Systems Pharmacology-Based Research on the Mechanism of Danzhi Xiaoyao San in the Treatment of Depression

Jingxiao Zhang; Ziyi Chen; Fengge Gao; Yanli Fan; Xuezhen Huang; Wei Zhou

Research Article

Austin Pharmacol Pharm. 2023; 7(1): 1026.

Systems Pharmacology-Based Research on the Mechanism of Danzhi Xiaoyao San in the Treatment of Depression

Jingxiao Zhang^1,2; Ziyi Chen¹; Fengge Gao²; Yanli Fan²; Xuezhen Huang²; Wei Zhou^1-3*

¹State Key Laboratory of Respiratory Disease for Allergy at Shenzhen University, Shenzhen Key Laboratory of Allergy & Immunology, Shenzhen University School of Medicine, Shenzhen University, China

²College of Food and Drug, Luoyang Normal University, China

³Department of Respirology & Allergy. Third Affiliated Hospital of Shenzhen University, Shenzhen University, China

*Corresponding author: Wei Zhou State Key Laboratory of Respiratory Disease for Allergy at Shenzhen University, Shenzhen Key Laboratory of Allergy & Immunology, Shenzhen University School of Medicine, Shenzhen University, China. Tel: +0379-68618516 Email: [email protected]

Received: May 09, 2023 Accepted: June 08, 2023 Published: June 15, 2023

Abstract

Depression is a common and serious mental disorder characterized by persistent feeling of sadness and loss of interest in activities. Despite conventional treatments can improve depression symptoms and prevent a recurrence, complementary and alternative therapies are necessary to be involved because of the detrimental effects of the current therapy. Traditional Chinese Medicine (TCM) formulas are considered to be a potential complementary method with special advantages for treating the multiple pathogenesis of depression in a holistic way. However, the underlying pharmacological mechanism of TCM formula on depression therapy remained elusive. Therefore, in current study, a systems pharmacology approach integrating Absorption, Distribution, Metabolism, and Excretion (ADME) filtering, target fishing, gene enrichment analysis, network pharmacology, and pathway analysis was developed to comprehensively explore the multiple therapeutic mechanisms of Danzhi Xiaoyao San (DZXYS) for the treatment of depression. Finally, 111 active components and 112 potential targets of DZXYS were identified through ADME filtering and target fishing. Gene enrichment analysis found that DZXYS played a significant role in treating depression through the regulation of multiple pathogenesis including neurotransmitter systems imbalance, brain derived neurotrophic factor, hypothalamic-pituitary-adrenal axis dysregulation, inflammation, and immune. Moreover, the compound-target and target-pathway networks were constructed to elucidate the therapeutic mechanism of DZXYS from the system perspective. This study proposes a promising way for facilitating in-depth understanding of the complicated therapeutic mechanism of TCM on depression.

Keywords: Danzhi xiaoyao san; Systems pharmacology; Active compounds; Depression; Mechanisms

Introduction

Depression is a multifactorial psychiatric disorder, characterized by specific symptoms including listlessness, interest drops, extreme of inferiority, hopelessness or guilt and a reduced ability to enjoy life [1]. According to the report released by World Health Organization (WHO), more than 350 million people worldwide are affected by depression, leading to a tremendous public health burden [2]. Evidence showed that depression is a systemic disease rather than a mental disorder, which always involves different pathophysiology mechanisms including neurotransmitter systems imbalance, decreased Brain Derived Neurotrophic Factor (BDNF), abnormal gene expression, Hypothalamic-Pituitary-Adrenal (HPA) axis dysregulation, impaired inflammatory response and immune regulation.

Antidepressant drugs are commonly used to help alleviate the symptoms of depression and prevent relapse of the illness. The current available clinical antidepressant medications mainly act on monoamine transmitters including serotonin and norepinephrine [3]. However, these drugs often cause detrimental effects, such as lagging, low compliance and failed treatment, which will lead to the intolerant or refractory responses of many patients [4,5]. Therefore, it is urgent to develop antidepressant drugs based on multiple pathogenesis against depression. Traditional Chinese medicine (TCM) as one of the major complementary and alternative medicine therapies featured as multi-components and multiple targets have been shown to possess special advantages for the treatment of complex pathogenesis of depression [6,7].

Danzhi Xiaoyao San (DZXYS), recognized as a classical prescription from Abstract for Chinese Internal Medicine (Nei Ke Zhai Yao) has been widely used to treat depression for many years. This herbal formula is composed of Radix Bupleuri (Chai- Hu), Paeoniae Radix Alba (Bai-Shao), Angelica Sinensis Radix (Dang-Gui), Fu-Ling, Atractylodes macrocephala Koidz. (Bai-Zhu), Licorice (Gan-Cao), Moutan Cortex (Mu-Dan-Pi), and Gardeniae Fructus (Zhi-Zi). A previous clinical study suggested that DZXYS played a significant role in lowering the Hamilton depression scale (HAMD), reducing the scores of anxiety/somatization, reversing cognitive impairment and feeling of despair in depressive patients [8]. Although DZXYS exhibit multiple therapeutic effects for relieving the symptoms of depression, its active compounds, related targets, pathways and underlying pharmacological mechanism remain elusive.

Systems pharmacology has been suggested as a promising approach to shift away from the traditional “one-drug, one-target, one-disease” towards the “multi-component, multi-target” strategy, which will shed light on a comprehensive investigation to systemically dissect the relationship between drugs, targets, pathways and diseases, as well as the potential pharmacological mechanisms of herbal formulae on disease therapy. Growing evidence revealed that systems pharmacology method is capable of uncovering the complicated pharmacological mechanisms of TCM herbs and formulas on the treatment of various diseases. For example, the combinatorial rule and the pharmacological mechanisms of Qing-Luo-Yin and Liu-Wei-Di-Huang Pill for the treatment of rheumatoid arthritis and various diseases were elucidated from a network/systemic perspective [9,10]. In our previous work, systems pharmacology has been successfully used to explore the potential mechanisms of the single herb and herb pairs for various diseases therapy [11,12]. In addition, a series of systems pharmacology frameworks have been developed to disclose the underlying mechanisms of TCM formulas for stroke, asthma and obesity [13-15].

Therefore, in current study, an integrative systems pharmacology strategy, which combines ADME (absorption, distribution, metabolism, and excretion) filtering, target fishing, gene enrichment analysis, network pharmacology and pathway analysis is proposed to reveal the multiple mechanisms of DZXYS in treating depression based on a holistic and systemic way. The detailed work flowchart is shown in Figure 1. The systems pharmacology framework constructed in our study not only sheds light on providing a probe to explore the complex therapeutic mechanism of DZXYS for depression at the system level, but also promotes the modernization and internationalization of TCM formulas.

Figure 1: Overall survival, autologous stem cell transplant (ASCT) versus no ASCT(p=0.12).

    
    
    Figure 1: Overall survival, autologous stem cell transplant (ASCT) versus no ASCT (p=0.12).

Materials and Methods

Building the Compound Database of DZXYS

The chemical constituents of DZXYS were extracted from the TCMSP (Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, https://tcmspw.com/tcmsp.php) database, and then manually supplemented from abundant literatures of CNKI and PubMed databases. All structures of these constituents were downloaded from TCMSP and NCBI PubChem databases, and then subjected to full geometry optimization using GUASS package with the same parameters as our previous work [16,17]. Considering that compounds with glycosyls cloud undergo glycosidase hydrolysis reaction before being absorbed, in this section, their corresponding aglycones were also added into the compound database of DZXYS for further research.

Active Compounds Screening

Predicting ADME properties of drug candidate molecules plays an important role in drug development, because of the fact that the failure of 60% of drug molecules is related to poor ADME properties [18]. Therefore, early ADME prediction of a candidate compound can significantly reduce the cost of drug research. For herbal medicine, it usually contains hundreds of constituents, but only a few bioactive compounds provide physiological benefits for human health. Identifying the active ingredients with favorable ADME properties is a fundamental step to uncover the therapeutic effects of DZXYS. In the present work, three in silico models, i.e., Drug-Likeness (DL), Oral Bioavailability (OB), and Blood-Brain Barrier (BBB) were employed to screen the potential active compounds of DZXYS.

Drug-likeness calculation: Drug-likeness is a qualitative profile used in drug design to optimize pharmacokinetic and pharmaceutical properties, such as solubility, and chemical stability. Therefore, for deciphering the molecular mechanism of functional food, it is first necessary to apply drug-likeness filter to remove non-drug-likeness compounds from the molecule database, and then just focus on the drug-likeness molecules [19]. In the present work, a robust in silico model was employed to screen the molecules with drug-likeness features from compound database of DZXYS. In this model, Tanimoto coefficient (as shown in Equation (1)) was used to calculate the DL index of each compound of DZXYS.

In which, A is the molecular descriptors of constituents of DZXYS, and B is the average molecular properties of 6511 small drug-like and drug molecules in DrugBank database (http://www.drugbank.ca). The DL threshold is ultimately set to 0.18, which is based on the average DL value in the DrugBank database.

Oral bioavailability evaluation: Being an important ADME parameter, oral bioavailability indicates the fractional extent of the oral bioactive molecule dosage which finally reaches its target site to exhibit the pharmacological activity [20]. In present work, OB value was also employed to screen the active constituents from DZXYS, and the values were computed through a reliable in silico model OBioavail 1.1 [21]. This model was built using metabolism (P450 3A4) and transport (P-glycoprotein) information of 805 drug and drug-like molecules. The linear (i.e., Partial Least Square (PLS), Multiple Linear Regression (MLR)), and nonlinear (support vector machine (SVR)) methods were used to construct this model, ending up with an optimal model holding a determination coefficient (R²) of 0.80 and a Standard Error of Estimate (SEE) of 0.31 for test sets. Finally, herbal constituents with proper OB values (OB ≥30%) were screened as the candidate compounds for further research.

BBB penetration: Blood-brain barrier is a highly selective semipermeable membrane that regulates the passage of small and large molecules into the Central Nervous System (CNS) [22]. Therefore, being the chief obstacle to the delivery of drugs to the CNS, BBB permeability was selected to identify the candidate ingredients that targeted the patient’s. CNS involved in the damp depression. Here, a reliable in silico BBB model constructed in our previous work [23] was employed to predict the BBB permeabilities of all compounds in DZXYS databases. Finally, the compounds with BBB values greater than -0.3 were identified as favorable BBB permeabilities, since molecules with less than -0.3 is not permeable.

Target Fishing and Gene Ontology Enrichment Analysis

Identifying compound-target interaction is a crucial task in drug discovery and elucidating the mechanism of drug action [24]. Here, a combinatorial method enriched with chemogenomic, similarity ensemble and data-mining approaches was employed to identify the compound-target interaction. First, the filtered active compounds were sent to the TTD (Therapeutic Targets Database http://bidd.nus.edu.sg/group/ttd/) and DrugBank databases to mine the compound-target interactions supported by abundant literatures. Second, two robust in silico models for identifying compound-target interaction, i.e., omics-based Ligand-Target Chemogenomic model (LTC) [25] and Similarity Ensemble Approach (SEA, http://sea.bkslab.org/) [26], were implemented to obtain the target proteins of filtered active compounds. Subsequently, all target information from the above two steps was sent to the database of Uniprot database (https://www.uniprot.org/) to eliminate the overlaps and noise. Finally, we mapped all target genes of DZXYS to the databases of Drug Bank, TTD, OMIM and DisGeNET to build the connections with depression.

Gene Ontology (GO) analysis was employed to reveal how active compounds of DZXYS acted on the multiple pathological mechanisms of depression. All depression- related target proteins of DZXYS were inputted into ClueGO plugin of Cytoscape 3.8.2 using p-value≤0.05 as the restriction, and GO enriched terms for cellular components, biological process and molecular functions were identified.

Network Construction and Analysis

Abundant experimental and clinical evidence has demonstrated that the pathological mechanism of depression mainly implicated in disorder of neurotransmitter, dysfunction of nervous system (BDNF, brain-derived neurotrophic factor), disorder of signal transduction (HPA (Hypothalamic Pituitary Adrenal) axis), metabolism imbalance, as well as dysregulation of inflammatory and immune responses. All target proteins of DZXYS were mapped onto these different pathological mechanisms of depression. Subsequently, Compound-Target network (C-T network) implicated in six individual pathological mechanisms were constructed to further discover the underlying mechanism of DZXYS in the treatment of depression. Pathway enrichment was employed to obtain the representative pathways of six pathological mechanism involved in depression based on Metascape databases [27]. Afterwards, these pathways and their linked target genes of DZXYS were used to construct T-P network. All visualized network graphs were constructed by Cytoscape 3.8.2 [28].

Results and Discussion

Filtering Active Components from DZXYS

A total of 1078 DZXYS candidate molecules were finally extracted from abundant literatures and TCMSP database, including 1036 ingredients from these 8 herbal medicines and 42 aglycones (Supplementary Table S1). Among them, Chai-Hu owned the largest number of constituents (347 molecules), as followed by Gan-Cao with 280 components and Dang-Gui with 126 chemicals. Other herbal medicines, Zhi-Zi, Bai- Shao, Mu-Dan-Pi, Bai-Zhu, and Fu-Ling contained 97, 84, 57, 55 and 33 compounds, respectively.

In general, an oral administrated medicine must overcome several in vivo obstacles like bioavailability, chemical and physical stabilities, before exhibition of the pharmacological effect at the binding site. Therefore, to identify the active molecules from DZXYS, we employed three classical in silico ADME parameters (including DL, OB and BBB). As a result, 106 active molecules from these eight herbal medicines in the DZXYS were found meeting the screening thresholds with satisfactory ADME profiles. For example, liquiritigenin, a flavonoid compound in Gan-Cao, displayed the favorable pharmacokinetic profiles (OB=32.76%, DL=0.18 and BBB=-0.29), and this compound was proved alleviating depressive-like behavior via inhibiting p-phosphatidylinositol 3-kinase (PI3K)/Akt/p-Mammalian Target of Rapamycin (mTOR) pathway and improving BDNF/p-tropomyosin-related kinase B (TrkB) pathway in mice model of depression [29]. A phytosterol compound beta-sitosterol (OB=36.91%, DL=0.87 and BBB=0.75) which is shared by Bai-Shao, Dang-Gui, Gan-Cao, Mu-Dan-Pi and Zhi-Zi also displayed anti-depressant-like activity in mice model. Betulinic acid (OB=55.38%, DL=0.78 and BBB=0.22), a pentacyclic triterpenoid shared by Bai-Shao, Gan-Cao and Mu-Dan-Pi, also reduced depressant-like behavior in tail suspension test [30]. A stigmastane-type phytosterol in Chai-Hu, a-spinasterol (OB=42.98%, DL=0.76 and BBB=0.79), which is a multitarget transient receptor potential cation channel subfamily V member 1 (TRPV1) antagonist and cyclooxygenase (PTGS1 (prostaglandin G/H synthase 1) and PTGS2 (prostaglandin G/H synthase 2)) inhibitor, exhibited anti-depressant-like effect in mice model [31,32]. Hederagenin (OB=36.91%, DL=0.75 and BBB=0.96), a triterpenoid saponin in Chai-Hu, also exhibited the anti-depression activity via regulating the expression of monoamine neurotransmitters and 5-hydroxytryptamine (serotonin) 1A receptor mRNA in rat model of depression [33]. a-Amyrin (OB=39.51%, DL=0.76 and BBB=1.28) was a pentacyclic triterpenoid from Bai-Zhu, and also exhibited the potent anti-depression effect through increasing the activities of amine oxidase [flavin-containing] A (MAOA) and Gamma Aminobutyric acid (GABA) in mice hippocampus [34]. Isoimperatorin (OB=45.46%, DL=0.23 and BBB=0.66), an active furocoumarin in Zhi-Zi, had a dual PTGS2 selective/5-lipoxygenase inhibitory property, making it possible for a novel anti-inflammatory drug. All these results convincingly proved the reliability and feasibility of our filter model.

As we know, different from the allopathy of western medicine, herbal formula featured as a holistic treatment regulates multiple therapeutic pathways to maintain the balance of human body. Factually, the pathological factors implicated in depression not only focus on the central nervous system, but also correlate with the cytokine hypothesis, oxidative stress and NO pathway [35]. Therefore, some major ingredients which possessed pharmacokinetic and pharmacological properties, but low BBB indexes, were also added into the active compound database, including paeoniflorin (OB=53.87%, DL=0.79, BBB=-1.86) and pachymic acid (OB=33.63%, DL=0.81, BBB=-0.57). For instance, paeoniflorin, the major active constituent found in Bai-Shao and Mu-Dan-Pi, had been reported to modulate HPA axis, via up-regulating serotonergic (serotonin and 5-hydroxyindoleacetic acid) and noradrenergic (noradrenaline) systems, ameliorating neuroinflammation and depressive-like behaviors, which contributed to a candidate molecule for the treatment of depression [36,37]. The other compound pachymic acid, a predominant triterpenoid in Fu-Ling, also had multiple pharmacological properties, such as anti-inflammation, anti-cancer and anti-vomiting [38].

To avoid the missed active constituents, a few active molecules were also manually added into the active molecules database of DZXYS based on text-mining in literature databases. For example, geniposide (OB=14.64%, DL=0.44, BBB=-2.61), as one of the main active molecules (73.44±2.62mg/g) in Zhi-Zi with both medicinal and nutritional effects [39], produced the antidepressant-like property via regulating HPA axis in chronic unpredictable mild stress-induced depressive rats [40], and this compound also ameliorated the depression-like behavior through up-regulating BDNF expression in streptozotocin-evoked diabetic mice [41]. In addition, albiflorin (OB=12.09%, DL=0.77, BBB=-2.19) had a high concentration (12.61±3.09 mg/g) in Bai-

Shao [42], exhibited obvious anti-depressant-like effect via up-regulating the expression levels of hippocampal serotonin (5-HT)/Norepinephrine (NE) and BDNF in mice model of depression [43]. Ferulic acid (OB=39.56%, DL=0.06, BBB=-0.03) in Dang-Gui is a marker for evaluating the quality of this herb, because of relative high concentration (0.21~1.75mg/g dry weight) and abundant pharmacological effects, like antidepressant-like, anti-inflammatory, anti-microbial, and anti-hyperlipidemic properties [44]. Therefore, these molecules were manually added into the active molecule database of DXP, although they obtained the low DL values or OB indexes.

By combining the results of filter model and text-mining, finally, 120 molecules were screened as the candidate active ingredients of DZXYS, and their ADME parameters were displayed in Table 1. Among them, Gan-Cao has the largest number of active ingredients (72 molecules), as followed by Chai-Hu and Mu-Dan-Pi both with

Table 1: The active ingredients and ADME parameters of DZXYS.




  
    MOL ID
    Molecule Name
    CAS
    DL
    OB(%)
    BBB
    Herbs
  
  
    CH257
    (+)-Anomalin
    73069-28-0
    0.66
    46.06
    0.00
    Chai-Hu
  
  
    BZ016
    (24S)-24-Propylcholesta-5-ene-3beta-ol
    64997-52-0
    0.78
    36.23
    1.09
    Bai-Zhu
  
  
    GC200
    (2R)-7-Hydroxy-2-(4-hydroxyphenyl)

      chroman-4-one
    41680-09-5
    0.18
    71.12
    -0.25
    Gan-Cao
  
  
    GC173
    1,3-Dihydroxy-9-methoxy-6- benzofurano[3,2-c]chromenone
    - 
    0.43
    48.14
    -0.19
    Gan-Cao
  
  
    GC218
    1-Methoxyphaseollidin
    65428-13-9
    0.64
    69.98
    0.48
    Gan-Cao
  
  
    CH205
    3',4',5',3,5,6,7-Heptamethoxyflavone
    17245-30-6
    0.59
    31.97
    0.08
    Chai-Hu
  
  
    ZZ053
    3-Epioleanolic acid
    25499-90-5
    0.76
    32.03
    0.39
    Zhi-Zi
  
  
    GC225
    3'-Hydroxy-4'-O-Methylglabridin
    - 
    0.57
    43.71
    0.73
    Gan-Cao
  
  
    GC233
    3'-Methoxyglabridin
    74046-05-2
    0.57
    46.16
    0.47
    Gan-Cao
  
  
    BZ032
    3β-Acetoxyatractylone
    61206-10-8
    0.22
    54.07
    1.08
    Bai-Zhu
  
  
    GC237
    4'-Methoxyglabridin
    - 
    0.52
    36.21
    0.61
    Gan-Cao
  
  
    MDP040
    4-O-methylpaeoniflorin_qt
    - 
    0.43
    67.24
    -0.15
    Mu-Dan-Pi
  
  
    GC247
    6-Prenylated eriodictyol
    - 
    0.41
    39.22
    -0.29
    Gan-Cao
  
  
    GC249
    7-Acetoxy-2-methylisoflavone
    3211-63-0
    0.26
    38.92
    0.16
    Gan-Cao
  
  
    GC057
    7-Methoxy-2-methyl isoflavone
    19725-44-1
    0.20
    42.56
    0.56
    Gan-Cao
  
  
    BZ055
    8β-Ethoxy atractylenolide ? 
    113269-35-5
    0.21
    35.95
    1.12
    Bai-Zhu
  
  
    ZZ062
    Ammidin
    482-44-0
    0.22
    34.55
    0.92
    Zhi-Zi
  
  
    CH216
    Areapillin
    83162-82-7
    0.41
    48.96
    -0.29
    Chai-Hu
  
  
    BS007
    Beta-sitosterol
    83-46-5
    0.75
    36.91
    0.87
    Bai-Shao
  
  
    DG021
    Beta-sitosterol
    83-46-5
    0.75
    36.91
    0.87
    Dang-Gui
  
  
    GC011
    Beta-sitosterol
    83-46-5
    0.75
    36.91
    0.87
    Gan-Cao
  
  
    MDP010
    Beta-sitosterol
    83-46-5
    0.75
    36.91
    0.87
    Mu-Dan-Pi
  
  
    ZZ014
    Beta-sitosterol
    83-46-5
    0.75
    36.91
    0.87
    Zhi-Zi
  
  
    BS002
    Betulinic acid
    472-15-1
    0.78
    55.38
    0.22
    Bai-Shao
  
  
    GC007
    Betulinic acid
    472-15-1
    0.78
    55.38
    0.22
    Gan-Cao
  
  
    MDP005
    Betulinic acid
    472-15-1
    0.78
    55.38
    0.22
    Mu-Dan-Pi
  
  
    ZZ069
    Corymbosin
    18103-41-8
    0.41
    51.96
    -0.21
    Zhi-Zi
  
  
    FL028
    Dehydroeburicoic acid
    6879-05-6
    0.83
    44.17
    -0.16
    Fu-Ling
  
  
    GC278
    Dehydroglyasperins C
    199331-35-6
    0.37
    53.82
    -0.12
    Gan-Cao
  
  
    FL015
    Eburicoic acid
    560-66-7
    0.81
    38.70
    -0.04
    Fu-Ling
  
  
    FL010
    Ergosta-7,22e-dien-3beta-ol
    1105-11-9
    0.72
    43.51
    0.91
    Fu-Ling
  
  
    FL011
    Ergosterol peroxide
    2061-64-5
    0.81
    40.36
    0.34
    Fu-Ling
  
  
    ZZ068
    Ethyl oleate (NF)
    111-62-6
    0.19
    32.40
    1.10
    Zhi-Zi
  
  
    GC068
    Euchrenone
    - 
    0.57
    30.29
    0.39
    Gan-Cao
  
  
    GC175
    Eurycarpin A
    166547-20-2
    0.37
    43.28
    -0.06
    Gan-Cao
  
  
    GC013
    Formononetin
    485-72-3
    0.21
    69.67
    0.02
    Gan-Cao
  
  
    GC254
    Gadelaidic acid
    506-31-0
    0.20
    30.70
    0.94
    Gan-Cao
  
  
    GC116
    Gancaonin A
    27762-99-8
    0.40
    51.08
    0.13
    Gan-Cao
  
  
    GC117
    Gancaonin B
    124596-86-7 
    0.45
    48.79
    -0.10
    Gan-Cao
  
  
    GC258
    Gancaonin G
    126716-34-5
    0.39
    60.44
    0.23
    Gan-Cao
  
  
    GC259
    Gancaonin H
    126716-35-6
    0.78
    50.10
    -0.14
    Gan-Cao
  
  
    GC123
    Gancaonin L
    129145-50-2
    0.41
    66.37
    -0.13
    Gan-Cao
  
  
    GC124
    Gancaonin M
    129145-51-3
    0.41
    30.49
    0.21
    Gan-Cao
  
  
    GC126
    Gancaonin O
    129145-53-5
    0.41
    44.15
    -0.28
    Gan-Cao
  
  
    GC170
    Glabranin
    41983-91-9
    0.31
    52.90
    0.31
    Gan-Cao
  
  
    GC171
    Glabrene
    60008-03-9
    0.44
    46.27
    0.04
    Gan-Cao
  
  
    GC168
    Glabridin
    59870-68-7
    0.47
    53.25
    0.36
    Gan-Cao
  
  
    GC172
    Glabrone
    60008-02-8
    0.50
    52.51
    -0.11
    Gan-Cao
  
  
    GC089
    Glepidotin A
    42193-83-9
    0.35
    44.72
    0.06
    Gan-Cao
  
  
    GC090
    Glepidotin B
    87440-56-0
    0.34
    64.46
    -0.09
    Gan-Cao
  
  
    GC070
    Glyasperin B
    142488-54-8
    0.44
    65.22
    -0.09
    Gan-Cao
  
  
    GC073
    Glyasperin C
    142474-53-1
    0.40
    45.56
    0.07
    Gan-Cao
  
  
    GC072
    Glyasperin F
    145382-61-2
    0.54
    75.84
    -0.15
    Gan-Cao
  
  
    GC265
    Glyasperins M
    - 
    0.59
    72.67
    -0.04
    Gan-Cao
  
  
    GC139
    Glycyrin
    66056-18-6
    0.47
    52.61
    -0.13
    Gan-Cao
  
  
    GC045
    Glycyrol
    23013-84-5
    0.67
    90.78
    -0.20
    Gan-Cao
  
  
    GC096
    Glypallichalcone
    146763-58-8
    0.19
    61.60
    0.23
    Gan-Cao
  
  
    GC167
    Glyzaglabrin
    65242-64-0
    0.35
    61.07
    -0.20
    Gan-Cao
  
  
    FL024
    Hederagenin
    465-99-6
    0.75
    36.91
    0.96
    Fu-Ling
  
  
    GC243
    Icos-5-enoic acid
    7329-42-2
    0.20
    30.70
    1.09
    Gan-Cao
  
  
    GC034
    Inermine
    2035-15-6
    0.54
    75.18
    0.40
    Gan-Cao
  
  
    GC239
    Inflacoumarin A
    158446-33-4
    0.33
    39.71
    -0.24
    Gan-Cao
  
  
    GC204
    Isobavachin
    31524-62-6
    0.32
    36.57
    -0.04
    Gan-Cao



Table 1: The active ingredients and ADME parameters of DZXYS.

Table 1 off 1 :




  
    GC216
    Isoformononetin
    486-63-5
    0.21
    38.37
    0.25
    Gan-Cao
  
  
    GC207
    Isoglycyrol
    23013-86-7
    0.84
    44.70
    0.05
    Gan-Cao
  
  
    ZZ063
    Isoimperatorin
    482-45-1
    0.23
    45.46
    0.66
    Zhi-Zi
  
  
    GC076
    Isotrifoliol
    329319-08-6
    0.42
    31.94
    -0.25
    Gan-Cao
  
  
    GC008
    Jaranol
    3301-49-3
    0.29
    50.83
    -0.22
    Gan-Cao
  
  
    GC077
    Kanzonol B
    - 
    0.35
    39.62
    -0.12
    Gan-Cao
  
  
    GC246
    Kanzonol F
    - 
    0.89
    32.47
    0.56
    Gan-Cao
  
  
    GC099
    Kanzonol U
    178330-48-8
    0.38
    58.44
    0.34
    Gan-Cao
  
  
    GC082
    Kanzonol W
    184584-82-5
    0.52
    50.48
    0.04
    Gan-Cao
  
  
    GC261
    Licoagrocarpin
    202815-29-0
    0.58
    58.81
    0.61
    Gan-Cao
  
  
    GC270
    Licoagroisoflavone
    - 
    0.49
    57.28
    0.09
    Gan-Cao
  
  
    GC110
    Licoarylcoumarin
    125709-31-1
    0.43
    59.62
    -0.23
    Gan-Cao
  
  
    GC022
    Licochalcone a
    58749-22-7
    0.29
    40.79
    -0.21
    Gan-Cao
  
  
    GC109
    Licochalcone G
    1261240-29-

      2
    0.32
    49.25
    -0.04
    Gan-Cao
  
  
    GC142
    Licocoumarone
    118524-14-4
    0.36
    33.21
    0.06
    Gan-Cao
  
  
    GC145
    Licoisoflavanone
    66067-26-3
    0.54
    52.47
    -0.22
    Gan-Cao
  
  
    GC143
    Licoisoflavone
    66056-19-7
    0.42
    41.61
    -0.27
    Gan-Cao
  
  
    GC144
    Licoisoflavone B
    66056-30-2
    0.55
    38.93
    -0.18
    Gan-Cao
  
  
    GC115
    Licoricone
    51847-92-8
    0.47
    63.58
    -0.14
    Gan-Cao
  
  
    CH122
    Linoleyl acetate
    5999-95-1
    0.20
    42.10
    1.08
    Chai-Hu
  
  
    GC040
    Liquiritigenin
    578-86-9
    0.18
    32.76
    -0.29
    Gan-Cao
  
  
    CH230
    Longikaurin A
    75207-67-9
    0.53
    47.72
    0.09
    Chai-Hu
  
  
    GC054
    Lupiwighteone
    104691-86-3
    0.37
    51.64
    -0.23
    Gan-Cao
  
  
    ZZ044
    Mandenol
    544-35-4
    0.19
    42.00
    1.14
    Zhi-Zi
  
  
    GC047
    Medicarpin
    607363-34-8
    0.34
    49.22
    0.53
    Gan-Cao
  
  
    CH234
    Octalupine
    6809-89-8
    0.28
    47.82
    0.30
    Chai-Hu
  
  
    GC274
    Odoratin
    53948-00-8
    0.30
    49.95
    -0.24
    Gan-Cao
  
  
    GC275
    Phaseol
    88478-02-8
    0.58
    78.77
    -0.06
    Gan-Cao
  
  
    GC094
    Phaseolinisoflavan
    40323-57-7
    0.45
    32.01
    0.46
    Gan-Cao
  
  
    GC050
    Pinocembrin
    480-39-7
    0.18
    64.72
    0.12
    Gan-Cao
  
  
    CH249
    Sainfuran
    90664-32-7
    0.23
    79.91
    0.23
    Chai-Hu
  
  
    GC067
    Shinflavanone
    157414-03-4
    0.72
    31.79
    0.25
    Gan-Cao
  
  
    GC151
    Shinpterocarpin
    157414-04-5
    0.73
    80.30
    0.68
    Gan-Cao
  
  
    CH051
    Stigmasterol
    83-48-7
    0.76
    43.83
    1.00
    Chai-Hu
  
  
    DG026
    Stigmasterol
    83-48-7
    0.76
    43.83
    1.00
    Dang-Gui
  
  
    ZZ020
    Stigmasterol
    83-48-7
    0.76
    43.83
    1.00
    Zhi-Zi
  
  
    ZZ083
    Sudan III
    85-86-9
    0.59
    84.07
    0.10
    Zhi-Zi
  
  
    ZZ046
    Supraene
    111-02-4
    0.42
    33.55
    1.73
    Zhi-Zi
  
  
    FL004
    Trametenolic acid
    24160-36-9
    0.80
    38.71
    -0.14
    Fu-Ling
  
  
    GC023
    Vestitol
    20879-05-4
    0.21
    74.66
    0.30
    Gan-Cao
  
  
    GC276
    Xambioona
    82345-36-6
    0.87
    54.85
    0.52
    Gan-Cao
  
  
    BZ011
    a-Amyrin
    638-95-9
    0.76
    39.51
    1.28
    Bai-Zhu
  
  
    CH318
    a-Spinasterol
    481-18-5
    0.76
    42.98
    0.79
    Chai-Hu
  
  
    BZ026
    Atractylenolide I
    73069-13-3
    0.15
    37.37
    1.29
    Bai-Zhu
  
  
    BZ029
    Atractylone
    6989-21-5
    0.13
    41.10
    1.85
    Bai-Zhu
  
  
    FL017
    Pachymic acid
    29070-92-6
    0.81
    33.63
    -0.57
    Fu-Ling
  
  
    DG022
    Ferulic acid
    537-98-4
    0.06
    39.56
    -0.03
    Dang-Gui
  
  
    MDP017
    Paeonol
    552-41-0
    0.04
    28.79
    0.84
    Mu-Dan-Pi
  
  
    BS068
    Paeoniflorin
    23180-57-6
    0.79
    53.87
    -1.86
    Bai-Shao
  
  
    MDP022
    Paeoniflorin
    23180-57-6
    0.79
    53.87
    -1.86
    Mu-Dan-Pi
  
  
    BS071
    Albiflorin
    39011-90-0
    0.77
    12.09
    -2.19
    Bai-Shao
  
  
    DG056
    (Z)-Ligustilide
    4431-01-0
    0.07
    51.30
    1.24
    Dang-Gui
  
  
    ZZ080
    Geniposide
    24512-63-8
    0.44
    14.64
    -2.61
    Zhi-Zi
  
  
    CH240
    Saikosaponin a
    20736-09-8
    0.09
    32.39
    -2.93
    Chai-Hu
  
  
    CH242
    Saikosaponin D
    20874-52-6
    0.09
    34.39
    -2.89
    Chai-Hu
  
  
    GC066
    Enoxolone
    471-53-4
    0.74
    22.05
    -0.53
    Gan-Cao
  
  
    GC136
    Glycyrrhizic acid
    1405-86-3
    0.11
    19.62
    -2.86
    Gan-Cao



Table 1 off 1:

11 active molecules. In addition, Bai-Shao, Bai-Zhu, Mu-Dan-Pi, Dang-Gui and Bai-Shao contained 7, 6, 5, 4 and 4 active ingredients, respectively.

Target Identification and Gene Ontology Enrichment Analysis

To further decode the therapeutic targets of DZXYS, a comprehensive range of target identification was provided. As a result, 431 targets were collected for 119 active ingredients, while only one compound (octalupine, CH234) had no related target protein. In order to focus on depression-related genes, 850 depression-related targets were collected based on the search engine results from four gene-disease databases. And then 431 targets and 119 active compounds of DZXYS were mapped to these 850 depression-related targets to build the connections with depression. Finally, 111 active compounds of DZXYS were identified interacting with 112 depression-related proteins (as displayed in Table S2).

As shown in Table S2, the overwhelming majority of those active ingredients (105 out of 111 compounds) were connected with more than one target proteins, displaying their multiple mechanisms of action. For example, ferulic acid, the main active compound of Dang-Gui, not only inhibited MAOA selectively [45], but also prevented the activity of ornithine decarboxylase (ODC1) by 46% [46]. Glycyrrhizic acid, which is the major sweet-tasting ingredient of Gan-Cao, not only suppressed the activity of caspase-3 (CASP3) [47], but also inhibited corticosteroid 11-beta-dehydrogenase isozyme 1 (HSD11B1) activity in rat [48]. Paeoniflorin, the major active compound of Bai-Shao and Mu-Dan-Pi, exerted a neuroprotective effect through activating adenosine receptor A1 (ADORA1) in rat [49], and also inhibited TNF (tumor necrosis factor), IL6 (Interleukin-6) to improve the cardiac function in rat model with ventricular remodeling [50]. Enoxolone, also called as glycyrrhetinic acid, was a pentacyclic triterpenoid derivative of Gan-Cao, and inhibited the expression of cytochrome P450 2E1 (CYP2E1) to attenuate the acetaminophen-induced liver injury in mice [51]. Additionally, as the major active ingredient of Zhi-Zi, geniposide upregulated HMOX1 (heme oxygenase 1) expression to improve the capacity of anti-oxidant effect in primary hippocampal neurons [52]. All these results documented that the bioactivity compounds in herbal medicines exhibited the promiscuous actions.

In order to explore the underlying molecular mechanism of these 112 targets DZXYS, GO enrichment analysis, including biological process, molecular function, and cellular component were carried out. As shown in Figure 2A, the top 5 enriched GO molecular processes included G protein-coupled amine receptor activity, regulation of blood vessel diameter, cellular response to catecholamine stimulus, chemical synaptic transmission, postsynaptic, and neurotransmitter biosynthetic process, which have been suggested to implicate in the pathological mechanism of depression. For example, G protein-coupled amine receptor, which is the largest human membrane protein family, is involved in numerous physiological functions such as parasympathetic and

Figure 2: GO enrichment analysis for the biological process (A), molecular function (B) and cellular component (C) of 112 depression-related targets of DZXYS. The nodes show the representative- enriched GO terms.

    
    
    Figure 2: GO enrichment analysis for the biological process (A), molecular function (B) and cellular component (C) of 112 depression-related targets of DZXYS. The nodes show the representative- enriched GO terms.

sympathetic nervous functions, immune regulation and metabolism, and has been found to be major therapeutic targets in various human diseases like psychiatric diseases and neurodegeneration [53].

In term of GO molecular function (Figure 2B), the candidate chemicals were mainly enriched in postsynaptic neurotransmitter receptor activity, G protein-coupled amine receptor activity, and steroid hormone receptor binding, etc. These molecular functions are linked with the pathological pathways of depression. For example, anti-depression drugs, such as Selective Serotonin Reuptake Inhibitors (SSRIs), Tricyclic Antidepressants (TCA), and Serotonin–Norepinephrine Reuptake Inhibitors (SNRIs), primarily inhibited the reuptake of monoamine neurotransmitters (like dopamine, noradrenaline, and serotonin) in an attempt to enhance the persistence of these neurotransmitters in the synaptic space to trigger postsynaptic neurotransmission receptors [54,55]. For GO cellular component (Figure 2C), the major enriched GO ontologies were post-synapse, membrane raft, dendritic spine, and so on, which are closely related with depressive disease. For example, the postsynaptic release of endocannabinoids played an important role in long-term depression in striatum [56].

Network Analysis to Explore the Therapeutic Mechanisms of DZXYS

Compound-Target network analysis: Modulation of Neurotransmitter Systems Plenty of experimental and clinical studies documented that neurotransmitter systems play the fundamental roles in the pathological mechanism of depression [57,58]. Actually, the petroleum ether soluble fraction and water-EtOH soluble fraction of DZXYS displayed anti-depressive effects through regulating the monoamine neurotransmitters (like 5-HT, dopamine and noradrenaline) and amino acid neurotransmitters in the hippocampus of rat models with Chronic

Unpredictable Mild Stress (CUMS) [59]. Therefore, the C-T network of DZXYS implicated in neurotransmitter systems was constructed as displayed in Figure 3.

Systems Pharmacology-Based Research on the Mechanism of Danzhi Xiaoyao San in the Treatment of Depression

Abstract

Introduction

Materials and Methods

Building the Compound Database of DZXYS

Active Compounds Screening

Target Fishing and Gene Ontology Enrichment Analysis

Network Construction and Analysis

Results and Discussion

Filtering Active Components from DZXYS

Target Identification and Gene Ontology Enrichment Analysis

Network Analysis to Explore the Therapeutic Mechanisms of DZXYS

Pathway Analysis of DZXYS

Conclusion

Author Statements

Acknowledgment

Conflict of Interest

References