANT ACQUISITION AND EXTRACTION 
3.2.1 Plant acquisition and authentication 
The stem bark (together with other plant parts) of T. monadelpha was collected from Bomaa, 
Brong-Ahafo Region, Ghana (7o05`06.60``N, 2o 10`01.66``W) and authenticated at the Ghana 
Herbarium, Department of Botany, University of Ghana. 
3.2.2 Preparation of stem bark extracts 
The stem bark was chopped into pieces, air dried for fourteen days and pulverized into fine 
powder. An initial mass of 4 kg of the powdered plant bark was serially extracted with petroleum 
ether, ethyl acetate and 70% ethanol over a 72-hour period using cold maceration technique. The 
weight of the residue after air-drying was determined before the subsequent extraction. The 
resulting extracts were concentrated under reduced pressure at 40-60°C to a dark brown syrupy 
mass in a rotary evaporator. They were further dried using a water-bath, and stored. The 
percentage yield of each crude extract was then calculated. 
The research was conducted in the Animal Experimentation Unit of the School of Biomedical 
and Allied Health Sciences and the Department of Pharmacology and Toxicology, University of 
Ghana. All behavioural studies were performed in the light cycle between 7:30 a.m and 2:30 p.m 
with experimentally naive I.C.R. mice. 
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This study was approved by the College of Health Sciences Ethical and Protocol Review 
Committee, University of Ghana and was assigned a protocol identification number: MS-Et/M.3-
P31/2015-2016. 
3.3 QUALITATIVE PHYTOCHEMICAL ANALYSIS 
The extracts were screened for the presence of phytochemical constituents such as alkaloids, 
glycosides, tannins, sterols, flavonoids, terpenoids and saponins as described by Trease and 
Evans (1989). 
3.3.1 Test for tannins 
An amount 0.2 g of each extract was boiled with 25 ml of water for 5 minutes, cooled and 
filtered. The volume was then adjusted to 25 ml. To 1 ml aliquot of each extract was added 10 ml 
of water and 2 drops of 1% ferric chloride for the appearance of a blue-black or green precipitate. 
3.3.2 Test for glycosides 
An amount of 0.2 g of each extract was warmed with 5 ml dilute H2SO4 on a water bath for 2 
minutes. The mixture was cooled, filtered and 4 drops of 20 % NaOH was added to each filtrate. 
A volume of 1ml of Fehling`s A and B solutions were added to each filtrate, warmed and 
observed for a red-brown precipitate. 
3.3.3 Test for saponins 
An amount of 0.2 g of each extract was shaken vigorously with about 10 ml of water in a 
stoppered test tube and observed for the presence of a persistent froth. 
3.3.4 Test for alkaloids 
An amount 0.2 g of each extract was boiled with 10 ml of dilute HCl for 5 minutes. The 
supernatant liquid was filtered into another test tube and 1ml of the filtrate taken, into which 3 
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drops of Dragendorff`s reagent (potassium bismuth iodide solution) was added. The mixture was 
shaken and observed for the appearance of an orange spot precipitate. 
3.3.5 Test for flavonoids 
A volume of 10 ml of 98% ethanol was added to 0.2 g of each extract. A small amount of zinc 
metal was added to the resulting extracts followed by drop wise addition of concentrated HCl. 
They were examined for the appearance of colours ranging from orange to red (flavones), orange 
to crimson (flavonols), crimson to magenta (flavonones). 
3.3.6 Test for sterols 
An amount of 0.2 g of each extract was added to 2 ml of chloroform and filtered. A volume of 2 
ml of acetic anhydride was added to 1 ml of the filtrate after which few drops of concentrated 
H2SO4 were carefully added along the sides of the test tube. A violet to blue colouration was an 
indication of the presence of sterols. 
3.3.7 Test for terpenoids  
An amount of 0.2 g of each extract was added to 2 ml of chloroform in a test tube followed by 
addition of 1 ml of concentrated H2SO4. A reddish-brown colouration at interface shows the 
presence of terpenoids.  
3.4 ANIMAL HUSBANDARY 
Nine hundred and seventy (970) ICR mice (20 – 25 g) were obtained from the Nugochi 
Memorial Institute for Medical Research, University of Ghana and kept at the Animal 
Experimentation Unit of the Department of Microbiology, School of Biomedical and Allied 
Health Science, University of Ghana. The animals were housed in cages with wood shavings as 
bedding and fed with standard mice chaw, given water and maintained under the required 
laboratory conditions. All animals used in this study were handled according to the Guide for the 
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Care and Use of Laboratory Animals (N.R.C., 1996). During the study, mice were re-used after a 
time-lag of at least three months. 
3.5 PRIMARY OBSERVATION TEST 
The behavioural and neuroactive effects of the extracts were first evaluated according to 
standardized observation grid similar to that described by Irwin, (1968). ICR mice were 
randomly divided into various groups (n=7) and kept in the experimental environment for 7 days 
to acclimatize. Animals were then fasted overnight, but had access to water ad libitum, and then 
treated orally with the extracts at various doses or vehicles. The mice were observed at 0, 15, 30, 
60, 120 and 180 min, up to 24 hours after treatment for general changes in behaviour and 
physiological function as well as mortality. The animals were then assessed for behaviours 
related to neurotoxicity, central nervous system (CNS) stimulation and depression. Effects on 
autonomic functions were also noted. This test was to ensure that the right doses of extract were 
selected. 
3.6 ACUTE ANTIDEPRESSANT MODELS 
3.6.1 Tail suspension test (TST) 
The TST was carried out as previously described by Steru et al., (1985). Mice were allowed to 
acclimatize to the room for 3.5-4 hours before the test. Ten groups of mice (n=7) were treated 
with the extracts, fluoxetine and imipramine or vehicle. One hour after oral administration of the 
test drugs, mice were then suspended be the tail individually from a horizontal bar (distance from 
floor is 30 cm) using adhesive tape (distance from tip of tail is 1 cm). Duration of immobility, 
defined as the absence of all movements except those required for respiration, curling, swinging 
and pedalling behaviour was recorded by an observer for 5 min from video recordings of the test 
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with the aid of public domain software JWatcher Version 1.0. Decline in immobility score was 
an index for antidepressant effect; increase in curling behaviour was suggestive of opioidergic 
activity. 
3.6.2 Forced swimming test (FST) 
The FST was based on that described by Porsolt et al., (1977). Mice were divided into 10 groups 
of 7 animals each and received the vehicle (water), extracts, or reference drugs; fluoxetine and 
imipramine. One hour after the oral administration of the test drugs, mice were gently dropped 
individually into transparent cylindrical polyethylene tanks (25 cm high, 10 cm internal 
diameter) containing water (25 to 28 oC) up to a level of 20 cm and allowed to swim for 6 min. 
Each session was recorded by a video camera suspended approximately 100 cm above the 
cylinders. The mean immobility score (when the mouse is floating upright and makes only small 
movements to keep its head above the water) swimming (active horizontal movements) and 
climbing (active vertical movements) scores during the 6 min test was scored, with the aid of 
public domain software JWatcher Version 1.0 (University of California, Los Angeles, USA and 
Macquarie University, Sydney, Australia. Available at http://www.jwatcher.ucla.edu/). A 
reduction in immobility score was an indication of antidepressant effect. An increase in climbing 
score without commensurate change in swimming behaviour was suggestive of adrenergic 
mechanisms while an increase in swimming score without change in climbing suggested 
serotoninergic interactions. 
 
 
 
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3.7 EXTRACTION OF SOME SECONDARY METABOLITES PRESENT IN THE 
(HYDROETHANOLIC) MOST EFFICACIOUS EXTRACT 
3.7.1 Saponins (Nahapetian and Bassiri, 1975) 
A mass of 50 g of hydroethanolic extract was dispersed in 500 ml of 20% ethanol. The 
suspension was then heated over a hot water bath for 4 hours with continuous stirring at about 55 
ºC. The mixture was filtered and the residue re-extracted with another 500 ml of 20% ethanol. 
The combined extracts were then reduced to 40 ml over water bath at about 90 ºC. The 
concentrate was then transferred into a 500 ml separating funnel and a volume of 50 ml diethyl 
ether was added and shaken vigorously. The aqueous layer was recovered while the ether layer 
discarded. The purification process was repeated.  Sixty (60) ml of n- butanol was added to the 
remaining fraction. The resulting solution was washed twice with 10 ml of 5% aqueous sodium 
chloride. The remaining solution was heated in a water bath. After evaporation the sample were 
dried in the oven into a constant weight. 
3.7.2 Alkaloids (Obadoni and Ochuko, 2001; Harbone, 1973) 
A mass of 50 g of the hydroethanolic extract was weighed into a beaker. A volume of 1000 ml of 
10% acetic acid in ethanol was added, covered and allowed to stand for 4 hours. The solution 
was filtered and the resulting filtrate was concentrated on a water bath to about one-quarter of the 
original volume. Concentrated ammonium hydroxide was added drop wise until the formation of 
a precipitate was complete. The whole solution was allowed to settle and the precipitate was 
collected and washed with dilute ammonium hydroxide and then filtered. The residue was the 
alkaloids, which was dried and weighed. Qualitative phytochemical analysis was subsequently 
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done on the isolated alkaloids extract to test for the presence/absence of the other secondary 
metabolites. 
3.7.3 Flavonoids (Bohm and Kocipai-Abyazan, 1994) 
A mass of 50 g of the hydroethanolic extract was twice extracted with 500 ml of 80% aqueous 
methanol at room temperature. The whole solution was filtered through whatman filter paper No. 
42 (125 mm). The filtrate was later transferred into a crucible and evaporated into dryness over a 
water bath and weighed to a constant weight. Qualitative phytochemical analysis was 
subsequently done on the isolated flavonoids extract to test for the presence/absence of the other 
secondary metabolites. 
3.7.4 Terpenoids (Ferguson, 1956) 
A mass of 50 g of the hydroethanolic extract was soaked in ethanol for 24 hours. The resulting 
solution was filtered; the filtrate was extracted with petroleum ether. The ether extract was 
treated as total terpenoids. Qualitative phytochemical analysis was subsequently done on the 
isolated terpenoids extract to test for the presence/absence of the other secondary metabolites. 
3.7.5 Tannins (Strumeyer and Malin, 1975) 
A mass of 50 g of crude hydroethanolic was weighed into a flask and 500 ml of 80% acetone 
(v/v) was added. The resulting solution was placed in a water bath at 70°C and carefully shaken 
for 15 minutes. After cooling, the supernatant was decanted carefully. The extraction was 
repeated twice and the supernatants were combined and concentrated using a rotary evaporator at 
40 °C to obtain the crude phenolic fraction. The crude phenolic extract (2.5 g) was dissolved in 
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20 ml of ethanol and applied on a column packed with 40 g of Sephadex LH-20 gel. Ethanol was 
used as first eluent, to allow the removal of lower molecular weight phenolic compounds. Then 
50% acetone in water (v/v) was used to elute tannins. 
The ethanol and 50% acetone fractions were applied on pre-coated TLC plates by using capillary 
tubes and developed in a TLC chamber using ethanol: acetone (1:1) mobile phase. The 
developed TLC plates were air dried and observed under ultra violet light UV at both 254 nm 
and 366 nm. The TLC plates were later sprayed with anisaldehyde reagent and heated for about 1 
minute for the development of colour in separated spots. 
3.8 ACUTE ANTIDEPRESSANT EFFECT OF EXTRACTED SECONDARY      
METABOLITES FROM THE HYDROETHANOLIC EXTRACT 
3.8.1 Tail suspension test  
The procedure used was similar to that describes in section 3.8.1. 
3.8.2 Forced swimming test  
The procedure used was similar to that describes in section 3.8.2 
       
 
 
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3.9 CHRONIC ANTIDEPRESSANT EFFECT OF THE (TOTAL ALKALOIDS) MOST 
EFFICACIOUS SECONDARY METABOLITE 
3.9.1    Open space swim test 
The  method  described  by  Stone  and  Lin (2011)  with  some  slight  modifications  was  used. 
Swimming was carried out in rat tub cages (28×26×41 cm, w×h×l) filled with 13 cm high tepid 
tap water (32–34 °C). Mice were swum individually for 15 min/day on 4 consecutive days in 
order to induce  a  depressive  state  characterized  by  the  decrease  in  mobility  and  distance  
travelled  by  the mice.  Drug  treatment  started  from  day  5,  through  days  7,  10,  14,  18.  
All swim sessions were videotaped from above.  No  special  procedures  were  used  to  dry  or  
warm  the  animals  as  they rapidly dried themselves with no observable episodes of shivering. 
The distance swum was rated as the  number  of  quadrants  of  the  tub  entered  and  duration  of  
immobility  from  the  total  time  the animal  was  observed to  float, which is defined  as 
drifting with the tail fully  extended  and no motion observed in the tail or limbs. 
3.10    POSSIBLE MECHANISMS OF ACTION OF ISOLATED ALAKOID                                                             
Based on recent literature of the mechanism of action of antidepressants and the pathophysiology 
of depression, the involvement of noradrenergic, serotoninergic, Glycine/NMDA receptor 
complex and nitric oxide pathways in the antidepressant effect of the secondary metabolite were 
investigated. 
3.10.1   Involvement of noradrenergic systems 
Mice  were  pre-treated  with  reserpine  and/or α-methyldopa  (α-MD)  in  order  to  investigate  
the possible  role  of  noradrenergic  system  in  the antidepressant activity  of the alkaloids (ALK 
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30, 100 and 300 mg kg-1 p.o.).  The doses of α-MD and reserpine were chosen based on work 
done by others (Woode et al., 2010; Kukuia et al., 2014).  To  deplete  newly  synthesized  pools  
of  noradrenaline  (NA)  and  dopamine (DA),  mice  were  treated  with  a  single  dose  of α-
MD  (400  mg kg-1,  i.p.)  3.5 hours before behavioural testing.  To  deplete  vesicular  pools  of  
NA and  DA,  mice  were  treated  with  a  single dose of reserpine  (1 mg kg-1, s.c.) 24 hours 
before behavioural testing.  In  an effort to deplete both the vesicular  and  cytosolic  pools  of  
NA and  DA,  mice  were  pre-treated  with  a  combination  of reserpine (1 mg kg-1, s.c., 24 
hours before behavioural testing) and α-MD (200 mg kg-1, i.p., 3.5 hours before behavioural 
testing), respectively. The tail suspension and modified forced swimming tests were used. 
In a separate experiment, the effects of a selective α1 receptor antagonist (prazosin, 3 mg kg
-1 
p.o.) on the antidepressant actions of the ALK (30, 100 and 300 mgkg-1, p.o.), imipramine (10 
mg kg-1,  p.o.) and atomoxetine (1 mg kg-1, p.o.). Mice were grouped into twelve (12) groups 
(n=7). Groups 1 - 6 were pre-treated with prazosin (3 mg kg-1, p.o.) thirty (30) minutes before the 
ALK (30, 100 and 300 mgkg-1, p.o.), atomoxetine (1 mg kg-1, p.o.), imipramine (10 mg kg-1, 
p.o.) or saline treatment on the day of experiment.  Group 7 received saline only, group 8-10 
received the ALK (30, 100 and 300 mg kg-1 p.o.) respectively, group 11 received atomoxetine (1 
mg kg-1, p.o.) and group 12 received imipramine   (10 mg kg-1, p.o.). The tail suspension and 
modified forced swimming tests were used to assess the immobility time.  
In another experiment, the effects of a selective α  receptor antagonist (yohimbine, 3 mgkg-12  
p.o.) on the antidepressant actions of the ALK (30, 100 and 300 mg kg-1, p.o.), imipramine (10 
mgkg-1,  p.o.) and atomoxetine (1 mg kg-1, p.o.). Mice were grouped into twelve (12) groups 
(n=7). Groups 1 - 6 were pre-treated with yohimbine (3 mg kg-1, p.o.) thirty (30) minutes before 
the ALK (30, 100 and 300 mg kg-1, p.o.), atomoxetine (1 mg kg-1, p.o.), imipramine (10 mg kg-1, 
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p.o.) or saline treatment on the day of experiment.  Group 7 received saline only, group 8-10 
received the ALK (30, 100 and 300 mg kg-1 p.o.) respectively, group 11 received atomoxetine (1 
mg kg-1, p.o.) and group 12 received imipramine (10 mg kg-1, p.o.). The tail suspension and 
modified forced swimming tests were used to assess the immobility time.    
3.10.2   Involvement of serotoninergic systems 
Mice were put into twenty (20) groups, n=7 pCPA (200 mg kg-1, i.p.) was administered once 
daily for 3 consecutive days to 10 groups of animals. On the fourth day, group 1 received saline, 
groups 2- 4 received the ALK (30, 100 and 300 mg kg-1 p.o.); groups 5- 7 received fluoxetine (3, 
10 and 30 mg kg-1, p.o.), groups 8- 10 received imipramine (3, 10 and 30 mg kg-1, p.o.). The 
remaining 10 groups  received  which  did  not  undergo  pre-treatment,  received  the ALK  (30, 
100 and  300  mg kg-1, p.o.), fluoxetine (3, 10 and 30 mg kg-1, p.o.), imipramine (3, 10 and 30 
mg kg-1, p.o.) or saline on the day  of  experiment.  The tail suspension and modified forced 
swimming tests were used.    
In a separate experiment, the effects 5-HT2 receptor antagonist (Cyproheptadine, 8 mg kg
-1 p.o.) 
on the antidepressant actions of the ALK (30, 100 and 300 mg kg-1, p.o.), imipramine (10  mg 
kg-1,  p.o.) and fluoxetine (10 mg kg-1, p.o.). Mice were grouped into twelve (12) groups (n=7). 
Groups 1 - 6 were pretreated with cyproheptadine (8 mg kg-1, p.o.) thirty (30) minutes before the 
ALK (30, 100 and 300 mgkg-1, p.o.), fluoxetine (10 mg kg-1, p.o.), imipramine (10 mg kg-1, p.o.) 
or saline treatment on the day of experiment.  Group 7 received saline only, group 8-10 received 
the ALK (30, 100 and 300 mg kg-1 p.o.) respectively, group 11 received fluoxetine (10 mg kg-1, 
p.o.) and group 12 received imipramine   (10 mg kg-1, p.o.). The tail suspension and modified 
forced swimming tests were used to assess the immobility time.    
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3.10.3   Involvement of glycine/NMDA receptor complex 
Mice were initially divided into groups, A and B. Each group was further subdivided into 10 
groups each (n=7).  Each  group  of  mice  from  group  A was pre-treated with D-cycloserine  
(2.5 mg  kg-1,  i.p.) and 30 min after the first three groups received an oral dose of the ALK (30, 
100 and 300 mg kg-1 p.o) with the next three groups receiving fluoxetine (3, 10 and 30 mg kg-1 
p.o)  and the last three groups receiving imipramine (3, 10 and 30 mg kg-1, p.o). The tenth group 
received only D-cycloserine. Ten groups of mice from group B received D-serine (600 mg kg-1 
i.p.) pretreatment and 30 min after, the first three groups received an oral dose of the ALK (30, 
100 and 300 mg kg-1 p.o.) with the next three groups receiving fluoxetine (3, 10 and 30 mg kg-1, 
p.o.) and last three groups receiving imipramine (3, 10 and 30 mg kg-1, p.o.).  The tenth group 
from group B received only D-serine.  The  forced  swimming  and  tail suspension  tests  were 
used as  described  above  to  investigate  the  antidepressant  mechanism. 
3.10.4   Involvement of L-arginine-NO-cGMP Pathway 
The possible participation of L-arginine-NO-cGMP system in the antidepressant effect of the 
ALK was investigated. Mice [(n=7) in each group] were pre-treated with a sub-effective dose of 
L-arginine (750 mg kg−1, i.p., a precursor of nitric oxide (NO) or saline 15 min before the ALK 
(30, 100 and 300 mgkg−1 p.o.) administration and assessed 45 min later for immobility time in 
the TST and FST.  
In separate experiments, mice [(n=7) in each group] were pre-treated with L-NAME (30 mg 
kg−1, i.p., a non-selective nitric oxide synthase (NOS) inhibitor) or saline 15 min before  ALK 
(30, 100 and 300 mg kg−1 p.o.) administration and assessed 45 min later for immobility time in 
the TST and FST.  
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In separate experiments, mice [(n=7) in each group] were pretreated with methylene blue (10 mg 
kg−1, i.p., an inhibitor of NOS and an inhibitor of soluble guanylate cyclase(sGC) or saline 15 
min before  ALK (30, 100 and 300 mgkg−1 p.o.) administration and assessed 45 min later for 
immobility time in the TST and FST.  
In another experiment, the possible role of cyclic guanosine monophosphate (cGMP) in the 
antidepressant action of ALK was investigated. Mice received an injection of sildenafil (5 mg 
kg−1, i.p., a phosphodiesterase 5 inhibitor) or saline 15 min before ALK (30, 100 and 300 mg 
kg−1 p.o.) administration and assessed 45 min later for immobility time in the TST and FST.  
3.11. STATISTICAL ANALYSIS 
GraphPad Prism for windows version 4.03 (GraphPad Software, San Diego, CA, USA) was used 
for all data analysis. P<0.05 was considered statistically significant. Differences in means was 
analysed by one-way ANOVA followed by Newman-Kuel`s post hoc test. Doses for 50% of the 
maximal effect (ED50) for each drug were determined using an iterative computer least square 
method, with the following nonlinear regression (three-parameter logistic) equation: 
                                                                   Y = a + (b – a) 
                                                                (1 + 10 (Log ED  – X)50 ) 
 
Where, X is the logarithm of dose and Y is the response. Y starts at a (the bottom) and goes to B 
(the top) with a sigmoid shape. 
 
 
 
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CHAPTER FOUR 
RESULTS  
4.1    QUANTITATIVE AND QUALITATIVE ANALYSIS OF CRUDE EXTRACTS 
4.1.1 Yield of crude extracts 
The hydroethanolic extract (HEE) gave the highest yield followed by the ethyl acetate extract 
(EAE) and the petroleum ether extract (PEE) producing the lowest yield (Table 4.1). 
Table 4.1:  Percentage yield of crude HEE, EAE and PEE from the stem bark of Trichilia 
monadelpha 
Crude extract Initial weight (g) Final weight (g) % Yield 
PEE 4000 19.6 0.49 
EAE 3790 22.74 0.60 
HEE 3640 266.22 7.31 
 
 
 
 
 
 
 
 
 
 
 
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4.1.2   Phytochemical test 
Preliminary phytochemical screening indicated the presence of alkaloids, flavonoids, glycosides, 
saponins, sterols, tannins, and terpenoids in HEE. EAE had alkaloids, glycosides, tannins, sterols 
and terpenoids while PEE showed the presence of alkaloids, sterols, and terpenoids (Table 4.2). 
Table 4.2: Preliminary phytochemical screening crude HAE, EAE and PEE from the stem 
bark of Trichilia monadelpha 
Constituents Inference 
HEE EAE PEE 
Alkaloids Present Present Present 
Saponins Present Absent Absent 
Flavonoids Present Absent Absent 
Tannins Present Present Absent 
Glycosides Present Present Absent 
Terpenoids Present Present Present 
Sterols Present Present Present 
 
 
 
 
 
 
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4.2 IRWIN TEST 
No signs of toxic effects were manifested during the 24 hour observation period for all the three extracts except for sedation for the 
doses from 30 – 3000 mg kg-1. There were signs of analgesic effects, frequent urination and defecation in all three extracts. No death 
was also recorded after 24 hours for all the administered doses in all the three extracts (Table 4.3). 
Table 4.3:  Observations in the acute toxicity test after oral administration of PEE, EAE and HEE of T. monadelpha in mice 
 
 EAE  
PEE  HEE 
 
Dose Mortality Latency   Observed drug Dose Mortality Latency       Dose Mortality Latency Observed drug effects 
Observed drug effects 
(mg/kg) D/T  (min) effects (mg/kg) D/T  (min) (mg/kg) D/T (min)  
0 - - - 0 - - - 0 - - - 
Analgesia, 
Analgesia, urination, Analgesia, urination, 
30 - 30 urination, 30 - 30 30 - 30 
defecation defecation 
defecation 
Analgesia, 
Analgesia, urination, Analgesia, urination, 
100 - 15 urination, 100 - 30 100 - 30 
defecation defecation 
defecation 
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Sedation 
analgesia, Sedation 
Sedation, analgesia, 
300 - 15 urination, 300 - 30 analgesia, urination, 300 - 30 
urination, defecation 
defecation defecation 
 
Sedation, 
analgesia, Sedation, analgesia, Sedation, analgesia, 
1000 - 15 1000 - 15 1000 - 15 
urination, urination, defecation urination, defecation 
defecation 
Sedation, 
analgesia, Sedation, analgesia, Sedation, analgesia, 
3000    - 15 3000    - 15 3000    - 30 
urination, urination, defecation urination, defecation 
defecation 
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4.3 ANTIDEPRESSANT EFFECTS OF CRUDE EXTRACTS 
4.3.1   Tail suspension test 
4.3.1.1 Immobility score 
All three extracts, (PEE, EAE and HEE) significantly decreased immobility score (F9,60 = 
55.11 P<0.0001; F9,60 = 66.02 P<0.0001; F9,60=34.83 P<0.0001 respectively). In TST, the 
order of antidepressant efficacy calculated from the log-dose response curve (Figure 4.4) with 
regards to immobility was fluoxetine > imipramine > HEE > EAE > PEE (Emax= 90.00, ED50 = 
1.58 ± 0.2; Emax = 78.01, ED50 = 4.32 ± 0.3; Emax = 75.44, ED50 = 26.64 ± 0.6; Emax = 61.51, 
ED50 = 66.83 ± 0.6; Emax = 42.43, ED50 = 196.10 ± 1.2 respectively). HEE was the most potent 
and efficacious in reducing immobility score in TST (Table4.4). 
40 b 
40
30 **
30
20 *** *** ***
*** 20 ***
*** ***
10 ***
*** ***
*** ***
***
10
*** ***
*** ***
0 0
H 30 00 00 -3 10 30 I-3 10 30E H 0 0 0 3 0 0 3 0 0V E- 1 3 X - - I- I- E -
3 - -10 30 X -1 -3 I I-1 I-3
E EE
- - L X X IM M - - M
P E
E F FL FL I I
M V E E E L LX LX I M M
P P E
A F
EA EA F F
I I
Dose (mg/kg) Dose (mg/kg)
 
c 
40
30
20 ***
***
*** ***
10 *** *** *** ***
***
0
H 30 00 00 -3 10 30 I-3 0 0
VE E- -1 3 X
1 3
E E E- FL LX
- - - -
LX IM
I I
F F IM IMH HE HE
Dose (mg/kg)
 
            Figure 4.1:  Effects of the extracts, (a) PEE (30 – 300 mg/kg), (b) EAE (30 -300 mg/kg) and (c) 
HEE (30 - 300 mg/kg), fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on immobility 
score in TST. Data are represented as group Means ± SEM. Significantly different from vehicle: 
*** P < 0.0001 (One-way ANOVA followed by Newman-Kuel`s test) 
 
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Immobility score
Immobility score
Immobility score
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4.3.1.1 Swinging score 
All three extracts, (PEE, EAE and HEE) exhibited a significant increase in swinging (F9,60 = 
57.83 P<0.0001; F9,60 = 44.30 P <0.0001; F9,60 = 16.15 P <0.0001 respectively) scores. 
 a b 
60
*** *** 60
*** ***
*** ***
40 *** *** *** ***
*** *** 40 *** ***
** **
20
20
0
0
EH -3
0 00 0 -3 0 0 -3 0 01 30 X -1 -3 I I-1 I-3 H 30 0 0 3V - - M E - 0 0 X- -1
0
-3
0 I-3 10 30- -
EE E E FLE E FL
X
FL
X I M M V E -1 -3I I E E L X X IM
I I
P A F L L IM IMP P E EA EA F F
Dose (mg/kg) Dose (mg/kg)
 
 
60
c 
*** ***
*** ***
40 ***
** *** ******
20
0
EH -3
0
10
0
30
0 -3 10 30 I-3 10 30
V EE
- - LX X- X- - -E E F L L I
M I I
IM IMH E F FH HE
Dose (mg/kg)
 
            Figure 4.2:  Effects of the extracts, (a) PEE (30 – 300 mg/kg), (b) EAE (30 -300 mg/kg) and (c) 
HEE (30 - 300 mg/kg), fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on swinging 
scores in TST. Data are represented as group Means ± SEM. Significantly different from 
vehicle: *** P < 0.0001; ** P < 0.001 (One-way ANOVA followed by Newman-Kuel`s test) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Swinging score
Swimming score
Swinging score
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4.3.1.1 Curling score 
All three extracts, (PEE, EAE and HEE) generally exhibited a significant increase in curling 
score in a dose-dependent manner (F9,60 = 8.236 P<0.0001; F9,60 = 44.85 P<0.0001; F9,60 = 
12.59  P <0.0001 respectively). 
 
 
a b 
20
*** 25 ***
15 ******
** 20
10 15
10
5
5
0
0
EH -3
0
10
0 00 -3 10 30X - - I-
3 0 0
3 I-1 I-3 EHV E -3
0 00 00 -3 10 0- -3 I-
3
-1
0
-3
0
E EE
- - L X X IM M M V E -1 -3 LX X X M I I
P P PE
E F FL FL I I A E E F L L I IM IME A A F FE E
Dose (mg/kg) Dose (mg/kg)
 
c 25
*** ***
20 *
15
10
5
0
EH -30 0 0 3 0 0 3 0 0V E -1
0 -30 LX
- -1 -3 I- I-1 I-3
E EE EE F FL
X LX IM IM IM
  H H H
F
    
  
Dose (mg/kg)
 
              Figure 4.3:  Effects of the extracts, (a) PEE (30 – 300 mg/kg), (b) EAE (30 -300 mg/kg) and (c) 
HEE (30 - 300 mg/kg), fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on curling scores 
in TST. Data are represented as group Means ± SEM. Significantly different from vehicle: *** P 
< 0.0001 (One-way ANOVA followed by Newman-Kuel`s test) 
 
 
 
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Curling scores
Curling scores
Curling scores
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150
HEE
PEE
100 EAE
FLX
IMI
50
0
1 2 3
Log Dose
 
            Figure 4.4: Log dose-response curve of the extracts, PEE (30 – 300 mg/kg), EAE (30 -300 
mg/kg) and HEE (30 - 300 mg/kg), fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) 
showing a % decrease in immobility score in TST in mice. Each point is the mean ± S.E.M of 7 
mice. 
 
 
4.3.2 Forced Swimming Test 
4.3.2.1. Immobility score 
All three extracts, (PEE, EAE and HEE) significantly decreased immobility score (F9,60 = 
87.33 P<0.0001; F9,60= 95.33 P<0.0001; F9,60= 81.73 P<0.0001 respectively) in a dose 
dependent manner. In FST, the order of antidepressant efficacy calculated from the dose 
response curve (Figure 4.8) with regards to immobility was fluoxetine > HEE > imipramine > 
EAE > PEE (Emax = 81.79, ED50 = 2.88 ± 0.2; Emax = 80.55, ED50 = 10.86 ± 1.0; Emax = 66.74, 
ED50 = 35.92 ± 0.6; Emax = 59.34, ED50 = 108.70 ± 0.6; Emax = 54.40, ED50 = 132.20 ± 6.0 
respectively).  From the calculated ED50 and Emax values, HEE was the most potent and 
efficacious among all the test extracts but less potent than fluoxetine and imipramine in 
reducing immobility score in FST (Table 4.4). 
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% Decrease in immobility
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a b 40
40
30
30
*** *** ***
***
*** *** 20 *** ***20 *** *** *** ****** ***
***
10 *** 10*** ***
0 0
H 0 0 H 0 0 0 3 0 0 3 0 0
E -3 10 30
0 -3 0
X -1 -3
0 I-3 10 30 E 3 0 0 - 1 3 I- 1 3
V E - -
-
L X X IM I I
- V - -1 -3 X - - M I- I-E L X X I
E E EE E F L
M M A E E F L L IM IM
P F F
L I I E A A F F
P P E E
Dose (mg/kg) Dose (mg/kg)
  
c4 0
30
***
20
*** ****** ***
***
10 *** *** ***
0
 
H 30 00 00 -3 10 30 I-3 10E 3
0
V EE
- -1 3 X - - I- I-
EE EE
-
FL LX
M
LX I M M
H F F I IH H
Dose (mg/kg)
 
             Figure 4.5:  Effects of the extracts, (a) PEE (30 – 300 mg/kg), (b) EAE (30 -300 mg/kg) and (c) 
HEE (30 - 300 mg/kg), fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on immobility 
score in FST. Data are represented as group Means ± SEM.  *** P < 0.0001; compared to 
vehicle-treated group (One-way ANOVA followed by Newman-Kuel`s test) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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Immobility score
Immobility score
Immobility score
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4.3.2.1 Swimming score 
All three extracts, (PEE, EAE and HEE) showed a significant increase in swimming (F9,60 = 
82.04 P<0.0001; F9,60 = 108.1 P <0.0001; F9,60 = 55.06 P <0.0001 respectively) scores. 
 
 
b 
a 50
50
*** ***
*** 40
40 *** ***
*** 30 ***
30 *** *** *** *** *** *** ***
*** *** ***
*** 20
20
10
10
0
0
H 0 0 0 3 0 0 3 0 0 H 30 00 00 -3 0 0- - -
3 0 0
3 0 0 1 3 I 1 3 E - 1 3 X -1 -3 I I-1 I-3
VE E- E-
1 -3 LX X- X- - -IM I I V E - -
M
E M M A E E
L LX XF L I IM IM
P PE PE
E F FL FL I I E A A F FE E
Dose (mg/kg) Dose (mg/kg)
 
 
 
c 
50
*** ***
40
*** ***
30 ***
*** ***
*** ***
20
10
0
0 0 0 3 0 0
EH -3 0 0 X- -1 -3 I-
3 10 30
V E -1 3 - -E E- L LX LX IM
I I
M M
HE HE HE
F F F I I
Dose (mg/kg)
 
 
             Figure 4.6:  Effects of the extracts, (a) PEE (30 – 300 mg/kg), (b) EAE (30 -300 mg/kg) and (c) 
HEE (30 - 300 mg/kg), fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on swimming 
scores in FST. Data are represented as group Means ± SEM.  *** P < 0.0001; compared to 
vehicle-treated group (One-way ANOVA followed by Newman-Kuel`s test) 
 
 
 
 
 
 
 
 
 
 
 
 
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Swimming score
Swimming score
Swimming score
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4.3.2.2 Climbing score 
All three extracts, (PEE, EAE and HEE) exhibited a significant increase in climbing (F9,60  = 
10.71 P<0.0001; F9,60 = 18.14 P <0.0001; F9,60 = 14.47 P <0.0001respectively) scores. 
 
 
a b 25
25
20 ***
*** ***
20 *** ******
***
** * ** ** 15 *
15
10
10
5
5
0
0
H 30 00 00 -3 10 30 I-3 0 0
H 30 00 00 -31 3 E - 1 3 X -1
0 0 3 0 0
E - 1 3 X -
3 I- I-1 I-3
V EE E- E- FL LX
- - - -
LX IM
I I V E E- E- MIM IM A A F
L
FL
X LX I
E F I
M IM
P PE PE F F E E
A
Dose (mg/kg) Dose (mg/kg)
  
c 
25
20 *** ****** ***
** ***15
10
5
0
H 30 00 00 -3 10 30E - X - - I-
3
1 3 I-1
0 0
V E - - L X X IM I
-3
E EE EEH FH H F
L FL IM IM
Dose (mg/kg)
 
 
             Figure 4.7:  Effects of the extracts, (a) PEE (30 – 300 mg/kg), (b) EAE (30 -300 mg/kg) and (c) 
HEE (30 - 300 mg/kg), fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on climbing 
scores in FST. Data are represented as group Means ± SEM.  *** P < 0.0001; ** P < 0.001; 
compared to vehicle-treated group (One-way ANOVA followed by Newman-Kuel`s test) 
 
 
 
 
 
75 
 
Climbing score
Climbing score
Climbing score
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100
HEE
80 EAE
PEE
60 FLX
IMI
40
20
0
0 1 2 3
Log Dose
 
            Figure 4.8: Log dose-response curve of the extracts, PEE (30 – 300 mg/kg), EAE (30 -300 
mg/kg) and HEE (30 - 300 mg/kg), fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) 
showing a % decrease in immobility score in FST in mice. Each point is the mean ± S.E.M of 7 
mice.    
 
 
Table 4.4: ED50 and Emax values of test drugs used in tail suspension and forced swim tests 
 
          DURATION OF IMMOBILITY 
TEST DRUG ED50                     E  m  a  x    
 
 FLX 1.58 ± 0.2 90.0 
TST IMI 4.32 ± 1.1 78.01 
PEE 196.1 ± 12.2 42.43 
EAE 66.83 ± 5.6 61.51 
HEE 26.64 ± 3.6 80.55 
  
 FLX 2.88 ± 0.6 81.79 
 IMI 10.86 ± 1.5 66.74 
         FST PEE 132.20 ± 14.2 54.40 
EAE 108.70 ± 10.6 59.34 
HEE 35.92 ± 2.0 75.44 
 
 
 
 
 
 
 
 
76 
 
% Decrease in immobility
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4.4   ANALYSIS OF EXTRACTED SECONDARY METABOLITES FROM THE 
HYDROETHANOLIC EXTRACT 
4.4.1 Yield of isolated secondary metabolites 
Alkaloids, terpenoids, flavonoids, saponins and tannins were extracted from HEE (Table 4.5.) 
Table 4.5:  Phytochemical screening and yield of secondary metabolites isolated from crude 
HEE from the stem bark of Trichilia monadelpha 
Secondary metabolites Final weight (g) % Yield Phytochemical Test 
Saponins 4.05 8.05 Saponins present 
Terpenoids present 
Steroids present 
Glycosides present 
Flavonoids 1.52 3.03 Flavonoids present 
Glycosides present 
Alkaloids 2.11 4.20 Alkaloids present  
Terpenoids 0.31 0.62 Terpenoids present 
Tannins 0.76 1.52 Tannins present 
 
4.5   ACUTE ANTIDEPRESSANT EFFECTS OF SECONDARY METABOLITES 
EXTRACTED FROM THE (HYDROETHANOLONIC) MOST EFFICACIOUS 
EXTRACT 
4.5.1   Tail suspension test 
Three secondary metabolites, SAP, FLV and ALK significantly decreased immobility score 
(F9,60 = 82.40 P< 0.0001; F9,60 = 154.2 P<0.0001; F9,60 = 100.6 P<0.0001 respectively). In 
TST, the order of antidepressant efficacy calculated from the dose response curve (Figure 
4.12) with regards to immobility score was fluoxetine > imipramine > ALK > SAP > FLV 
(Emax = 96.0, ED50 = 1.86 ± 0.9; Emax= 95.4, ED50 =4.58 ± 1.2; Emax = 71.1, ED50 = 122.70 ± 
5.4; Emax = 55.3, ED50 = 227.20 ± 6.9; Emax = 20.7, ED50 = 912.80 ± 9.2 respectively). From 
the calculated ED50 and Emax values, the ALK was the most potent and efficacious among all 
the test drugs in reducing immobility score in TST (Table 4.6)
77 
 
University of Ghana http://ugspace.ug.edu.gh
 
b
40
a 40
30
*** ***
30 ***
20 ***
20 *** ******
*** *** 10 ****** ***
10 *** ***
***
0
0
H 0 0 0 3 0 0 3 0 0
H 30 00 00 0
E 3 0 - -
E -
3 1 30 I-3 10 30 V
-
N -1 -3
0 X -1 -3 I I-1X X -
3
L IM I
V V- -1 -3 LX X- X- IM I
- I- A N N F FL FLM M T A A I
M IM
FL LV LV F FL FL I IF F T T
Dose (mg/kg) Dose (mg/kg)
 
c 40 d 40
30 30
***
20 *** *** *** 20 ***
*** ***
*** ***
10 *** *** 10 ***
***
*** ***
0 0
H 30 0 0 -3 0 0 -3 0 0 H 0 0 0 -3 0 0 -3 0 0
VE K- -1
0 30 X -1 -3 I I-1 I-3 E 3 0- M V R-L X X I -1 -3
0 X 1 3 I 1 3X- X- M I- I-
L K M M R R
L L L I M M
A L L
K F FL FL I I TE TE
F
TE F F
I I
A A
Dose (mg/kg) Dose (mg/kg)
 
e
40
30 ***
***
20 *** ***
*** ***
10 *** ******
0
H 30 00 00 -3 10 30 I-3 10 30
VE P- -1 -3 LX X- X- M I- I-A I M MS SA
P AP F FL FL I IS
Dose (mg/kg)
 
             Figure 4.9:  Effects of the secondary metabolites, (a) FLV (30 – 300 mg/kg), (b) TAN (30 -300 
mg/kg), (c) ALK (30 - 300 mg/kg), (d) TER (30- 300 mg/kg) and (e) SAP (30 -300 mg/kg), 
fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on immobility score in TST. Data are 
represented as group Means ± SEM. Significantly different from vehicle: *** P < 0.0001 (One-
way ANOVA followed by Newman-Kuel`s test) 
 
 
 
78 
 
Immobility score Immobility score
Immobility score
Immobility score
Immobility score
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4.5.1.1 Swinging score 
FLV and ALK demonstrated a significant increase in swinging scores (F9,60  = 78.70 P<0.0001; 
F9,60 = 50.64. respectively). 
a b
60 60
*** ***
*** ****** ***
***
***
40 *** *** 40 *** ***
***
20 20
0 0
H 0 0 0 3 0 0 3 0 0 H 30 00 00 -3 0 0 3 0 0E -3 0 0 - 1 3 I-1 1 3
E - 1 3 X -1 -3 I
-
I-1 I-3
V LV V- V-
3 LX X- - I- I- V N - - L X X IM
F L L F FL FL
X IM IM IM A N N L L
M M
T A A
F F F I I
F F T T
Dose (mg/kg) Dose (mg/kg)
  
c d
60 60
*** *** *** *** ***
*** *** ***
*** *** ***40 ***40
*** *** ***
20 20
0 0
H 30 00 00 -3 0 0 3E - 1 3 X -1 -3 I
-
I-1
0 0
-3 E
H -3
0 001 30
0 -3 10X - -3
0 I-3 0 0
V K - - M I V R - - L X X M I
-1 I-3
L LKA L
K FL LX LX I IM IM TE ER ER F
I M M
F F T T F
L FL I I
A A
Dose (mg/kg) Dose (mg/kg)
  
e
60
***
*** *** ******
40 ***
20
0
EH 30 00 00 -3 10 30 -3 10 30V - 1AP P- P-
3 LX - -
I I- I-
S A A F FL
X
FL
X IM IM IM
S S
Dose (mg/kg)
 
 
Figure 4.10:  Effects of the secondary metabolites, (a) FLV (30 – 300 mg/kg), (b) TAN (30 -300 mg/kg), 
(c) ALK (30 - 300 mg/kg), (d) TER (30- 300 mg/kg) and (e) SAP (30 -300 mg/kg), fluoxetine (3 -30 
mg/kg) and imipramine (3 -30 mg/kg) on swinging scores in TST. Data are represented as group Means 
± SEM. Significantly different from vehicle: *** P < 0.0001 (One-way ANOVA followed by Newman-
Kuel`s test).  
 
79 
 
Swinging score Swinging score
Swinging score
Swinging score
Swinging score
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4.5.1.2 Curling score 
SAP and ALK displayed a significant increase in curling scores (F9,60  = 17.58 P<0.0001; F9,60 
= 9.655 P <0.0001 respectively). 
 
b
a 15
15
10
10
5
5
0
0
H 30 00 00 -3 0 0 3 0 0H 30 00 00 -3 10 30 I-3 10 30 E
1 3 I- 1 3
VE
- -1 -3 X - - M I- I-
LV
-
V-
1
V-
3 X - - M I- I- V N N N FL LX LX I M M
F L L F
L
FL
X X I M M
FL I I T
A
TA TA F F
I I
F F
Dose (mg/kg) Dose (mg/kg)
 
d
15
c
20
*** 10
***
15
*
10 5
5
0
0
EH 3
0 00- 1 30
0 -3 10 30 I-3 10 30
EH 30 00 0 3 0 0 3 0 0 V - -
X X- X- M I- -0 - 1 3 I- 1 3 R L I I
V M MLK
- -1 -3 LX X- X- IM I- I- E R R F L L I I
A LK LK F FL FL I
M IM T TE TE F F
A A
Dose (mg/kg) Dose (mg/kg)
 
e
25
***
20 ***
***
15
10
5
0
VE
H -30 0-10 -30
0
X-
3 -10 -30 I-3 10 30
AP P P FL X X IM
I- -
A A FL FL IM IM
I
S S S
Dose (mg/kg)
 
             Figure 4.11:  Effects of the secondary metabolites, (a) FLV (30 – 300 mg/kg), (b) TAN (30 -300 
mg/kg), (c) ALK (30 - 300 mg/kg), (d) TER (30- 300 mg/kg) and (e) SAP (30 -300 mg/kg), 
fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on curling scores in TST. Data are 
represented as group Means ± SEM. Significantly different from vehicle: *** P < 0.0001 (One-
way ANOVA followed by Newman-Kuel`s test) 
 
80 
 
Curling score Curling score
Curling score
Curling scores
Curling scores
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150
SAP
FLV
100 ALK
FLX
IMI
50
0
0 1 2 3
Log Dose
 
Figure 4.12: Log dose-response curve of the secondary metabolites, FLV (30 – 300 mg/kg), ALK (30 - 
300 mg/kg) and SAP (30 -300 mg/kg), fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) showing 
a % decrease in immobility score in TST in mice. Each point is the mean ± S.E.M of 7 mice. 
 
4.5.2   Forced Swimming Test 
4.5.2.1 Immobility score 
All five secondary metabolites (FLV, TAN, ALK, TER and SAP) significantly decreased 
immobility score (F9,60 = 101.7 P<0.0001; F9,60 = 164.4 P<0.0001; F9,60 = 91.43 P<0.0001; 
F9,60 = 82.12 P<0.0001; F9,60 = 72.80 P<0.0001 respectively). In FST, the order of 
antidepressant efficacy calculated from the dose response curve (Figure 4.16) with regards to 
immobility score was fluoxetine >  imipramine > ALK > SAP > FLV > TER > TAN (Emax = 
98.3, ED50= 2.21 ± 1.2; Emax = 98.0, ED50 = 6.80 ± 1.8; Emax = 76.4, ED50 = 83.15 ± 6.3; Emax = 
66.1, ED50 = 141.10±7.4;Emax = 40.5, ED50 = 376.70 ± 9.2; Emax = 40.3, ED50 = 408.80 ±10.3; 
Emax = 24.8, ED50 = 1348.00 ± 9.7 respectively). From the calculated ED50 and Emax values, 
ALK was the most potent and efficacious among all the test drugs in reducing immobility score 
in FST (Table 4.6) 
81 
 
% Decrease in immobility
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a b 40
50
** ***
40 30
***
*** ***
30 ***
*** 20 *** *** ***
20 *** *** *** 10 *** ***
10 *** ***
0
0
0 0
H 0 0 0 -3 0 0 3 0 0 E
H
- -3 10 30
0 -3 0 0 3 0 0
3 0 0 1 3 I 1 3 V - - X X-
1 -3 I- 1 3
E - 1 3 X - - I- I- N L X IM
I- I-
V V - - L X X IM A N N F L L IML M M F F I
M
F FL
V LV F FL FL I I T A AF T T
Dose (mg/kg) Dose (mg/kg)
  
d
c 40
50 ***
30 ***
40 *** ***
30 20 ******
*** *** ***
20 *** *** ****** *** 10 *** ***
10 *** ***
0
0
H 30 00 00 -3 10 30 I-3 0 0H 30 00 00 -3 10 30 I-3 10 30 VE -E - - - - - R -1 3 X
- - 1 3- L X X M I
- I-
V
LK
-1 -3 X M I I R R L L I M M
LK LK
F
FL LX LX I M M TE E E F F I I
A F F I IA A T T
Dose (mg/kg) Dose (mg/kg)
 
e
50
40
***
30
***
*** ***
20 *** *** ***
10 *** ***
0
H 30 00 00 -3 10 0 3 0 0
VE P- 1 3 X
3 I-
- - L X- X- IM I
-1 I-3
A P P F L L IMS I
M
SA SA F F
Dose (mg/kg)
 
             Figure 4.13: Effects of the secondary metabolites, (a) FLV (30 – 300 mg/kg), (b) TAN (30 -300 
mg/kg), (c) ALK (30 - 300 mg/kg), (d) TER (30- 300 mg/kg) and (e) SAP (30 -300 mg/kg), 
fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on immobility score in FST. Data are 
represented as group Means ± SEM. Significantly different from vehicle: *** P < 0.0001 (One-
way ANOVA followed by Newman-Kuel`s test). 
 
82 
 
Immobility score Immobility score
Immobility score
Immobility score
Immobility score
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4.5.2.1 Swimming score 
All five secondary metabolites (FLV, TAN, ALK, TER and SAP) showed a significant 
increase in swimming (F9,60 = 58.08 P<0.0001; F9,60 = 93.05 P<0.0001;F9,60 = 69.09 
P<0.0001; F9,60 = 89.25 P<0.0001; F9,60 = 42.95 P<0.0001 respectively) score. 
b
a
50 50
*** ***
*** ***
40 40
*** ***
30 30
*** *** *** *** ***
***
*** *** ***** **
20 20
**
10 10
0 0
H 0 0 0 3 0 0 3 0 0 H 30 00 00 -3 10 30 -3E 3 0 0 - 1
0 30
V V- 1 3 X -
1 -3 I- E II-1 I-3 V N- -1 -3 LX X- X- M I- I-I
FL LV
-
LV
- FL FL
X X IM
FL IM IM
A N N F FL FL IM MT A A I
F F T T
Dose (mg/kg) Dose (mg/kg)
  
c
50 d
*** 50
***
40 *** ***
*** 40
*** ***30 *** *** ******
*** 30 *** ******
20 * * ***
20
10
10
0 0
H 30 00 00 -3 10 30 I-3 0 0E - 0 0 0 3 0 0 3V -1 -3 X - - M I-
1 I-3 EH -3 10 30 X- -1 -3 I- I-1
0
I-3
0
K
AL LK LK F
L LX LX I IM IM V ER R- R- FL LX LX IM IM IM
A A F F T TE TE F F
Dose (mg/kg) Dose (mg/kg)
  
 
e
50
***
***
40
***
30 *** ***
*** *** ***
20
10
0
EH 30 00 00 -3 -10 -30
3
- 1 3 X -MI I-1
0 -30V P - - L X X I I
SA P P FSA SA F
L FL IM IM
Dose (mg/kg)
 
 
             Figure 4.14:  Effects of the secondary metabolites, (a) FLV (30 – 300 mg/kg), (b) TAN (30 -300 
mg/kg), (c) ALK (30 - 300 mg/kg), (d) TER (30- 300 mg/kg) and (e) SAP (30 -300 mg/kg), 
fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on swimming scores in FST. Data are 
represented as group Means ± SEM. Significantly different from vehicle: *** P < 0.0001; ** P 
< 0.001; * P < 0.01 (One-way ANOVA followed by Newman-Kuel`s test) 
 
 
 
83 
 
Swimming score Swimming score
Swimming score
Swimming score
Swimming score
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4.5.2.1 Climbing score 
Only SAP, TER and ALK showed a significant increase in climbing scores (F9,60 = 10.52 
P<0.0001;  F9,60 = 7.907 P <0.0001; F9,60 = 12.78 P<0.0001 respectively). 
b
a 25
25 ***
*** 20 ***20 *** ***
***
15
15 * * **
10 10
5 5
0 0
0 0 0 3 0 0 3 0 0
VE
H -3 0 0
0 0
1 3 X- -1 -3 I- I-1 I-3 E
H -3 10 30
0
X-
3
-1
0
-3
0 I-3 0I-1 I-3
0
LV V-F L LV
- FL LX LX IM IM IM V N N- N- FL LX X IMF F A L IM IMF F T TA TA F F
Dose (mg/kg) Dose (mg/kg)
 
d
25
c
***
25 20 ***
*** * ***
20
*** *** 15 * *
*** * *
15 * *
* * 10
10
5
5
0
0
H 0 0 0 3 0 0 3 0 0
EH -3
0 00 00 -3 10 0- -3 I-
3 0
-1 -3
0
VE -
3 0 0 X- -1 -3 I-1 3 I-1 I-3
V K 1 3 XL K- K- FL LX LX I
M I I ER
- - M
IM IM ER ER F
L LX LX I IM IM
A T F FAL AL F F T T
Dose (mg/kg) Dose (mg/kg)
 
 
e
25
***
20 ***
***
15 ***
* ** * *
10
5
0
H 30 00 00 -3E 1
0 30 I-3 10 30
V AP
- -1 -3 LX X- X- M I- I-I M M
S SA
P AP F LS F F
L I I
Dose (mg/kg)
 
 
             Figure 4.15:  Effects of the secondary metabolites, (a) FLV (30 – 300 mg/kg), (b) TAN (30 -300 
mg/kg), (c) ALK (30 - 300 mg/kg), (d) TER (30- 300 mg/kg) and (e) SAP (30 -300 mg/kg), 
fluoxetine (3 -30 mg/kg) and imipramine (3 -30 mg/kg) on climbing scores in FST. Data are 
represented as group Means ± SEM. Significantly different from vehicle: *** P < 0.0001; ** P 
< 0.001; * P < 0.01 (One-way ANOVA followed by Newman-Kuel`s test) 
 
 
84 
 
Climbing score
Climbing score
Climbing score
Climbing score
Climbing score
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150
SAP
FLV
100 ALK
TAN
TER
50 FLX
IMI
0
0 1 2 3
Log Dose
 
 
Figure 4.16: Log dose-response curve of the secondary metabolites, FLV (30 – 300 mg/kg), TAN 
(30 -300 mg/kg), ALK (30 - 300 mg/kg), TER (30- 300 mg/kg) and SAP (30 -300 mg/kg), fluoxetine (3 
-30 mg/kg) and imipramine (3 -30 mg/kg) showing a % decrease in immobility score in FST in mice. 
Each point is the mean ± S.E.M of 7 mice. 
 
 
Table 4.6: ED50 and Emax values of secondary metabolites and drugs used in tail suspension     
and forced swimming tests 
 
          DURATION OF IMMOBILITY 
TEST DRUG 
 ED50                      E   m  a x  
 FLX 1.86 ± 0.8 96.0 
TST IMI 4.58 ± 1.2 95.4 
FLV 912.80 ± 19.2 20.7 
ALK 122.70 ± 11.4 71.1 
SAP 227.20 ± 113.9 55.3 
  
 FLX 2.21 ± 1.2  98.3 
 IMI 6.80 ± 1.8 98.0 
FST FLV 376.70 ± 14.2 40.5 
TAN 1348.00 ± 23.7 24.8 
ALK 83.15 ± 6.3 76.4 
TER 408.80 ± 14.8 40.3 
SAP 141.10 ± 12.4 66.1 
 
 
 
 
 
85 
 
% Decrease in immobility
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4.6     CHRONIC ANTIDEPRESSANT EFFECT OF THE (ALKALOIDS) 
MOST EFFICACIOUS SECONDARY METABOLITE 
4.6.1 The open space swim test 
4.6.1.1 Open space swim test of the ALK  
The extracted total alkaloids exhibited significant antidepressant potentials in mice when 
taken through the open space swim test. From the time course  curve,  ALK caused a 
significant decline in immobility after day two of treatment and this was maintained up to the 
fourteenth day of treatment (F3,68  = 21.76 P<0.0001) (Figure 4.17a). Disparately, the ALK 
increased the number of quadrants entered (distance travelled) by the mice (F3,68 = 14.46  
P<0.0001) (Figure 4.17b). ALK was less more potent and efficacious than FLX and BUP in 
reducing immobility time which is a more reliable index for mice. Similarly, ALK was also 
the least efficacious and potent with regards to distance travelled (Figure 4.20 and Table 4.7). 
Ctrl
ALK 30 mg/kg
a Ctrl
ALK 100 mg/kg b ALK 30 mg/kg
ALK 300 mg/kg ALK 100 mg/kg
1000
500 ALK 300 mg/kg
800
400
600
300 ***
**
400 *** 200 ***
*** *** *** ***
200 *** 100
***
0 *** *** 0
0 3 6 9 12 15 18 0 3 6 9 12 15 18
Days Days
 
Figure 4.17 Effects of ALK (30 - 300 mgkg-1) treatment on the (a) duration of immobility and the (b) 
distance travelled in the open space swim test. Significantly different from control: *P<0.05, **P<0.001, 
***P<0.001 by Newman Keuls’ test. 
 
 
 
 
86 
 
Duration of immobility (s)
Distance travelled
(no. of quadrants entered)
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4.6.1.2 Open space swim test of FLX 
Fluoxetine showed a decrease in immobility time after day 6of treatment (Figure 4.18a) but 
similar    effect    as    ALK    with    regards    to    distance    travelled    (Figure    4). 
Ctrl
a CtrlFLX 3 mg/kg
b FLX 3 mg/kg
FLX 10 mg/kg
FLX 10 mg/kg
1000 FLX 30 mg/kg
FLX 30 mg/kg
400
800 ***
300
600 ***
*** ***
400 200*** ***** *** ***
***
200 *** 100 ***
*** *
0 *** 0
0 3 6 9 12 15 18 0 3 6 9 12 15 18
Days Days
 
Figure 4.18 Effects of FLX (3 - 30 mg kg-1) treatment on the (a) duration of immobility and the (b) 
distance travelled in the open space swim test. Significantly different from control: *P<0.05, **P<0.001, 
***P<0.001 by Newman Keuls’ test. 
 
 
4.6.1.2 Open space swim test of BUP 
Bupropion showed a decrease in immobility time after day 6 of treatment (Figure 4.19a) but 
similar effect as ALK with regards to distance travelled (Figure 4.19b). 
Ctrl
b BUP 3 mg/kg
a Ctrl BUP 10 mg/kg
BUP 3 mg/kg
BUP 30 mg/kg
BUP 10 mg/kg
1000 400BUP 30 mg/kg
***
800 300
600
*** 200 ***
400 ** ** ***
***
*** 100 **
200 *** ***
***
0 *** 0
0 3 6 9 12 15 18 0 3 6 9 12 15 18
Days Days
  
Figure 4.19 Effects of BUP (3 - 30 mgkg-1) treatment on the (a) duration of immobility and the (b) 
distance travelled in the open space swim test. Significantly different from control: *P<0.05, **P<0.001, 
***P<0.001 by Newman Keuls’ test. 
 
 
87 
 
Duration of immobility (s) Duration of immobility (s)
Distance travelled
Distance travelled (no. of quadrants entered)
(no. of quadrants entered)
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ALK
ALK FLX
FLX BUP
150 100
BUP
80
100
60
40
50
20
0 0
0 1 2 3 0 1 2 3
Log Dose Log Dose
         
Figure 4.20 Log dose-response curves showing the effect of  ALK (30 - 300 mgkg-1), FLX (3 - 30 mg 
kg-1)  and  BUP (3 - 30 mgkg-1)  on  (a)  %  decrease in  immobility  time  and  (b)  %  increase  in  
distance travelled in the open space swim test in mice. Each point is the mean ± S.E.M. of 10 animals. 
 
 
Table 4.7 ED50 and Emax values of drugs used in the open space swim test 
Parameters           ALK                  FLX                  BUP 
ED50 Emax ED50 Emax ED50 Emax 
Immobility time 11.61±2.2 89.7 1.71± 0.6 95.5 4.98± 1.7 95.1 
Distance 58.4± 5.1 83.9 26.9± 6.3 98.2 29.0± 6.5 98.4 
travelled 
 
 
 
 
 
 
 
 
88 
 
Duration of immobility (s)
Distance travelled
(no. of quadrants entered)
University of Ghana http://ugspace.ug.edu.gh
4.7 POSSIBLE MECHANISMS OF ACTION OF EXTRACTED TOTAL ALKALOIDS 
4.7.1   INVOLVEMENT OF NORADRENERGIC SYSTEMS 
4.7.1.1 α-methyldopa pre-treatment 
-1
Results from figure 4.21 indicates that pre-treatment of mice with α-methyldopa (400  mg kg , 
-1
i.p.) alone reversed the antidepressant effect of ALK (30, 100 and 300 mg kg ) and IMI (3, 10 
-1 -1
and 30 mg kg ) but not FLX (3, 10 and 30 mg kg ) in both (a) TST and (b) FST but α-
methyldopa alone did not alter immobility score (F19,120 = 80.50, P<0.0001:TST;  F19,120 = 
60.83, P <0.0001; FST). 
Untreated
a -MD-treated
50

 

40  
30
***
20 *** *** ***
*** ***
10 *** ***
*** *** ***
***
0
trl 30 100 300 3 10 30 3 10 30C
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
Untreated
b -MD-treated
50


 40  
30
*** ***
20 *** ***
***
***
10
0
trl 30 00 00 3 10 30 3 10 0C 1 3 3
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)  
-1
Figure 4.21: Effects of pre-treatment of mice with α-MD (400 mg kg , i.p) alone on immobility scores 
-1 -1 -1
of ALK (30,100 and 300 mg kg  p.o.), FLX (3, 10 and 30 mg kg  p.o.) and IMI (3, 10 and 30 mg kg  
p.o.) in (a) TST and (b) FST. Data are represented as group Means ± SEM of 7 animals. Significantly 
different from vehicle: ***P<0.0001; **P<0.001;*P<0.01(One-way ANOVA followed by Newman-
Kuel`stest).   ◊◊◊ P<0.001; ◊◊ P<0.01; ◊ P<0.05; significant difference between treatment and dose 
(Two Way ANOVA with Bonferonni post hoc test). 
89 
 
Immobility score(s) Immobility score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.1.2 Reserpine pre-treatment 
-1
Pre-treatment with reserpine (1mg kg , s.c.) alone also significantly blocked the reduction in 
-1 -1
immobility exhibited by ALK (30, 100 and 300 mg kg ) and IMI (3, 10 and 30 mg kg ) but 
-1
not FLX (3, 10 and 30 mg kg ) in both (c) TST and (d) FST but administration of reserpine 
alone did not show any difference when compared to the control (F19,120 = 59.92, P<0.0001: 
TST; F19,120 = 64.89, P <0.0001; FST). 
Untreated
c
Reserpine treated
50
    
40
30
***
20 *** ***
***
*** ***
*** ***
10 *** *** ***
***
0
trl 30 00 00 3 10 30 3 10 30C 1 3
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
Untreated
Reserpine treated
d
50
  

 
40
**
30
***
***
***
20 ***
*** ****** ***
*** ***
***
10 ***
0
rl 0 0 0 3 0 0 3 0 0
Ct 3 10 30 1 3 1 3
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
Figure 4.22: Effects of pre-treatment of mice with reserpine (1mg kg-1, s.c.) on immobility scores of 
ALK (30, 100 and 300 mg kg-1 p.o.), FLX (3, 10 and 30 mg kg-1 p.o.) and IMI (3, 10 and 30 mg kg-1 p.o.) 
in (c) TST and (d) FST. Data are represented as group Means ± SEM of 7 animals. Significantly different 
from vehicle: ***P<0.0001; **P<0.001; *P<0.01 (One-way ANOVA followed by Newman-Kuel`s test).   
◊◊◊ P<0.001; ◊◊ P<0.01; ◊ P<0.05; significant difference between treatment and dose (Two Way 
ANOVA with Bonferonni post hoc test) 
 
 
 
 
90 
 
Immobility score(s) Immobility score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.1.3 Pre-treatment withα-methyldopa/reserpine 
-1 -1
Simultaneous administration of reserpine (1 mg kg , s.c.) and α-MD (200 mg kg , i.p.) 
-1
obliterated the antidepressant activity of ALK (30, 100 and 300 mg kg ) and IMI (3, 10 and 
-1 -1
30 mg kg ) but not FLX (3, 10 and 30 mg kg ) in (f) FST but partially reversed the 
-1
antidepressant effect of FLX (30 mg kg ) in (e) TST (F19,120 = 62.29,  P<0.0001:TST; F19,120 
= 60.89, P <0.0001; FST). 
Untreated
e -MD/Reserpine treated
50

*    
40 
30
*** 
20 *** *** *** ***
***
***
*** ***
10 *** ***
***
0
Ctr
l 30 10
0
30
0 3 10 30 3 10 30
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
Untreated
-MD/Reserpine treated
f
50

   

40
30
*** ***
20 *** *** *** ***
*** ******
10 ***
***
***
0
trl 30 00 0 3 0 0 3 0 0C 1 30 1 3 1 3
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
  
-1
Figure 4.23: Effects of pre-treatment of mice with a combination of α-MD (200 mg kg , i.p) and 
-1 -1
reserpine (1 mg kg , s.c.) on immobility scores of ALK (30, 100 and 300 mg kg  p.o.), FLX (3, 10 
-1 -1
and 30 mg kg  p.o.) and IMI (3, 10 and 30 mg kg  p.o.) in (e) TST and (f) FST. Data are represented 
as group Means ± SEM of 7 animals. Significantly different from vehicle: *** P < 0.0001; ** P < 
0.001; * P < 0.01 (One-way ANOVA followed by Newman-Kuel`s test). ◊◊◊ P < 0.001; ◊◊ P < 0.01; ◊ 
P < 0.05; significant difference between treatment and dose (Two Way ANOVA with Bonferonni post 
hoc test). 
91 
 
Immobility score(s) Immobility score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.1.3.1 α-methyldopa/reserpine pre-treatment on swimming and climbing score in FST  
-1
ALK, FLX and IMI increased swimming score but simultaneous reserpine (1 mg kg , s.c.) 
-1
and α MD (200 mg kg , i.p.) pre-treatment caused a significant reversal in the swimming 
scores of ALK, and IMI, but not FLX (F19,120 = 59.95; P<0.0001) (Figure 4.21g). 
Administration of ALK, FLX and IMI caused an increase in climbing score but was revered in 
ALK (300 mg kg-1) and IMI (3 and 30 mg kg-1) with simultaneous reserpine (1 mg kg-1, s.c.) 
and α-MD (200 mg kg-1, i.p.) pre-treatment (F19,120 = 7.546; P<0.0001) (Figure 4.21h). 
Untreated Untreated
g h
-MD/Reserpine treated -MD/Reserpine treated
50 25
*** 
***
*** 
40 *** 20 ******
 *** *** 
 
 ***

 ***
30 *** ***  15*** *** * * *
*** *
**
20 10
10 5
0 0
tr
l
30 00 00 3 0 0 3 0 0 t
rl 301 3 1 3 10
0 00 3 10 30 33 1
0 30
C 1 3 C
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg) ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
Figure 4.24: Effects of pre-treatment of mice with a combination of α-MD (200 mg kg-1,i.p) 
and reserpine (1mg kg-1,s.c.) on swimming (g) and climbing scores (h) of ALK (30, 100 and 
300 mg kg-1 p.o.), FLX (3, 10 and 30 mg kg-1 p.o.) and IMI (3, 10 and 30 mg kg-1 p.o.) in 
FST. Data are represented as group Means ± SEM of 7 animals. Significantly different from 
vehicle: *** P<0.0001; ** P<0.001; * P<0.01 (One-way ANOVA followed by Newman- 
Kuel`s test). ◊◊◊ P<0.001; ◊◊ P<0.01;  ◊ P<0.05; significant difference between treatment and 
dose (Two Way ANOVA with Bonferonni post hoc test). 
 
 
 
 
92 
 
Swimming score(s)
Climbing score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.1.4 Involvement of α1 receptor 
In attempt to investigate the involvement of α1   and α2   receptor stimulation in the 
-1
antidepressant effects of ALK (Figure 4.25), mice pre-treated with prazosin (3 mg kg p.o.), a 
specific α1receptor antagonist did not alter the reduction in immobility of ALK (30, 100 and 300 
-1 -1 -1
mg kg ) and IMI (10 mg kg ) but blocked the antidepressant potentials of ATO (1 mg kg ) in 
both (a) TST and (b) FST (F11,72 = 42.13, P<0.0001: TST;  F11,72 = 46.01, P<0.0001; FST) 
Untreated
Untreated b Prazosin treated
a Prazosin treated 50
50
40
40 *

30 
30
***
*** *** ******
*** *** ***
*** 20 ***20 ****** ****** *** ***
***
*** ***
10 *** 10
0 0
rl lt 30 00 00 1 10 tr 30 00 00 1 10
C 1 3 C 1 3
   ALK (mg/kg) ATO (mg/kg) IMI (mg/kg)    ALK (mg/kg) ATO(mg/kg) IMI (mg/kg)
 
−1
Figure 4.25: Effect of pre-treatment of mice with prazosin (3 mg kg , p.o., a selective α1-receptor 
−1 −1 −1
antagonist) on ALK (30, 100 and 300 mg kg ,p.o.), ATO (1 mg kg , p.o.) and IMI (10 mg kg , p.o.) 
induced reduction in immobility time in the (a) TST and (b) FST. Each column represents the mean ± 
SEM (n=7) Significantly different from vehicle: *** P<0.0001; ** P<0.001; * P<0.01 (One-way 
ANOVA followed by Newman-Kuel`s test). ◊◊◊ P<0.001; ◊◊ P<0.01; ◊ P<0.05; significant difference 
between treatment and dose (Two Way ANOVA with Bonferonni post hoc test). 
 
93 
 
Immobility score(s)
Immobility score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.1.5 Involvement of α2 receptor 
-1
Pre-treatment of mice with yohimbine (3 mg kg  p.o.) a specific α2 receptor antagonist 
-1
significantly potentiated the antidepressant effect of ALK (30, 100 and 300 mg kg ) and ATO 
-1
(1 mg kg ) in (c) TST and (d) FST (F11,72 = 28.22, P<0.0001: TST;  F11,72 = 40.71, P<0.0001; 
FST) (figure 4.26). 
Untreated
Untreated
c Yohimbine treated
Yohimbine treated
40 d
 50

30 40
***
 
*** 
30

20  
*** ***
*** *** 
***
*** 20 *** *** *** ******
*** *** *** *** *** *** ***
10 *** *** ***
10 ***
0 0
rlt 30 0 0 1 0 r
l 0 0 0 1 0
C 1
0 30 1 t 3 10 30 1
ATO (mg/kg) C
   ALK (mg/kg) IMI (mg/kg) ATO (mg/kg)   ALK (mg/kg) IMI (mg/kg)
 
−1
Figure 4.26: Effect of pre-treatment of mice with yohimbine (3 mg kg , p.o., α2-receptor antagonist) 
−1 −1 −1
on ALK (30, 100 and 300 mg kg , p.o.), ATO (1 mg kg , p.o.) and IMI (10 mg kg , p.o.) induced 
reduction in immobility time in the (c) TST and (d) FST. Each column represents the mean ± SEM 
(n=7) Significantly different from vehicle: *** P<0.0001; ** P<0.001; * P<0.01(One-way ANOVA 
followed by Newman-Kuel`s test). ◊◊◊ P<0.001; ◊◊ P<0.01; ◊ P<0.05; significant difference between 
treatment and dose (Two Way ANOVA with Bonferonni post hoc test)
94 
 
Immobility score(s)
Immobility score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.2 INVOLVEMENT OF SEROTONINERGIC SYSTEMS 
4.7.2.1 pCPA pre-treatment 
-1
Pre-treatment of mice with pCPA (200 mg kg ) abolished the antidepressant effect of ALK 
-1 -1 -
(30, 100 and 300 mg kg , p.o.), FLX (3, 10 and 30 mg kg , p.o.) and IMI (3, 10 and 30 mg kg
1
, p.o.) in the (a) TST and (b) FST. The mean counts for immobility (F19,120  = 118.7; 
P<0.0001) (Figure 4.27a; TST) and (F19,120 = 81.45; P<0.0001) (Figure 4.27b; FST) in the 
ALK and FLX treated groups after pCPA treatment did not show any  difference when 
compared with the control. 
Untreated
a
pCPA treated
50

     
40

** 
*** ***
30
***
20 *** ***
***
***
***
10 *** ***
***
0
Ctr
l 30 100 300 3 10 30 3 10 30
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
Untreated
b pCPA treated
50
 
 40   
 
*
30
***
20 *** *** ***
***
***
10 *** ***
***
0
l
Ctr 30 100 300 3 10 300 3 10 300
   ALK (mg/kg)    FLX(mg/kg)    IMI (mg/kg)  
−1
Figure 4.27: Effect of pre-treatment of mice with pCPA (200 mg kg , i.p) on ALK (30, 100 and 300 
−1 −1 −1
mg kg , p.o.), FLX (3, 10, and 30 mg kg , p.o.) and IMI (3, 10 and 30 mg kg , p.o.) immobility score 
in the (a) TST and (b) FST. Each column represents the mean ± SEM (n=7) Significantly different 
from vehicle: *** P<0.0001; ** P<0.001; * P<0.01(One-way ANOVA followed by Newman-Kuel`s 
test). ◊◊◊ P<0.001; ◊◊ P<0.01; ◊ P<0.05; significant difference between treatment and dose (Two Way 
ANOVA with Bonferonni post hoc test). 
95 
 
Immobility score(s) Immobility score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.2.1.1 pCPA pre-treatment on swimming and climbing scores in FST 
ALK, FLX and IMI increased swimming score which was reversed by pCPA treatment (F19,120= 
-1
54.23; P<0.0001) (Figure 4.28c). Administration of ALK (30, 100 and 300 mg kg ), FLX (3, 10 
-1 -1
and 30 mg kg ) and IMI (3, 10, 30 mg kg ) caused an increase in climbing score but was 
-1 -1
revered in ALK (300 mg kg ) and IMI (30 mg kg ) with pCPA treatment (F19,120= 8.607; 
P<0.0001) (Figure4.28d). 
Untreated
c
pCPA treated Untreatedd
50 pCPA treated

 25
*** 
40 ***  ***
 20 ***
 ***  *** **

 ***
30 ***
*** 
*** *** 15 * *
*** *
*** *
20 10
10 5
0 0
rl 0 0 0 3 0 0 3 0 0 tr
l
30t 3 0 0
0 00 3 10 30 3 10 30
C 1 30 1 3 1 3 C 1 3
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg) ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
Figure 4.28: Effect of pre-treatment of mice with pCPA (200 mgkg−1, i.p) on ALK (30, 100 and 300 
mg kg−1, p.o.), FLX (3, 10 and 30 mg kg−1, p.o.) and IMI (3, 10 and 30 mg kg−1, p.o.) swimming score 
(c) and climbing score (d) in FST. Each column represents the mean ±SEM (n=7) Significantly 
different from vehicle: *** P<0.0001; ** P<0.001; * P<0.01(One-way ANOVA followed by 
Newman-Kuel`s test). ◊◊◊ P<0.001; ◊◊ P<0.01; ◊ P<0.05; significant difference between treatment 
and dose (Two Way ANOVA with Bonferonni post hoc test). 
 
 
 
 
 
 
 
 
96 
 
Swimming score(s)
Climbing score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.2.2. Involvement of 5-HT2 receptor 
In an attempt to investigate the involvement of 5HT2 receptor activation in the antidepressant 
-1
effects of ALK (Figure 4.29), mice were pre-treated with cyproheptadine (8 mg kg  p.o.), a 
specific 5-HT2 receptor antagonist. It was observed that pre-treatment with cyproheptadine 
-1
significantly reversed the antidepressant of ALK (30, 100 and 300 mg kg ), FLX (10 mg kg-1) 
-1
and IMI (10 mg kg ) both (a) TST and (b) FST (F11,72 = 92.24, P<0.0001: TST;  F11,72 = 46.18, 
P <0.0001; FST). 
 
a Untreated
b Untreated
Cyproheptadine treated Cyproheptadine treated
50 50
 
 
 
40   40 
*** ***** *
30 30 ***
***
*** ***
20 ** *** 20 ******
*
***
10 *** 10
***
0 0
rl 0 0 0 rl 0 0 0 0 0t
C 3 10 30 1
0 10 tC 3 10 30 1 1
   ALK (mg/kg) FLX(mg/kg) IMI (mg/kg)    ALK (mg/kg) FLX(mg/kg) IMI (mg/kg)
 
−1
Figure 4.29: Effect of pre-treatment of mice with cyproheptadine (8 mg kg , p.o., a selective 5-HT2 
receptor antagonist on ALK (30, 100 and 300 mg kg−1, p.o.), FLX (10 mg kg−1, p.o.) and IMI (10 mg  
kg−1, p.o.) immobility score in the (a) TST and (b) FST. Each column represents the mean ± SEM 
(n=7) Significantly different from vehicle: *** P<0.0001; ** P<0.001; * P<0.01 (One-way ANOVA 
followed by Newman-Kuel`s test).   ◊◊◊ P<0.001; ◊◊ P<0.01; ◊ P<0.05; significant difference between 
treatment and dose (Two Way ANOVA with Bonferonni post hoc test). 
 
97 
 
Immobility score(s)
Immobility score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.3   INVOLVEMENT OF GLYCINE /NMDA RECEPTOR COMPLEX 
4.73.1 D-serine pre-treatment 
−1
Figure 4.30 shows the effect of combined administration of D-serine (600 mg kg , i.p., a full 
agonist on glyicine/NMDA receptor) on ALK, FLX and IMI on TST and FST. The antidepressant 
−1 −1
effect of ALK (30, 100 and 300 mg kg , p.o.), FLX (3, 10 and 30 mg kg , p.o.) and IMI (3, 10 
−1 −1
and 30 mg kg , p.o.) was significantly reversed by the pre-treatment of D-serine (600 mg kg , 
i.p) in both (a) TST (F19,120 = 67.26, P<0.0001) and (b) FST (F19,120 = 29.37,  P<0.0001). 
Untreated
b D-serine treated
50
 
40  
**  
*** ** 

30 *** ***
***
***
***
*** ***
20 *** ***
*** *** ***
10 *** ***
0
trlC 30 100 300 3 10 30 3 10 30
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
Untreated
a D-serine treated
50


 
   

40
30
***
20 *** ***
***
*** ***
10 *** ***
***
0
trl 30 100 300 3 10 30 3 0 0C 1 3
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
−1
Figure 4.30: Effect of pre-treatment of mice with D-serine (600 mg kg , i.p., a full agonist on 
−1 −1
glyicine/NMDA receptor) on ALK (30, 100 and 300 mg kg , p.o.), FLX (3, 10, and 30 mg kg , p.o.) 
−1
and IMI (3, 10 and 30 mg kg , p.o.) immobility score in the (a) TST and (b) FST. Each column 
represents the mean ± SEM (n=7) Significantly different from vehicle: *** P<0.0001; ** P<0.001; * 
P<0.01(One-way ANOVA followed by Newman-Kuel`s test). ◊◊◊ P<0.001; ◊◊ P<0.01; ◊ P<0.05; 
significant difference between treatment and dose (Two Way ANOVA with Bonferonni post hoc test). 
98 
 
Immobility score(s) Immobility score(s)
University of Ghana http://ugspace.ug.edu.gh
4.7.3.1.1. D-serine pre-treatment on swimming and climbing scores in FST 
ALK, FLX and IMI all caused increase in swimming score and this was observed to be 
reduced by D-serine in ALK and IMI but unaffected in IMI. Climbing scores were increased 
−1 −1
by ALK (30, 100 and 300 mg kg , p.o.), FLX (10 mg kg , p.o.) and IMI (3, 10 and 30 mg 
−1 −1
kg , p.o.). Pre-treatment of D-serine further increased climbing score in ALK (300 mg kg , 
−1
p.o.) and FLX (3, 10 and 30 mg kg , p.o.)  but rather caused a reduction in that of IMI (3, 10 
−1
and 30 mg kg , p.o.). 
e Untreated
D-serine treated g Untreated
50 D-serine treated

 40
***

40  ***

 
*** 30 *** 

***
30 *** *** *** *** 
*** ****** 
*** ***  ***
*** 20 ** **
20
10
10
0 0
rl 0 0 0 3 0 0 3 0 0
l
tr 30 00 0 3 0 0 3 0 0t
C 3 10 30 1 3 1 3 C 1 3
0 1 3 1 3
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg) ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
−1
Figure 4.31: Effect of pre-treatment of mice with D-serine on ALK (30, 100 and 300 mg kg , p.o.), 
−1 −1
FLX (3, 10, and 30 mg kg , p.o.) and IMI (3, 10 and 30 mg kg , p.o.) swimming (e) and climbing (g) 
scores. Each column represents the mean ± SEM (n=7) Significantly different from vehicle: *** P 
<0.0001; ** P < 0.001; * P < 0.01 (One-way ANOVA followed by Newman-Kuel`s test).  ◊◊◊ P 
<0.001; ◊◊ P < 0.01; ◊ P < 0.05; significant difference between treatment and dose (Two Way 
ANOVA with Bonferonni post hoc test) 
 
 
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4.7.3.2 D-cycloserine pre-treatment 
Figure 4.32 shows the effect of D-cycloserine on ALK, FLX and IMI in TST and FST. Pre-
−1
treatment of D-cycloserine (2.5 mg kg , i.p) caused a further decline in immobility score in 
−1
ALK (30, 100 and 300 mg kg , p.o.), thus potentiating its observed antidepressant effect but 
−1 −1
not in FLX (3, 10 and 30 mg kg , p.o.) and IMI (3, 10 and 30 mg kg , p.o) in both (c) 
TST (F19,120 = 38.86,  P< 0.0001) and (d) FST (F19,120 = 35.46,  P< 0.0001). 
Untreated
d
D-cycloserine treated
50
40
30

***
 ***
*** ***
20 *** *** *** ***
*** ******
***
10 *** *** ****** ***
***
0
trlC 3
0
10
0 00 33 1
0 30 3 10 30
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
c Untreated
D-cycloserine treated
40
30

 
****
20 *** *** ***
***
*** ***
*** *** *** *****
10 ***
***** **** *
******
0
trl 30 00 00 3 10 30 3 10 30C 1 3
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
Fig
−1
ure 4.32: Effect of pre-treatment of mice with D-cycloserine (2.5 mg kg , i.p., a partial agonist on 
−1 −1
glyicine/NMDA receptor on ALK (30, 100 and 300 mg kg , p.o.), FLX (3, 10, and 30 mg kg , p.o.) 
−1
and IMI (3, 10 and 30 mg kg , p.o.)  immobility score in the (c) TST  and (d) FST. Each column 
represents the mean ± SEM (n=7) Significantly different from vehicle: *** P < 0.0001; ** P < 
0.001;* P < 0.01 (One-way ANOVA followed by Newman-Kuel`s test).  ◊◊◊ P < 0.001; ◊◊ P < 0.01; 
◊ P <0.05; significant difference between treatment and dose (Two Way ANOVA with Bonferonni 
post hoc test) 
 
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4.7.3.2.1 D-cycloserine pre-treatment on swimming and climbing scores in FST  
Swimming behaviour was rather further enhanced by D-cycloserine pre-treatment in ALK 
−1
(30, 100 and 300 mg kg , p.o.). However, climbing score was unaffected in ALK (30, 100 and 
−1 −1
300 mg kg , p.o.) and FLX (3, 10 and 30 mg kg , p.o.) but was further increased in IMI (3, 
−1
10 and 30 mg kg , p.o.) with D-cycloserine pre-treatment. 
 
Untreated Untreated
f D-cycloserine treated h D-cycloserine treated
60 40  

 ****** ***
 
 *** ***
*** ***
30
***
40 *** ******


*** 
*** 20 ** ****** *** *** **
*** *
**
20
10
0 0
tr
l 0 0 0 3 0 0 3 0 0 ltr 30 00 00 3 0 0 3 0 0
C 3 10 30 1 3 1 3 C 1 3
1 3 1 3
ALK (mg/kg) FLX (mg/kg) IMI (mg/kg) ALK (mg/kg) FLX (mg/kg) IMI (mg/kg)
 
−1
Figure 4.33: Effect of pre-treatment of mice with D-cycloserine on ALK (30, 100 and 300 mg kg , 
−1 −1
p.o.), FLX (3, 10, and 30 mg kg , p.o.) and IMI (3, 10 and 30 mg kg , p.o.) swimming (f) and 
climbing (h) score in FST. Each column represents the mean ± SEM (n=7) Significantly different 
from vehicle: *** P < 0.0001; ** P < 0.001; * P < 0.01 (One-way ANOVA followed by Newman- 
Kuel`s test).  ◊◊◊ P < 0.001; ◊◊ P < 0.01; ◊ P < 0.05; significant difference between treatment and 
dose (Two Way ANOVA with Bonferonni post hoc test) 
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4.7.4 INVOLVEMENT OF L-ARGININE-NO-cGMP PATHWAY  
Figure 4.34 - 4.37 depicts the involvement of nitric oxide pathway in the antidepressant 
−1
potential of ALK (30, 100 and 300 mg kg , p.o.) in both TST and FST. 
4.7.4.1. Pre-treatment with L-arginine 
−1
Administration of L-arginine (750 mg kg , i.p., a precursor of nitric oxide) had no anti- 
immobility effects on mice in the (a) TST and (b) FST compared with saline (vehicle) treated 
group. Pre-treatment with L-arginine did not significantly abolished the antidepressant effect 
-1
of ALK (30, 100 and 300 mg kg ) (F7,48 =17.04,  P< 0.0001) and FST (b) (F7,48 = 42.48,  
P<0.0001). 
a Saline treated b Saline treated
L-arginine treated L-arginine treated
40 50
 40
30 

*** ***
30 ****** *** *** ***
20 *** *** ***
***
20 ***
10
10
0 0
tr
l 0 l3 10
0 0 tr 0 0 0
C 3
0
C 3 10 30
ALK (mg/kg) ALK (mg/kg)
 
−1
Figure 4.34: Effects of pre-treatment of mice with L-arginine (750 mg kg , i.p., a precursor 
−1
of nitric oxide) on ALK (30, 100 and 300 mg kg , p.o.) induced reduction in immobility time 
in the (a) TST and (b) FST. Each column represents the mean ± SEM (n=7). Significantly 
different from vehicle: *** P < 0.0001; ** P < 0.001; * P < 0.01 (One-way ANOVA 
followed by Newman-Kuel`s test).  ◊◊◊ P < 0.001; ◊◊ P < 0.01; ◊ P < 0.05; significant 
difference between treatment and dose (Two Way ANOVA with Bonferonni post hoc test).
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4.7.4.2 Pre-treatment with L-NAME 
−1
L-NAME (30 mg kg , i.p., a non-selective NOS inhibitor) when administered alone did not 
affect  immobility score  in  comparison  with  the    saline  treated  group  only in  (c)  TST, 
however, L-NAME exhibited a significant antidepressant effect in the (d) FST. Pre-treatment of 
-
L-NAME caused an enhancement in the antidepressant effect of ALK (30, 100 and 300 mg kg
1
) by causing a further reduction in immobility scores in both (c) TST (F7,48  = 42.89.04, P< 
0.0001) and (d) FST (F7,48 = 59.88,  P< 0.0001). 
Saline treated
d
Saline treated L-NAME treated
c
L-NAME treated 50 
40
40
30

 30 
  *** 
*** ***
20 *** ***
*** 20 ***
***
*** ***
10 ***10 *** ***
0
0 l
tr 0 0 0
rl 0 0 0 C
3 10 30
t
C 3 10 30
ALK (mg/kg) ALK (mg/kg)
 
−1
Figure 4.35: Effects of pre-treatment of mice with L-NAME (30 mg kg , i.p., a non-selective nitric 
−1
oxide synthase inhibitor) on ALK (30, 100 and 300 mg kg , p.o.) induced reduction in immobility 
time in the (c) TST and (d) FST. Each column represents the mean ± SEM (n=7). Significantly 
different from vehicle: *** P < 0.0001; ** P < 0.001; * P < 0.01 (One-way ANOVA followed by 
Newman-Kuel`s test).   ◊◊◊ P < 0.001; ◊◊ P < 0.01; ◊ P < 0.05; significant difference between 
treatment and dose (Two Way ANOVA with Bonferonni post hoc test).
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4.7.4.3 Pre-treatment with methylene blue 
−1
Pre-treatment of methylene blue (10 mg kg , i.p., an inhibitor of NO synthase and an 
inhibitor of sGC) caused an enhancement in the antidepressant effect of ALK (30, 100 and 
-1
300 mg kg ) by causing a further reduction in immobility scores in both (e) TST  (F7,48  
= 45.09,  P< 0.0001) and (f) FST (F7,48 = 298.1,  P< 0.0001). 
Saline treated Saline treatede f
Methylene blue treated Methylene blue treated
40 50
40
30
 
 30 
*** 
20 *** *** ***
*** 20 *** ***
***
10 *** ***
10 *** ***
0 0
rlt 0 0 0 rl
C 3
0 0 0
10 30 tC 3 10 30
ALK (mg/kg) ALK (mg/kg)
 
−1
Figure 4.36: Effects of pre-treatment of mice with methylene blue (10 mg kg , i.p., an inhibitor of 
NO synthase and an inhibitor of sGC) on ALK (30, 100 and 300 mg kg−1, p.o.) induced reduction in 
immobility time in the (e) TST  and  (f) FST.  Each column represents the mean ± SEM (n=7). 
Significantly different from vehicle: *** P < 0.0001; ** P < 0.001; * P < 0.01 (One-way ANOVA 
followed by Newman-Kuel`s test).  ◊◊◊ P < 0.001; ◊◊ P < 0.01; ◊ P < 0.05; significant difference 
between treatment and dose (Two Way ANOVA with Bonferonni post hoc test)
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4.7.4.3. Pre-treatment with Sildenafil 
−1
Pre-treatment of sildenafil (5mg kg , i.p., a phosphodiesterase-5 inhibitor) did not have any 
-1
significant effect on the antidepressant activity of ALK (30, 100 and 300 mg kg ) in both (g) 
TST and (h) FST 
 
g Saline treated h Saline treated
Sildenafil treated Sildenafil treated50
40
40
30
*** 30
*** *** ***
20 *** *** *** *** ****** ***
20 ***
10 10
0 0
l l
tr 0 0 0 t
r
3 0 3
0 00 00
C 1 30 C 1 3
ALK (mg/kg) ALK (mg/kg)
 
−1
Figure  4.37:  Effects  of  pre-treatment  of  mice  sildenafil  (5mg  kg ,  i.p.,  a  phosphodiesterase-5 
−1
inhibitor) on ALK (30, 100 and 300 mg kg , p.o.) induced reduction in immobility time in the (g) 
TST and (h) FST. Each column represents the mean ± SEM (n=7). Significantly different from 
vehicle: *** P < 0.0001; ** P < 0.001; * P < 0.01 (One-way ANOVA followed by Newman-Kuel`s 
test).  ◊◊◊ P < 0.001; ◊◊ P < 0.01; ◊ P < 0.05; significant difference between treatment and dose (Two 
Way ANOVA with Bonferonni post hoc test) 
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CHAPTER FIVE 
5.1 DISCUSSION 
Depression is a multifarious disorder in which several underlying presentations may share a 
collective phenomenology but have diverse etiologies. Clinical studies indicate that a 
considerable  percentage  of  patients  who  seek  medication  for  major  depression  have  a 
chronic-recurrent  course  of  the  disorder  (Hardeveld  et  al.,  2010).  Moreover,  depressed 
patients   often   have several associated physical disorders, suicidal   tendencies   and   the 
prolonged  improvement  of symptomatology  as  seen with  most current    antidepressants 
may  cause an upsurge in mortality if drugs with rapid onset, continued effect and multiple 
therapeutic targets that better addresses the heterogeneous nature of the disorder are not 
sought (Lucas, 2008). Additionally, discovery of active bioactive compounds in herbal 
medicinal preparations may turn out to be useful in clarifying the pharmacological activity and 
possible mechanisms of action for potential drug discovery (Tseng et al., 2007). It was based 
on this assertion that the antidepressant effect of secondary metabolites isolated from the 
stem  bark  extract  of  Trichilia  monadelpha  was  ascertained  in  this  study and  to  further 
evaluate the possible mechanisms of action of the most potent and efficacious phytochemical. 
Preliminary phytochemical screening of the stem bark extracts of Trichilia monadelpha in 
this present study revealed the presence of alkaloids, flavonoids, glycosides, saponins, sterols, 
tannins, and terpenoids in hydroethanolic extract. HEE, a more polar solvent was used and 
this was expected to extract polar constituents from the stem bark of the plant. Ethyl acetate 
extract, a slightly polar solvent had alkaloids, glycosides, tannins, sterols and terpenoids 
while the petroleum ether extract showed the presence of alkaloids, sterols, and terpenoids 
possibly due to its non-polar properties as a solvent therefore isolated the non-polar 
components from the plant`s stem bark. This observation was harmonious with similar studies 
done by Ben et al., (2013). 
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Several scientific reports have indicated that the respective pharmacological and therapeutic 
potentials of medicinal plants are due to the presence of active biological compounds most of 
which are secondary metabolites (Maganha et al., 2010; Rogerio et al., 2010). Thus the 
presence of such a wide collection of phytochemicals in the stem bark may imply widespread 
phyto-pharmacological effects as reported by its multipurpose uses in African traditional 
medicine. Saponins are the naturally occurring strong foam-forming glycosides (Quante et 
al., 2010). Scientific evidence revealed that saponins possess neuroprotective effect via the 
inhibition   of   apoptosis   and   intraneuronal   calcium   dynamics,   antidepressant   effects, 
anticancer,  anti-inflammatory,  antifungal,  moluscidal,  spermicidal etc. (Xiang et al., 2011). 
Alkaloids are reported to be considered as one of the most effective and therapeutically 
essential plant substance (Makkar et al., 2007). They possess diverse clinical properties 
including antidepressant effects, agents for CNS and analgesia, inhibition of muscle spasms, 
anti-inflammatory and antineoplastic effects (Nesterova et al., 2011; Yang et al., 2006). 
Terpenoids isolated from Valerian officinalis are known to possess effective anxiolytic and 
antidepressant effects, anticancer properties among others (Kennedy and Wightman, 2011). 
Phenolic compounds have been reported to possess multiple biological effects including 
antidepressant activity (St. John’s wort), neuroprotective, anticancer, anti-inflammatory as 
well as enhancing endothelial functioning (Shi and Wang, 2006; Chao et al., 2009). Sterols 
are cholesterol-like compounds and are known for their antimicrobial, anti-diabetic, 
anticancer, ability to reduce cholesterol level and boost immune function, (Breytenbach et al., 
2001; Katan et al., 2003). Although the individuals potent bioactive compounds are yet be 
isolated, characterized and tested for their respective pharmacological properties, the 
occurrence of these phytochemicals may validate the traditional use of T. monadelpha in 
managing most psychiatric conditions including depression. 
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In the Irwin test, all three extracts (HEE, EAE and PEE) exhibited sedative effects at higher 
doses without impairing motor coordination and respiration function in mice. This is indicative 
of possible CNS depressant effect. In addition, no mortality was also recorded after 24 hours 
for all the administered doses in all the three extracts suggesting that the minimum lethal dose 
for our test extracts in mice may be above 3000 mg kg-1. The Irwin test is used as a safety 
approach for detecting untoward effects of a new compound on general behaviour, 
physiological function and for evaluating its acute neurotoxicity (Roux et al., 2005; Lynch et 
al., 2011). All three extracts showed analgesic effects confirming the traditional usage of the 
plant in managing the pain (Woode et al., 2012). 
In this study, oral administration of HEE, EAE and PEE demonstrated potent antidepressant 
activity in both the forced swimming and tail suspension tests which are two most widely 
used pharmacological models for assessing antidepressant activity. In both models, all the 
extracts produced a dose-related decline in immobility scores by increasing specific active 
behavioural components like swimming and climbing in the FST, and curling and swinging 
in the TST respectively. 
Mice develop immobility when they are in a stressful condition without the opportunity for 
escape. The immobile behaviour is known to reflect either a failure to endure in an escape- 
directed  behaviour  after  persistence  stress  or  the  occurrence  of  passive  behaviour  that 
extricate the animal from active forms of coping with stressful stimuli (Cryan and Lucki, 
2000). Decline in immobility is used as the principal index for the antidepressant effect of test 
substances in these models (Cryan et al., 2005). Several antidepressants in clinical use 
selectively induces reduction of behavioural immobility in TST and FST (Borsini and Meli, 
1988; Petit-Demouliere et al., 2005). Thus HEE, EAE and PEE were able to cause a reduction 
in immobility behaviour which is suggestive of an antidepressant effect. 
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Recent modifications of the traditional FST and TST demonstrated that specific behavioural 
components of active behaviours differentiate neurochemically unique antidepressants (Cryan 
et  al.,  2002;  Lucki,  1997).    In  the  modified  FST,  drugs  that  cause  an  upsurge in    the 
swimming score without significantly altering the climbing behaviour are purported to be 
sensitive to the serotoninergic pathway, while drugs with selective effects on catecholamine 
neurotransmission   increase the climbing score without affecting swimming score (Page et 
al., 1999; Rénéric et al., 2001) In this study, HEE, EAE and PEE exhibited significant 
increase in swimming and climbing scores thus suggesting that all three extracts might be 
acting possibly via serotoninergic and catecholaminergic pathway. The unique active 
behaviours observed by antidepressants have been reported to be superimposable on 
combinations of serotoninergic and noradrenergic compounds (Slattery and Cryan, 2012). In 
the TST, all three extracts demonstrated significant increase in swinging and curling 
behaviours. Antidepressants that inhibit noradrenaline and/or serotonin re-uptake cause a 
diminution in immobility of mice by increasing their swinging behaviour but with no effect 
on  their  curling  behaviour.  However,  curling  behaviour  is  reported  to  be  indicative  of 
possible  enhancement  of  opioidergic  activity  (Berrocoso  et  al.,  2013).  Therefore, the 
observed antidepressant activity of HEE, EAE and PEE may partly be dependent on its effect 
on opioidergic systems. Antidepressants which act via increase in the inhibition of reuptake 
of monoamines have been reported to mediate the enhancement of the opioid pathway 
(Berrocoso et al., 2009; Jutkiewicz and Roques, 2012). The role of opioids as recognized 
antidepressants is butressed by the clinical effectiveness of  μ‑opioid receptor agonists such 
as  tramadol,  oxycodone,  oxymorphone,  etc.,  in  the  treatment  of  refractory  depression 
(Shapira et al., 2001; Hegadoren et al., 2009; Berrocoso et al., 2013). Berrocoso et al. (2009) 
further   demonstarted   that   blocking   opioid   receptors   with   naloxone   inhibited   the
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antidepressant-like effect of codeine and μ-opioid receptor gene knockout mice exhibited 
decreased normal curling behaviour in TST. 
The results presented shows that HEE was the most potent and efficacious followed by EAE 
with the PEE having the least potency and efficacy in reducing immobility score in both TST 
and FST. This observation could be due, partly to the active bioactive metabolites present in 
each of the extracts (Briskin, 2000) and could   possibly be attributed to the different 
mechanisms by which each extract could be acting to elicit its pharmacological effect. 
Determination of active major biochemical constituents are generally recommended for 
standardization and quality control of plant crude products and related investigations as this 
may prove essential in elucidation pharmacological activity for potential drug development 
(Chao et al., 2009; Tseng et al., 2007). Based on the results in this study, alkaloids, saponins, 
flavonoids, terpenoids and tannins were extracted from the HEE (the most potent and 
efficacious crude extract) and their antidepressant activity was investigated. Interestingly, 
role of plant secondary metabolites in the discovery of antidepressants have attracted 
tremendous attention in recent years (Gong et al., 2014). 
Qualitative test of the extracted saponins from the HEE revealed the presence of steroids, 
terpenoids and glycosides indicating that the saponins present are steroidal glycosides and 
triterpenoidal glycosides. Saponins occur as glycosides whose aglycone is either triterpenoid 
or steroidal structures.  Their ability to produce detergent or  soap-like  characteristic  in 
aqueous solution is due to the combination of lipophilic sugars at their ends (Kabera et al., 
2014). Saponins are naturally occurring plant glycosides with significant medicinal benefits 
such anti-inflammatory, antispasmodic, aphrodisiac, antidepressant effects. 
Flavonoids are a group of more than 4000 phenolic compounds consisting of a central three- 
ring structure that occur in plant.  In nature, flavonoids can occur  either  in  the  free  or
 
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conjugated forms, and often in plants they are mainly present as glycosides with a sugar 
moiety or more sugar moieties linked through a hydroxide group or through carbon-carbon 
bonds (Sisa et al,, 2010) and hence the detection of glycosides in its qualitative screening. 
They  are  usually classified  according  to  their  aglycone  chemical  structure,  into  flavols, 
flavones, flavonones, anthocyanidins, isoflavones, catechins and chalcones (Hernández et al., 
2009) Alkaloids present the largest single group of secondary metabolites that contain basic 
nitrogen  atoms.  They are synthesized  by secondary metabolism  of  primary metabolites, 
usually amino acids (e g: phenylalanine, tyrosine, tryptophan etc) and are normally classified 
according to their heterocyclic ring system they possess (Woolley, 2001).   Alkaloids have 
proven to possess useful medicinal properties that improve the health of mankind. Morphine 
and cocaine are some useful isolated alkaloidal compounds which act on the nervous system 
(Charbogne et al., 2014). 
Terpenoids constitute a large family of phytoconstituents of little functional and structural 
common ground. They are polymeric isoprene derivatives and synthesized from acetate via 
the mevalonic acid pathway. Compounds of terpenoids are lipophilic, volatilize easily, have 
strong odours and flavours. Traditionally, plant-based terpenoids have been used by humans 
in the food, pharmaceutical, and chemical industries (Breitmaier, 2008; Kabera et al., 2014). 
Tannins are natural, water-soluble, polyphenolic compounds with molecular weight ranging 
from 500 to 4,000, usually classified into 2 classes: hydrolysable tannins and condensed 
tannins. Hydrolysable tannins are mostly found combined with polysaccharide, proteins and 
in some cases alkaloids whereas the condensed tannins are not conjugated to any sugar 
moiety (Huang et al., 2007). 
The results from the present study indicate that ALK, SAP, FLV, TER and TAN have 
antidepressant effects in FST, a widely used animal model with a high predictive validity for
 
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investigating the antidepressant effect of test compounds. All five metabolites significantly 
decreased immobility scores and as well showed increase in swimming score demonstrating 
possible activation of serotoninergic system in their respective mechanism of action (Cryan et 
al., 2002). However, only SAP, TER and ALK showed a significant increase in climbing 
behaviour revealing them as potential catecholaminergic agents (Cryan et al., 2002; Rénéric 
et al., 2001). Therefore,we hypothezised that SAP, TER and ALK might be eliciting their 
observed antidepressant effect via both serotoninergic and catecholaminergic pathways. 
Dissimilarly, results obtained from the TST in the study indicate that only three three 
metabolites ALK, FLV and SAP significantly reduced immobility score. The non-uniform 
nature of the results implies that both of these models might follow different 
pathophysiological mechanisms in inducing immobility. Chatterjee et al., (2012) reported 
that although these models are similar in face behavioural symptoms, pharmacological 
evaluation indicates that dopamine functioning is a necessity for performance of mice in the 
FST, whereas both serotonergic and dopaminergic systems are involved in TST model. FLV 
and ALK showed a significant increase in swinging scores whereas SAP and ALK induced 
diminution in immobility by causing increase in curling behaviour in TST.   It is therefore 
likely that their observed antidepressant effect is partly due to  its effect on opioidergic 
systems since curling behaviour is reported to be indicative of opioidergic activity (Berrocoso 
et al., 2013; Kukuia et al., 2015). Comparing the efficacy of HEE to that of the idividual 
active  phytoconstituents  evaluated,  it  can  be  deduced  that  the  antidepressant  efficacy 
observed in the HEE can be attributed to the synergistic effect produced by the individual 
active phytoconstituents and possibly via varying mechanisms of action (Briskin, 2000).   
The results presented shows that the ALK was the most potent and efficacious secondary in 
reducing immobility score in both TST  and  FST.  Thus in our search  for  pure,  most 
efficacious and potent bioactive compound responsible for the antidepressant effect observed
 
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in Trichilia monadelpha, alkaloids   isolated from the HEE was considered to be an ideal 
phytoconstituent to warrant further investigations into its pharmacological roles in treating 
depression. 
ALK exhibited a rapid and sustained antidepressant effect in the chronically depressed mice. 
The  metabolite caused a decline in immobility  significantly  at the second day of treatment 
and  increased distanced  travelled at the sixth day of treatment,  the  primary  indices  of 
antidepressant  effect,  in  the  open  space  swim test (Sun and Alkon, 2003; Stone and Lin, 
2011).  Depression is  induced  either over a  period  of weeks  and/or  require exposure to 
traumatic stress and depressed subjects only respond prolonged chronic treatment with 
antidepressants but not to acute or subacute treatment (Stone and Lin, 2011). Most current 
depression pharmacotherapies exhibit delay in symptom improvement, aside from the 
untoward side effects and lack of efficacy against refractory depression (Kukuia et al., 2016). 
Antidepressant effect in this model with respect to the duration of immobility which is 
deemed the more consistent index in mice (Stone et   al.,   2008;   Stone   and   Lin,   2011) 
started on the second day of drug treatment whiles a delay in the onset of action was observed 
in fluoxetine and bupropion treated mice. Although depression is conventionally described as 
a state of neurotransmitter imbalance and currently used antidepressants such as SSRIs, 
TCAs and bupropion   have been designed to achieve these effects more potently and 
selectively via blockade of transporters (Andrade and Rao, 2010). These effects can be 
detected immediately after drug administration, however, the therapeutic effect of some of 
these antidepressant treatments requires a number of weeks to become clinically important 
(Frazer and Benmansour, 2002; Harmer et al., 2009; Samuels and Hen, 2011). Several reports 
have indicated a complex array of downstream neuropharmacological changes, such as 
changes in signal transduction, down regulation of neurotransmitter receptors, desensitization   
of autoreceptors   (5HT1A and   5HT1B/D)   and   transporters, increases   in
 
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hippocampal neurogenesis and mobilization   of   neurotrophins that develop after chronic 
treatment with some of these may be implicated in their clinical efficacy and the duration 
taken for these processes to take place may play a role to the time lag  in  their  clinical 
onset   of   action (Duman and Monteggia, 2006; Harmer et al., 2009; Manji et al., 2003; 
Tardito et al., 2006). Scientific research findings have revealed that 5-HT2C antagonists are 
putative fast-onset antidepressants, which act through enhancement of mesocortical 
dopaminergic   signalling   (Opal   et   al.,   2014).   In   addition,   potential   faster   acting 
antidepressants known to respond to chronic treatment only include serotonin receptor-4 
agonists (Lucas et al., 2007; Mendez-David et al., 2014). Antidepressants that possess 
antagonist effect on 5-HT1A somatodendritic autoreceptors have been reported to exhibit 
accelerated onset of action (Levinstein and Samuels, 2014). The inhibitory effect of  the  5- 
HT1A  autoreceptors   is one   of   the reasons   for   the   delay   in   onset   of   action   of 
antidepressants    affecting    5-HT    systems  (Moret,  2005).  This has been  the  basis  for 
adjunctive therapies with 5HT1A  receptor partial agonists buspirone or pindolol and SSRIs 
(Keks et al., 2007). Recently antidepressants that activate melatonin receptors have been 
reported to demonstrate faster onset of action in animal models (Alamo et al., 2014). 
Recent studies have found that ketamine, a NMDA receptor antagonist, elicits rapid and 
protracted  antidepressant  effects  in  animals  exposed  to  chronic  stress  (Levinstein  and 
Samuels, 2014). It can therefore be hypothesized that the ALK which may have revealed to 
produce an enhancement in monoaminergic neurotransmission in the TST and FST might as 
well possibly be acting on other systems and/or receptors thus demonstrating a rapid onset of 
behavioural effect in the open space swim test. 
The detailed specification of the neural mechanisms underlying the effects of potential 
antidepressants  can  characterized  novel  candidates  implicated  in  the  pathophysiology of 
depression and the search for possible new targets for therapeutic intervention (Cryan and
 
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Lucki, 2000). The present study investigated the role of noradrenaline and dopamine in the 
acute behavioural effects  of  the ALK in  the  modified  FST and TST by  using  drugs  
that impede   with their neurotransmitter   biosynthesis   and/or   release. Pre-treatment with 
α- methyldopa, a competitive inhibitor of the enzyme DOPA decarboxylase that inhibits the 
conversion of L-DOPA to dopamine and hence inhibiting the biosynthesis of catecholamines 
(Chhabra, 2016) abolished the antidepressant effects of the ALK and imipramine but failed to 
attenuate the behavioural effects of fluoxetine. This suggests that the ALK may affect the 
biosynthesis  of  noradrenaline  and/or  dopamine.  Moreover, dopamine beta-hydroxylase 
coverts α-methyldopa to α-methylnorepinephrine which is an agonist of pre-synaptic CNS α2- 
adrenergic receptors. Activation of these receptors in the brainstem leads to inhibition of 
vesicular release of noradrenaline (Chhabra, 2016). Thus results may also suggest that ALK 
may also be involved in the vesicular release of NA probably via blockade of presynaptic α2- 
adrenergic receptors. In addition, pre-treatment of mice with reserpine alone reversed the 
decline  in  immobility  induced  by  the ALK  and  IMI  whiles  that  of  fluoxetine  was  not 
significantly affected  in  both  TST  and  FST.  Reserpine  irreversibly blocks  the  vesicular 
monoamine  transporter  2  (VMAT-2)  which  is  located  primarily within  the  CNS  and  is 
responsible  for  transporting  free intracellular monoamines  into secretory vesicles (Ji et al., 
2007; Metzger et al., 2002; Wimalasena, 2011). Thus the ability of reserpine pre-treatment to 
attenuate the reduction in immobility of ALK may suggest that the depletion of vesicular 
pools  of  monoamines  may affect  the  action  of  the ALK  since  reserpine  treatment  leads  
to depletion of vesicular monoamine stores (Fukui et al., 2007). The ability of reserpine pre- 
treatment  to  reverse  the  antidepressant  effects  of  the  extract  and  imipramine  but  not 
fluoxetine however, seem to suggest that reserpine does not affect vesicular storage of 5-HT 
to the same extent as that of noradrenaline. Wimalasena, (2011) reported that reserpine has a 
lower inhibitory affinity for VMAT 2 – mediated 5HT transport into secretory vesicles.  This
 
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report is coherent with the results obtained by  Woode et al., (2010) showing  that reserpine 
at the dose used produced a 93 and 95%  diminution  of  cortical noradrenaline and dopamine 
content  respectively,  and  a  78% depletion  of  5-HT levels. To inhibit both synthesis and 
deplete vesicular storage of noradrenaline and dopamine, mice  were pre-treated with  α- 
methyldopa and reserpine. The results demonstrated that a combined treatment of reserpine 
and α-methyldopa significantly abolished the antidepressant effect of the ALK and IMI but 
not FLX similar that obtained when reserpine and α-methyldopa were administered alone. 
Additionally the increase in both climbing and swimming behaviours observed in the ALK 
and IMI treated mice were reversed in both ALK and IMI but these behaviours were not 
affected in FLX after pre-treatment with both reserpine and α-methyldopa. Thus, the 
combination had only a reasonable effect on NA and DA but failed to have any significant 
affect 5-HT neurotransmission. These results demonstrate that the antidepressant effect of 
ALK may be dependent on noradrenergic neurotransmission. 
The pharmacological role of some specific adrenergic receptors in the antidepressant activity 
of ALK was investigated. Results of the study shows that the anti-immobility effects of the 
ALK was not affected by prazosin (α1-receptor antagonist) but the antidepressant effect of 
atomoxetine   (selective noradrenaline re-uptake inhibitor) was inhibited by prazosin pre- 
treatment. Stone et al., (2003) reported that activation of brain α1-adrenoceptors are 
instrumental in behavioural activation, particularly sensitive to stress and its desensitization 
or blockade has been implicated in depressive illness. The inability of prazosin to reverse the 
antidepressant effect of the ALK may suggest that the ALK may not be acting via activating 
α1- adrenoceptors. The study also revealed that yohimbine (α1-receptor antagonist) 
potentiated the anti-immobility effect of ALK thus a demonstration of potential noradrenaline 
toxicity. Studies have shown that major depression is accompanied by increased α2-adrenergic 
receptors in the hippocampus and cerebral cortex (Hieble, 2007). Presynaptic α2-adrenergic
 
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receptors  are  inhibitory  autoreceptors  that  regulate  NA     release  and  therefore  their 
antagonism increases noradrenaline release (O'Donnell, 2009). Similarly, if presynaptic α2- 
adrenergic receptors are essential for the antidepressant-like effect of a drug, blockade of the 
receptor would be expected to potentiate rather than block its effects on behaviour, however, 
the opposite is observed if postsynaptic α2-adrenergic receptors are involved (Zhang et al., 
2009). Studies using post-mortem specimens from depressed suicide victims shows an 
increase in α2A-receptors in the prefrontal cortex which suggest that α2-adrenergic antagonists 
may produce antidepressant effect (Zhang et al., 2009). The present results suggest that 
blockade of pre-synaptic, α2-adrenergic receptors may play a major role in the mediation of 
antidepressant effects of t h e  ALK. These results demonstrate that the antidepressant 
effect of ALK may partly be dependent on noradrenergic neurotransmission. 
In the present study, the pre-treatment of pCPA, a selective inhibitor of the rate-limiting 
enzyme in the biosynthesis of serotonin, tryptophan hydroxylase, was the approach used to 
deplete endogenous brain serotonin levels without affecting noradrenergic and dopaminergic 
synthesis (O'Leary et al., 2007). This treatment was able to abolish the antidepressant effect 
of ALK, FLX and IMI in the TST and FST, indicating that its observed antidepressant 
activity is dependent on the enhancement of serotoninergic neurotransmission. The reversal 
of the antidepressant activity of fluoxetine in pCPA treated mice is coherent with reports that 
fluoxetine  demonstrate  its  acute  behavioural  effects  via  the  selective  blockade  of  the 
serotonin transporter thus increasing extracellular serotonin in the synaptic cleft (Colla et al., 
2012). ALK, imipramine and  fluoxetine  increased  swimming  score which was  reversed 
with pCPA pre-treatment, further  augmenting their  action  on  the  serotoninergic  system 
(Chau et al., 2011). In the present study, the anti-immobility effect elicited by ALK in TST 
and FST was blocked by the pre-treatment of mice with cyproheptadine (a 5-HT2 receptor 
antagonist). Several clinical studies have shown that antidepressant with affinity for 5-HT2A
 
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receptors augment the clinical response to SSRIs in treatment-resistant patients (Shelton et 
al., 2001) recent study indicates its involvement in SSRI-mediated actions, showing also 
antidepressant-like properties of selective 5-HT2B receptor agonists (Diaz et al., 2012). 
Desensitization of 5-HT2C receptors is also reported following chronic SSRI treatment. 
Preclinical data show that 5-HT2C antagonism augments the neurochemical and behavioural 
effects of SSRIs (Cremers et al., 2007). This further confirms the role of the 5-HT system in 
the mechanism of the antidepressant activity of ALK. 
Several studies have support the role of the glutamatergic system in the pathophysiology of 
affective disorders as well as the efficacy of glutamatergic compounds such as functional 
glycine/NMDA receptor antagonists as antidepressant agents (Zarate et al., 2013). These 
agents have been reported to demonstrate a relatively lower side effect  profiles  compared 
to  the  competitive  and  non-competitive  NMDA  antagonists (Poleszak et al., 2011). This 
study demonstrated that the pre- treatment of mice with D-cycloserine (a partial agonist of 
glycine/NMDA receptors) further potentiated the anti-immobility effect of ALK in both the 
TST and FST suggesting that ALK may be acting as an antagonist on the glycine/NMDA 
receptor complex. In contrast, pre-treatment of D-serine (a full agonist on glycine/NMDA 
receptors) blocked the anti-immobility effect of ALK, FLX and IMI indicating that activation 
of the glycine/NMDA receptor complex causes a diminution of antidepressant activity of 
both serotonin and noradrenaline-based compounds (Wlaz´ et al., 2011). Preclinical and 
clinical observations have shown that monoaminergic-based antidepressants decrease NMDA 
binding, expression and function (Skolnick, 1999). Several reports have stated that the 
interaction between NMDA receptor and serotoninergic neurotransmission is more palpable 
than NMDA receptor and noradrenergic pathway and thus interaction between glutamate and 
serotonin may be important for the control of many brain activities (Poleszak et al., 2011; 
Szewczyk et al., 2009). The increase in swimming behaviour demonstrated by ALK saw a
 
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further rise with D-cycloserine pre-treatment but a reversal effect was exhibited with D-serine 
pre-treatment. Climbing scores of the ALK treated mice were not affected by both D-serine 
and D-cycloserine pre-treatment.  This result further supports the  theory  that  the  
interaction between NMDA receptor and serotoninergic neurotransmission is more palpable 
than NMDA receptor and noradrenergic pathway. 
The glycine/NMDA receptor antagonistic effect of the ALK in addition to its enhancement in 
monoaminergic neurotransmission strongly supports the rapid onset of behavioural effect 
demonstrated in the open space swim test. Recent studies demonstrate that a NMDA receptor 
antagonist ketamine, could address the limited efficacy and time lag for therapeutic response 
to typical antidepressants (Duman and Li, 2012). Chronic physical and social stress impairs 
neurogenesis, while chronic antidepressant treatments including serotonin-selective reuptake 
inhibitors (SSRIs) and norepinephrine-selective reuptake inhibitors (NSRIs) enhance 
neurogenesis (Sahay and Hen, 2007). Effective chronic antidepressant   treatments are 
associated  with  an  improvement  of  hippocampal neurogenesis, upsurge  in  neurotrophin 
levels, increase of synaptic function  and  a  resultant rise in  hippocampal function  which 
can  be  quantified as  neuronal  response  or  behaviour (Monteggia et al., 2007). Thus the 
effectiveness and the sustained antidepressant effect of ALK may be partly due to effect on 
synaptogenesis and neurotrophic factors. 
The L-arginine-NO-cGMP pathway has been associated with the pathophysiology of 
depression (Kaster et al., 2005). Nitric oxide plays an essential role in the CNS and 
pharmacological modulation of the NO pathway may be seen as a novel therapeutic approach 
for the effective management of depression (Zomkowski et al., 2012). The involvement of 
nitric oxide signalling pathway has been demonstrated in the antidepressant activity of 
venlafaxine, bupropion and berberine chloride (an alkaloid obtained from Berberis aristata) 
(Dhir and Kulkarni, 2007). 
 
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In this study, it was shown that the reduction of immobility time elicited by ALK in the FST 
and TST was attenuated by pre-treatment of mice with L-arginine (NOS substrate). Previous 
studies have demonstrated that the antidepressant-like effects of paroxetine was blocked by 
pre-treatment with L-arginine (Ghasemi et al., 2009) and that of   putative antidepressant 
ascorbic acid (Moretti et al., 2011). This result may suggest that the antidepressant effect of 
ALK may be dependent on the inhibition of NO synthesis. Furthermore, a potentiated 
antidepressant effect was observed with the pre-treatment of L-NAME (a non-selective NOS 
inhibitor) in ALK treated mice. Several studies have exhibited that NOS inhibitors elicit 
antidepressant activity in animal models predictive of antidepressant effect (Mutlu et al., 
2009). In addition, pre-treatment of mice with methylene blue (direct inhibitor of both NOS 
and sGC) produced a synergistic antidepressant effect with ALK. This result also suggests 
that the anti-immobility effect of ALK may as well be partly mediated by the inhibition of 
NOS and/or sGC activity. Similar to our results, a research demonstrated that methylene blue 
potentiated the antidepressant-like effect of venlafaxine in  the FST  (Dhir  and  Kulkarni, 
2007). Heiberg et al. (2002) demonstrated that excessive cGMP levels may generate some 
depressive symptoms and decreasing its levels may show antidepressant-like actions. 
Phosphodiesterase enzyme is resonsible for the degradation of cGMP. Therefore inhibiting 
the enzymatic activity of phosphodiesterase may cause an upsurge in the levels of cGMP and 
thus produce depressive-like conditions (Dhir and Kulkarni, 2007).  In this study, the anti- 
immobility effect of ALK was not affected by the pre-treatment with sildenafil (a selective 
phosphodiesterase-5 inhibitor).This indicates that ALK may probably not exert its 
antidepressant by directly decreasing cGMP levels but via nitric oxide synthesis inhibition. 
It has been reported that L -arginine blocks the antidepressant effects of the classical TCA, 
imipramine (Harkin et al., 2003).  This observation has led to hypotheses regarding the 
potential   contribution   of   serotoninergic/noradrenergic   mechanisms   in   the   observed
 
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antidepressant-like effects of the NOS inhibitors. In addition, NO can inactivate tryptophan 
hydroxylase, the rate limiting enzyme in the synthesis of serotonin (Kuhn and Arthur, 1997) 
and also ineffective doses of NOS inhibitors potentiate antidepressant effect of TCAs, SSRIs 
but not SNRIs in the FST (Harkin et al., 2003). Therefore, the possible mediation of the nitric 
oxide system in the observed antidepressant activity of the ALK could be attributed to its 
interaction with the serotoninergic system. These results further reinforces the assumption in 
this study that the ALK may have demonstrated its antidepressant effect partly via inhibition 
of NO synthesis and thus points to a significant role of nitrergic system in the mechanism of 
action of antidepressant agents (Wegener and Volke, 2010). 
 
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Figure 5.1: A schematic representation of the proposed mechanism of action of the ALK extracted from 
HEE of the stem bark of T. monadelpha. The interaction of the ALK with the serotoninergic-
noradrenergic-nitric oxide-glycine/NMDA-opioidergic pathways leads to a cascade of signal 
transduction mechanisms which are responsible for the observed antidepressant effect. 
 
5.2 CONCLUSION 
The research provides scientific evidence that the hydroethanolic, ethyl acetate and petroleum 
ether extracts from the stem bark of Trichilia monadelpha demonstrate antidepressant effect in 
murine models. The hydroethanolic extract was found to be the most efficacious. 
Total alkaloids, saponins, flavonoids, tannins and terpenoids extracted from the hydroethanolic 
extract exhibited antidepressant potentials in various acute murine models. Total alkaloids were 
 
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found to be the most efficacious. Total alkaloids demonstrated a rapid and sustained 
antidepressant effect in the open space swim test. 
The observed antidepressant effect of the ALK may be attributed to its possible complex 
interaction with several systems: noradrenergic, serotoninergic, glycine/NMDA receptor, L-
arginine-NO-cGMP, opioidergic pathway. Specifically, blockade of α2-adrenergic receptors, 
enhancement of 5-HT2 receptors, antagonism of glycine/NMDA receptors and inhibitory effect 
on nitric oxide synthesis (NOS) and soluble guanylate cyclase (sGC) may explain the observed 
behavioural effects. 
5.3 RECOMMENDATION 
 The active pure compound(s) responsible for the rapid and sustained antidepressant 
effect of the crude alkaloids should be isolated and characterized. 
 Chronic toxicity on the alkaloids should be evaluated to establish its safety. 
 Other models of depression should be used to assess/confirm the antidepressant 
properties of the alkaloid and investigate other possible mechanism(s) of action. 
 Some of the secondary metabolites should be combined and their antidepressant efficacy 
and onset of antidepressant effect evaluated. 
5.4 LIMITATION 
  The study did not incorporate the determination of the onset of antidepressant action 
of the crude hydroethanolic extract in the open space swim test.
 
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