Loading

Journal of Neurological Disorders and Stroke

Network Pharmacology-Based Pharmacological Mechanisms of Ginseng for Depression in Post-COVID 19

Research Article | Open Access

  • 0. Author contributed equally
  • 1. School of Pharmacy, Shandong University of Traditional Chinese Medicine, China
  • 2. National Oceanographic Center, China
  • 3. Experimental center, Shandong University of Traditional Chinese Medicine, China
  • 4. Shandong Provincial Collaborative Innovation Center for Quality Control and Construction of the whole Industrial Chain of Traditional Chinese Medicine, China
+ Show More - Show Less
Corresponding Authors
Chunchao Han, School of Pharmacy, Shandong University of Traditional Chinese Medicine, Jinan, 250355, People’s Republic of China, Tel: 86-531-82613129; Fax: 86-86-531-82613129
Abstract

Introduction: The novel coronavirus disease 2019 (COVID-19) is in the midst of worldwide panic and global health concern since December 2019. In order to provide theoretical guidance for further clinical application in post-pandemic, we investigated active compounds and pharmacological mechanisms of ginseng to exert anti-depressant activity using network pharmacology, and discussed the active ingredients with immune-regulation and anti-depression.

Materials and Methods: Information on compounds in ginseng was obtained from public databases, and genes related to depression were gathered using the Gene Cards database. Networks of ginseng-associated targets and depression-related genes were constructed through STRING database. Potential targets and pathway enrichment analysis related to the therapeutic efficacy of ginseng for depression were identified using Cytoscape and Database for Annotation, Visualization and Integrated Discovery (DAVID).

Results: Network pharmacological analysis of ginseng in treatment of depression identified 16 active ingredients, 47 potential targets, 32 GO terms, and 8 target generegulated major pathways. Among them, kaempferol, beta-sitosterol, stigmasterol, fumarine and frutinone A are bioactive compounds and key chemicals. Core genes in PPI network were AKT1, CASP3, NOS3, TNF, and PPARG. Ginseng relieves depression by affecting biological processes associated with neurotransmitters, neurotrophic factors, neurogenesis, HPA axis and inflammatory response, which are reciprocally connected with each other. More importantly, we found that frutinone A and kaempferol are key ingredients in ginseng with dual activities of immune-regulation and anti-depression.

Conclusion: Ginseng can regulate whole-body systems through a complex genes-interaction network, resulting in a certain effect on depression. This research demonstrates that ginseng is a preferable herb clinically in post-pandemic and network pharmacology approach can be an effective tool to reveal the mechanisms of traditional Chinese medicine from a holistic perspective.

Keywords

Depression, Ginseng, Network Pharmacology, Post-COVID-19

Citation

Wang N, Wang X, He M, Zheng W, Cai X, et al. (2022) Network Pharmacology-Based Pharmacological Mechanisms of Ginseng for Depression in Post-COVID 19. J Neurol Disord Stroke 9(2): 1196

INTRODUCTION

The novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus-2, is in the midst of worldwide panic and global health concern since December 2019 [1]. The most common symptoms of COVID-19 illness are fever, cough, and dyspnea [2]. In the most severe cases, people with poor immunity may develop pneumonia and multiple organ failure, eventually leading to death. However, no specific drug or vaccine has yet been developed and the epidemic will not be brought under positive control in the short term. To our knowledge, the onset of a sudden and immediately lifethreatening illness could lead to posttraumatic stress disorder [3]. Quarantine is necessary to manage the outbreak, and the experience of being quarantined can, in some cases, lead to longterm adverse mental health consequences [4]. Furthermore, many other economic problems caused by epidemic, such as financial difficulties and loss of employment, undoubtedly increased public anxiety and depression. Based on these, it is of great significance to prevent the outbreak of depression after a global epidemic while improving the public immunity.

Panax ginseng Meyer, as a precious tonic traditional Chinese medicine (TCM), usually grows in cooler areas like Northeast China, Korea peninsula and Russia. The Greek term “Panax”, which means “cure of all diseases”, implied its important position in the medical field. Ginseng can regulates each type of immune cells, therefore maintaining homeostasis of the immune system and enhancing resistance to illness or microbial attacks [5]. Quan et al., also found ginseng and salviae herbs play a role as immune activators during influenza virus infection [6]. As recorded in the traditional Chinese work, Jingyue Quanshu (Jing-yue’s Complete Works), ginseng has been used in the classic prescription Qifu Yin to treat neurasthenia and other nervous system diseases. Ginsenoside, as the main pharmacologically active components of ginseng, have been found to exhibit as novel antidepressant agents [7]. It can be seen that ginseng has a good effect on both immune-regulation and anti-depression. Hao et al., integrated metabolomics and network pharmacology to study the immuneregulation mechanism of ginseng [8]. However, its anti-depression therapeutic mechanisms have not yet been clearly elucidated. In order to provide guidance for clinical application in postpandemic, it is necessary to make clear the active ingredients and mechanism of ginseng’s antidepressant effect.

Network pharmacology has been introduced in recent years for exploring the molecular mechanisms of TCM. The key ideas of emerging network pharmacology and network biology shares much with the holistic philosophy of TCM, updating the research paradigm from the current “one target, one drug” mode to a new “network target, multi-components” mode [9]. Through bridging the emerging network science and ancient TCM, we obtain novel methodologies and opportunities for discovering bioactive ingredients and biomarkers, potentially revealing mechanisms of action. Even though the anti-depression effects of ginseng have been reported, network pharmacology-based prediction of the bioactive components and target pathways has not been performed.

In this study, we investigated pharmacological mechanisms of ginseng to exert anti-depressant activity using network pharmacology. The flowchart of the experimental procedures of our study is shown in Figure 1. We also discussed the active ingredients with immune-regulation and anti-depression, in order to provide theoretical guidance for further clinical application in post-pandemic (Figure 1).

Figure 1 The flowchart of the network pharmacology-based strategy for deciphering the mechanisms of ginseng on depression.

Figure 1: The flowchart of the network pharmacology-based strategy for deciphering the mechanisms of ginseng on depression.

MATERIALS AND METHODS

Database construction and ADME screening of ginseng ingredients

All of the known ingredients of ginseng were manually collected from related literature and phytochemical databases [10]: Traditional Chinese Medicine Systems Pharmacology Database (TCMSP, http://tcmspw.com/tcmsp.php). An in silico integrative model~ADME (absorption, distribution, metabolism, and excretion) was used to select the ingredients with favorable pharmacokinetics properties. The parameter used in this study included oral bioavailability (OB) and drug-likeness (DL). OB refers to the rate and degree of drug absorption into human circulation after oral administration and DL refers to the similarity of a compound to a known drug. They are two of the most commonly used pharmacokinetic properties in drug screening. Ingredients conforming to the requirements of both OB ≥30% and DL ≥0.18 were regarded as active ingredients in ginseng for further analysis.

Target genes related to the identified compounds

In the TCMSP database, the potantial targets of each active ingredient were found. The Uniprot data library (https://www. uniprot.org/) was used to convert the selected target into a gene name of Homo sapiens (Human) to prepare the target genes related to the identified compounds. Component-target data of ginseng were obtained after deleting the duplicates.

Collection of therapeutic targets of ginseng for depression

Information on depression-associated target genes was collected from the human gene database (Gene Cards, http:// www.genecards.org/) using “depression” as the keywords, and only “Homo sapiens” proteins linked to depression were selected. With relevance score > 7.32 as the threshold, the obtained targets were screened. In order to obtain the potential anti-depressant targets of ginseng, the targets of each active ingredient were intersected with depression-related targets through an online mapping platform (http: //bioinfo. Genotoul.fr/jvenn/example. html).

Protein-protein interaction data

The potential anti-depressant targets of ginseng were imported into the String database (http://stringdb.org/) for the analysis of protein-protein interaction (PPI). A confidence score above 0.4 indicates an interaction relationship. Therefore, the confidence was set as confidence > 0.4, while other parameters remained defaults.

Construction of the pharmacological networks

All visualized network models were established via Cytoscape 3.8.0 (http://www.cytoscape.org/), an open software package project for visualizing, integrating, modeling and analyzing the interaction networks [11]. In the network, nodes represent compounds or target genes, while edges represent the interactions between them. The “Network Analyze” in Cytoscape 3.8.0 is used to analyze the topology properties of the Network. Three networks were constructed: (1) Compound-compound target network. The potential targets of each active ingredient in ginseng were used to generate it; (2) Compound-target-disease network. The potential anti-depressant targets of ginseng were used to generate it; (3) PPI network of depression-related targets in ginseng.

Gene ontology and pathway enrichment analysis

The potential anti-depressant targets of ginseng was input into the Database for Annotation, Visualization and Integrated Discovery (DAVID, https://david.ncifcrf.gov/tools.jsp) for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Gene species and background were limited to human. The false discovery rate (FDR) < 0. 05 was used as the filter to obtain the top GO terms of biological process (BP), cell component (CC) and molecular function (MF). The enrichment analysis of KEGG metabolic pathway was screened under the conditions of P < 0.01 and FDR < 0.05. The results were visualized using Graphpad Prism 8.0.2 (https://www.graphpad.com/).

RESULTS

Candidate compound screening for ginseng

Retrieved from TCMSP, there were 190 components related to ginseng in total. Under the screening thresholds of OB ≥30% and DL ≥0.18, 22 active ingredients were selected for further analysis (Table 1). Among them, there are five active ingredients with higher OB: Celabenzine (101.88%), Aposiopolamine (66.65%), Frutinone A (65.9%), Inermin (65.83%) and Girinimbin (61.22%). These components play important roles in the pharmacological activities of ginseng. (Table 1).

Table 1: Active compounds and ADME parameters of ginseng (OB ≥30%, DL ≥0.18).
ID MOL ID Molecule Name OB(%) DL
RS1 MOL002879 Diop 43.59 0.39
RS2 MOL000449 Stigmasterol 43.83 0.76
RS3 MOL000358 Beta-sitosterol 36.91 0.75
RS4 MOL003648 Inermin 65.83 0.54
RS5 MOL000422 Kaempferol 41.88 0.24
RS6 MOL005308 Aposiopolamine 66.65 0.22
RS7 MOL005317 Deoxyharringtonine 39.27 0.81
RS8 MOL005318 Dianthramine 40.45 0.20
RS9 MOL005320 Arachidonate 45.57 0.20
RS10 MOL005321 Frutinone A 65.9 0.34
RS11 MOL005344 Ginsenoside Rh2 36.32 0.56
RS12 MOL005348 Ginsenoside Rh4 31.11 0.78
RS13 MOL005356 Girinimbin 61.22 0.31
RS14 MOL005376 Panaxadiol 33.09 0.79
RS15 MOL005384 Suchilactone 57.52 0.56
RS16 MOL005399 Alexandrin 36.91 0.75
RS17 MOL000787 Fumarine 59.26 0.83
RS18 MOL004492 Chrysanthemaxanthin 38.72 0.58
RS19 MOL005314 Celabenzine 101.88 0.49
RS20 MOL005357 Gomisin B 31.99 0.83
RS21 MOL005360 Malkangunin 57.71 0.63
RS22 MOL005401 Ginsenoside Rg5 39.56 0.79

Potential target prediction for ginseng

Among the 22 active components, 5 of them did not find corresponding targets, while the remaining 17 components obtained 109 potential targets after removing duplicates. All active compounds, their targets and the interactions between them are presented in the compound-compound target network (Figure 2), which is composed of 126 nodes (17 components and 109 targets) and 246 edges. The pink nodes represent drug targets while the blue nodes represent compounds, and the edges represent the interactions between them. Degree, a topological parameter describing the importance of a node, stands for the number of edges connecting to the node. We used it to further determine the importance of each active component. Through analysis, we found that RS5 exhibited the largest number of potential targets connections (Kaempferol, degree = 59), followed by RS3 (Beta-sitosterol, degree = 36), RS2 (Stigmasterol, degree = 31), RS17 (Fumarine, degree = 24) and RS4 (Inermin, degree = 16). The same active ingredient can act on different targets, and different active ingredients can also act on the same target, which fully reflects the multi-component, multi-target action characteristics of ginseng. (Figure 2).

Figure 2 Compound-compound target network. The size of the node is proportional to the value of the degree.

Figure 2: Compound-compound target network. The size of the node is proportional to the value of the degree.

Collection of therapeutic targets of ginseng for depression

A total of 11478 disease targets were obtained from GeneCards with “depression” as the keyword. Among them, 975 depression-related genes meet the requirement of relevance score > 7.32 and ginseng have 47 potential targets for depression (Figure 3a). Compound-target-disease network (Figure 3b) with 63 nodes and 102 edges linked 16 compounds and 47 target genes related to depression. Among the 16 candidate compounds, RS5 exhibited the largest number of potential anti-depression targets connections (Kaempferol, degree = 24), followed by RS3 (Betasitosterol, degree = 18), RS2 (Stigmasterol, degree = 14), RS17 (Fumarine, degree = 9) and RS10 (Frutinone A, degree = 8). For the 47 potential anti-depression targets, the network showed PTGS2 had the largest number of compound-target interactions, followed by SCN5A, GABRA1, CHRNA7 and SLC6A4, while the remaining 42 targets showed interactions with up to three compounds. (Figure 3).

Figure 3 (a) Venn diagram. (b) Compound-target-disease network with 63 nodes and 102 edges.

Figure 3: (a) Venn diagram. (b) Compound-target-disease network with 63 nodes and 102 edges.

Protein-protein interaction analysis

After removing a free target, the PPI network (Figure 4) contains 46 nodes and 259 edges, with average node degree of 11 and average local clustering coefficient of 0.533. Target size and color are used to reflect the degree, while edge thickness and color are used to reflect the combine score. The important targets were painted red and located centrally in the network. AKT1 (degree = 25), CASP3 (degree = 20), NOS3 (degree = 19), TNF (degree = 19), PPARG (degree = 18), SLC6A4 (degree = 18), ACHE (degree = 18), IL1B (degree = 17), PTGS2 (degree = 17) and MAOA (degree = 16) were the top ten genes regarding their degree. AKT1 also has the highest closeness centrality (0.67), indicating the faster the signal is transferred to other nodes. Due to the highest betweenness centrality (0.14), AKT1 is considered a bottleneck node in monopolistic position between modules in the network and more suitable as a therapeutic target. (Figure 4).

Figure 4 PPI network of depression-related targets in ginseng.

Figure 4: PPI network of depression-related targets in ginseng.

GO biological process and KEGG pathway enrichment analysis

Through DAVID database, we obtained 305 GO terms (226 BP terms, 31 CC terms and 48 MF terms) and 68 pathways in total. With FDR < 0.05 as the screening condition, 32 GO terms (22 BP terms, 6 CC terms and 4 MF terms) were selected (Figure 5). The BP terms were mainly involved in neurotransmitters, neurotrophic factors, neurogenesis, HPA axis and inflammatory response. The processes were, in the aspect of neurotransmitters: insulin secretion (GO:0050796) and positive regulation of chemokine biosynthetic process (GO:0045080); in the aspect of neurotrophic factors: positive regulation of ERK1 and ERK2 cascade (GO:0070374); in the aspect of neurogenesis: positive regulation of cell proliferation (GO:0008284), insulin secretion (GO:0050796), angiogenesis (GO:0045766) and negative regulation of calcium ion transport (GO:0051926); in the aspect of HPA axis: lipopolysaccharide-mediated signaling (GO:0031663); in the aspect of inflammatory response: positive regulation of nitric oxide biosynthetic process (GO:0045429), lipopolysaccharide-mediated signaling (GO:0031663), positive regulation of chemokine biosynthetic process (GO:0045080) and response to hypoxia (GO:0001666). The 6 CC terms were involved in plasma membrane (GO:0005886), integral component of plasma membrane (GO:0005887), membrane raft (GO:0045121), neuron projection (GO:0043005), postsynaptic membrane (GO:0045211) and Caveola (GO:0005901). Among them, plasma membrane and integral component of plasma membrane accounted for the largest proportion, with 29 and 15 targets respectively. Depending on the outcomes of GO enrichment, the enriched molecular function ontologies were dominated by protein homodimerization activity (GO:0042803), enzyme binding (GO:0019899), heme binding (GO:0020037), extracellular ligand-gated ion channel activity (GO:0005230).

Figure 5 GO functional annotation analysis of 47 target genes were sorted according to FDR < 0. 05.

Figure 5: GO functional annotation analysis of 47 target genes were sorted according to FDR < 0. 05.

Under the conditions of P < 0.01 and FDR < 0.05 (Table 2), we found that pathways in neuroactive ligand-receptor interaction (hsa04080), African trypanosomiasis (hsa05143), HIF-1 signaling pathway (hsa04066), Leishmaniasis (hsa05140), Toxoplasmosis (hsa05145), Serotonergic synapse (hsa04726), Tuberculosis (hsa05152) and Malaria (hsa05144) are the interaction pathways that ginseng exerts combined antidepressant effects (Figure 5 and 6) (Table 2).

Figure 6 KEGG pathways analysis of 47 target genes were sorted according to P < 0.01 and FDR < 0.05.

Figure 6: KEGG pathways analysis of 47 target genes were sorted according to P < 0.01 and FDR < 0.05

Table 2: Functions of potential target genes based on KEGG pathway analysis.
Pathway ID Term Target genes Count
hsa04080 Neuroactive ligand-receptor interaction OPRM1, DRD1, GABRA2, GABRA1, CHRM2,GABRA5,DRA2A,ADRA1A, CHRNA7, NR3C1, OPRD1, HTR2A 12
hsa05143 African trypanosomiasis PRKCA,VCAM1,ICAM1, TNF, IFNG, IL1B 6
hsa04066 HIF-1 signaling pathway PRKCA,AKT1,HMOX1, BCL2, IFNG, NOS3, NOS2, INSR 8
hsa05140 Leishmaniasis TNF, PTGS2, IFNG, IL1B, NOS2, STAT1, TGFB1 7
hsa05145 Toxoplasmosis AKT1, CASP3, TNF, BCL2, IFNG, NOS2, STAT1, TGFB1 8
hsa04726 Serotonergic synapse PRKCA, CASP3, PTGS2, MAOA, SLC6A4, MAOB, HTR3A, HTR2A 8
hsa05152 Tuberculosis AKT1, CASP3, TNF, BCL2, IFNG, IL1B, NOS2, STAT1, TGFB1 9
hsa05144 Malaria VCAM1, ICAM1, TNF, IFNG, IL1B, TGFB1 6

 

DISCUSSION

Depression is a complex disorder with multiple etiologies including genetic, epigenetic, and environmental factors. All of the proposed pathophysiological mechanisms of depression are not separate but integrally related and interact bidirectionally [12]. First-line antidepressants, SSRIs (selective 5-HT reuptake inhibitors), were forced to stop taking due to its inhibition of gastrointestinal motility. Tricyclic antidepressants have a nonnegligible side effect on the heart and brain. Their therapeutic approaches are both single-target. TCM is characterized by multi-target, multi-pathway and low side effect. Multi-component therapy produces “synergies”, in which the combined effects are greater than the sum of the individual effects. To our knowledge, the anti-depression mechanisms of active ingredients from TCM can be summed up as following: increasing synaptic availability of monoamines [13], alleviation of the HPA axis dysfunctions [14], regulation of the cAMP signaling pathway[15], and caspases [16], and amelioration of the dysregulation of immune and inflammation [17]. Ginseng has been shown to be a precious herbal medicine with dual activities of immune-regulation and anti-depression. In this study, we investigated pharmacological mechanisms of ginseng to exert anti-depressant activity using network pharmacology.

The screened active components can be classified as flavonoids, saponins, sterols, organic acids and etc. Some nodes are more concentrated in the network than others [18]. We found that several key compounds, including kaempferol, beta-sitosterol, stigmasterol, fumarine and frutinone A, play dominant roles in this network. As the most common flavonoid, kaempferol has attracted much attention due to its anti-cancer, antiinflammatory, antioxidant, antibacterial and antiviral effects. Gao et al. have comfirmed that antidepressive effects of kaempferol are mediated by reduction of oxidative stress, proinflammatory cytokines and up-regulation of AKT/β-catenin cascade [19]. Stigmasterol has been found to exert neuro-protective effect through reduction of oxidative stress and inactivation of autophagy via AMPK/mTOR and JNK pathways [20]. It has been reported that β-sitosterol has protective effects on various brain-related diseases independent of their lipid-lowering effects. Moreover, β-sitosterol can also suppress the development of cerebral aneurysm by inhibiting inflammatory reactions including TNF-α [21]. This indicated that our prediction of the active ingredient in ginseng that plays an antidepressant role is reasonable. However, frutinone A are mostly considered as an active ingredient of the broad spectrum antimicrobial herbal extract up to now and antidepression may be its potential pharmacological activity that has not yet been discovered. As mentioned above, main compounds of ginseng on immune-regulation were selected by the network pharmacology analysis, including ginsenoside Re, ginsenoside Rg1, frutinone A, and kaempferol [8]. Through analysis, we found frutinone A and kaempferol are also the major ingredients in ginseng to exert anti-depressant activity. Therefore, these two ingredients are the key ingredients in ginseng with dual activities of immune-regulation and anti-depression.

In the PPI network, AKT1 has the highest degree, closeness centrality and betweenness centrality. It is in the monopolistic position between modules in the network and more suitable as a therapeutic target. AKT1, a downstream enzyme that has been implicated in the pathogenesis of serotonin-related disorders, facilitates growth factor-mediated cell survival and block apoptosis through the regulation of its downstream effector (GSK-3) in depressants [22-23]. Moreover, SLC6A4 is responsible for the serotonergic neurotransmission, which is an important substance that regulates neural activity. The serotonin-linked polymorphic region (5-HTTLPR) is a degenerate repetition of the gene encoding the 5-hydroxytryptamine transporter (SLC6A4). The S/S genotype in this region is associated with decreased serotonin expression and increased susceptibility to depression [12]. TNF and IL-1B may be involved in major depression not just by activating certain cascades of inflammation but also by many other mechanisms [24]. It is not difficult to see that ginseng’s treatment of depression involves neurotransmitters (especially serotonin), inflammation, neurotrophic factors and many other aspects. Furthermore, inflammatory cytokines have been shown to reduce monoamine levels in depressed patients by increasing the metabolism of tryptophan, an important precursor to serotonin [12]. It also reconfirmed the factors that influence depression are not separate but integrally related and interact bidirectionally. These results were consistent with our enrichment analysis, and have been previously reported to be related to depression.

GO analysis revealed that ginseng relieves depression by affecting biological processes associated with neurotransmitters, neurotrophic factors, neurogenesis, HPA axis and inflammatory response, which are reciprocally connected with each other (Figure 7). For example, inflammation leads to HPA hyperactivity and HPA hyperactivity in turn plays an adverse role in the inflammatory process, forming a vicious circle. The target genes were majorly associated with the biological process of response to drug, indicated the key requirement of avoiding drug dependence in depression drug development and clinical treatment [25]. Extracellular signal-regulated kinase 1/2 (ERK1/2) signaling, which belongs to the large family of mitogen-activated protein kinase signaling cascases, showed low activity in the frontal cortex (Brodmann 8, 9, 10) and hippocampus in depressed patients [26]. It has been shown to have significant effects on the regulation of long-term enhancement, long-term depression, and neuronal survival through neurotrophic/growth factors [27-28]. In recent years, more and more studies have proved that astrocytes not only have a supporting effect, but also regulate physiological processes by secreting neurotrophic factors. This suggests that ginseng can play a direct and indirect therapeutic role by acting on astrocytes or nerve cells. Intracellular Ca2+ accumulation or overload can lead to a series of neuronal injuries (neuronal degeneration, necrosis, and apoptosis) by the activation of CaMK signal transduction pathways. Angiogenesis is also closely related to neuronal regeneration. A variety of angiogenic factors, especially the vascular endothelial growth factor (VEGF), not only has effect on promoting angiogenesis, but also on the nerve nutrition and neurogenesis. Through negative regulation of calcium ion transport, positive regulation of angiogenesis and cell proliferation, ginseng promote neurogenesis, which is thought to contribute to anti-stress recovery and underlie the clinical efficacy of antidepressants [29]. Moreover, ginseng can regulate insulin secretion, and insulin in the nervous system is related to the growth of nerve cells and the release of neurotransmitters. Chemokines not only regulate neurotransmitters but also affect inflammation. In recent years, studies have shown an increasing link between depression and chemokines. Glucocorticoid is the main cytokine released by macrophages, and ginseng’s effect on lipopolysaccharide-mediated signaling is important to regulate inflammation and HPA axis dysfunction. Besides that, the positive regulation of ginseng in smooth muscle cell proliferation provides support for brain-smooth muscle axis hypothesis. The hypothesis holds that there is a bidirectional neuroendocrine pathway that regulates specific brain regions and smooth muscles through local CYP enzymes and endogenous active substances, thus alleviating depression. Furthermore, results showed the main cell component terms were involved in plasma membrane and integral component of plasma membrane, while protein homodimerization activity and enzyme binding dominated the enriched molecular function ontologies. (Figure 7)

Figure 7 Illustration of the crucial biological processes caused by putative targets and known therapeutic targets for depression..

Figure 7: Illustration of the crucial biological processes caused by putative targets and known therapeutic targets for depression.

In addition, KEGG pathway analysis were primarily pertaining to neuroactive ligand-receptor interaction, serotonergic synapse and HIF-1 signaling pathway, which followed the previous reports that these pathways participate in crucial functions in the progression and development of depression (Figure 8). It is worth mentioning that there were several pathways, which are concerned with diseases, such as African trypanosomiasis, Leishmaniasis, Toxoplasmosis, Tuberculosis, and Malaria, prompting that ginseng may have potential therapeutic efects on these diseases. Twelve targets enriched onto neuroactive ligand-receptor interaction pathway were mostly neurotransmitter receptors. Monoamine neurotransmitters (serotonin, norepinephrine and dopamine) have a potential role in the pathogenesis of depression and monoamine hypothesis explained how antidepressants work [30]. HIF-1 signaling pathway is associated with AKT, NF-κB signaling pathways and the transcription of VEGF, which interferes with inflammatory injury, oxidative stress, apoptosis and tumor growth. FG-4592 improves depressive-like behaviors through HIF-1-mediated neurogenesis and synapse plasticity in rats [31]. Taken together, these results indicate that ginseng can regulate whole-body systems through a complex genes-interaction network, resulting in a certain effect on depression (Figure 8).

Figure 8 The anti-depression pathway of ginseng. The blue nodes represent the targets of ginseng acting on the pathway. (a) HIF-1 signaling  pathway. (b) Serotonergic synapse. (c) Neuroactive ligand-receptor interaction.

Figure 8: The anti-depression pathway of ginseng. The blue nodes represent the targets of ginseng acting on the pathway. (a) HIF-1 signaling pathway. (b) Serotonergic synapse. (c) Neuroactive ligand-receptor interaction.

LIMITATIONS

In this study, due to the traffic restrictions because of the Coronavirus disease COVID-19-related pandemic, we were unable to perform experiment to validate the theoretical predictions. Further work should address these issues to improve the reliability of the results.

CONCLUSIONS

Past experience shows that mental health problems often occur in the public following a major epidemic. This study used a scientifc approach, network pharmacology, to decipher the pharmacological mechanisms of ginseng in the treatment of depression. We discovered that the therapeutic activities of ginseng for depression mainly involve neurotransmitters, neurotrophic factors, neurogenesis, HPA axis and inflammatory response, which are reciprocally connected with each other and implied these were involved in the underlying mechanisms of ginseng on depression. These findings could provide theoretical guidance in the investigation of ginseng for further clinical application in post-COVID-19. And network pharmacology approach can be an effective tool to reveal the mechanisms of traditional Chinese medicine from a holistic perspective.

FINANCIAL SUPPORT

The Project of Shandong Province Key Research and Development Program [Grant No. 2017YYSP030] supported this work. Traditional Chinese Medicine Resources and Utilization Innovation Team. Shandong Provincial Natural Science Foundation, China (No. ZR2017MH086). Major Science and Technology Innovation in Shandong Province [Grant No. 2017CXGC1307]. Key Laboratory of Classical Theory of Traditional Chinese Medicine, Ministry of Education. Shandong Provincial Key Laboratory of Traditional Chinese Medicine for Basic research.

REFERENCES

1. World Health Organization (WHO). Laboratory testing of 2019 novel coronavirus (2019-nCoV) in suspected human cases. 2020a.

2. Asadi-Pooya AA, Simani L. Central nervous system manifestations of COVID-19: A systematic review. J Neurol Sci. 2020; 413: 116832.

3. Wu KK, Chan SK, Ma TM. Posttraumatic stress, anxiety, and depression in survivors of severe acute respiratory syndrome (SARS). J Trauma Stress. 2005; 18: 39-42.

4. Liu X, Kakade M, Fuller CJ, Fan B, Fang Y, Kong J, et al. Depression after exposure to stressful events: lessons learned from the severe acute respiratory syndrome epidemic. Compr Psychiatry. 2012; 53: 15-23.

5. Kang S, Min H. Ginseng, the ‘Immunity Boost’: The Effects of Panax ginseng on Immune System. J Ginseng Res. 2012; 36: 354?368.

6. Quan FS, Compans RW, Cho YK, Kang SM. Ginseng and Salviae herbs play a role as immune activators and modulate immune responses during influenza virus infection. Vaccine. 2007; 25: 272?282.

7. Wang YS, Shen CY, Jiang JG. Antidepressant active ingredients from herbs and nutraceuticals used in TCM: pharmacological mechanisms and prospects for drug discovery. Pharmacol Res. 2019; 150: 104520.

8. Hao J, Hu H, Liu J, Wang X, Liu X, Wang J, et al. Integrated Metabolomics and Network Pharmacology Study on Immunoregulation Mechanisms of Panax ginseng through Macrophages. Evid Based Complement Alternat Med. 2019; 2019: 3630260.

9. Li S, Zhang B. Traditional Chinese medicine network pharmacology: theory, methodology and application. Chin J Nat Med. 2013; 11: 110-120.

10. Jinlong Ru, Peng Li, Jinan Wang, Wei Zhou, Bohui Li, Chao Huang, et al. TCMSP: a database of systems pharmacology for drug discovery from herbal medicines. J Cheminform. 2014; 6: 13.

11. Li L, Qiu H, Liu M, Cai Y. A Network Pharmacology-Based Study of the Molecular Mechanisms of Shaoyao-Gancao Decoction in Treating Parkinson’s Disease. Interdiscip Sci. 2020; 12: 131-144.

12. Dean J, Keshavan M. The neurobiology of depression: An integrated view. Asian J Psychiatr. 2017; 27: 101-111.

13. Delgado PL. Depression: the case for a monoamine deficiency. J Clin Psychiatry. 2000; 61: 7-11.

14. Ott V, Friedrich M, Prilop S, Lehnert H, Jauch-Chara K, Born J, et al. Food anticipation and subsequent food withdrawal increase serum cortisol in healthy men. Physiol Behav. 2011; 103: 594-599.

15. Castrén E, Rantamäki T. The role of BDNF and its receptors in depression and antidepressant drug action: Reactivation of developmental plasticity. Dev Neurobiol. 2010; 70: 289-297.

16. Coyle JT, Duman RS. Finding the intracellular signaling pathways affected by mood disorder treatments. Neuron. 2003; 38: 157-160.

17. Shalini S, Dorstyn L, Dawar S, Kumar S. Old, new and emerging functions of caspases. Cell Death Differ. 2015; 22: 526-539.

18. Hong M, Zhang Y, Li S, Tan HY, Wang N, Mu S, et al. A Network Pharmacology-Based Study on the Hepatoprotective Effect of Fructus Schisandrae. Molecules. 2017; 22: 1617.

19. Gao W, Wang W, Peng Y, Deng Z. Antidepressive effects of kaempferol mediated by reduction of oxidative stress, proinflammatory cytokines and up-regulation of AKT/β-catenin cascade. Metab Brain Dis. 2019; 34: 485-494.

20. Sun J, Li X, Liu J, Pan X, Zhao Q. Stigmasterol Exerts Neuro-Protective Effect Against Ischemic/Reperfusion Injury through Reduction of Oxidative Stress and Inactivation of Autophagy. Neuropsychiatr Dis Treat. 2019; 15: 2991-3001.

21. Yang Q, Yu D, Zhang Y. β-Sitosterol Attenuates the Intracranial Aneurysm Growth by Suppressing TNF-α-Mediated Mechanism. Pharmacology. 2019; 104: 303-311.

22. Pereira PA, Bicalho MA, de Moraes EN, Leandro Malloy-Diniz, Isadora Cristine Reis Sguizzato Bozzi, Rodrigo Nicolato, et al. Genetic variant of AKT1 and AKTIP associated with late-onset depression in a Brazilian population. Int J Geriatr Psychiatry. 2014; 29: 399-405.

23.Wang YS, Shen CY, Jiang JG. Antidepressant active ingredients from herbs and nutraceuticals used in TCM: pharmacological mechanisms and prospects for drug discovery. Pharmacol Res. 2019; 150: 104520.

24. Schmidt FM, Koch J, Nowak C, Holdt LM, Teupser D, Hegerl U, et al. Ligands and receptors of the TNF superfamily are decreased in major depression and during early antidepressant therapy. J Psychiatr Res. 2019; 119: 116?121.

25. Liu Y, Fan P, Zhang S, Wang Y, Liu D. Prioritization and comprehensive analysis of genes related to major depressive disorder. Mol Genet Genomic Med. 2019; 7: e659.

26. Dwivedi Y, Rizavi HS, Roberts RC, Conley RC, Tamminga CA, Pandey GN. Reduced activation and expression of ERK1/2 MAP kinase in the post-mortem brain of depressed suicide subjects. J Neurochem. 2001; 77: 916-928.

27. Dwivedi Y, Rizavi HS, Zhang H, Roberts RC, Conley RR, Pandey GN. Aberrant extracellular signal-regulated kinase (ERK)1/2 signalling in suicide brain: role of ERK kinase 1 (MEK1). Int J Neuropsychopharmacol. 2009; 12: 1337-1354.

28. Giovannini MG. The role of the extracellular signal-regulated kinase pathway in memory encoding. Rev Neurosci. 2006; 17: 619-634.

29. Kraus C, Castrén E, Kasper S, Lanzenberger R. Serotonin and neuroplasticity–links between molecular, functional and structural pathophysiology in depression. Neurosci Biobehav Rev 2017; 77: 317–26.

30. Numakawa T, Suzuki S, Kumamaru E, Adachi N, Richards M, Kunugi H. BDNF function and intracellular signaling in neurons. Histol Histopathol. 2010; 25: 237-258.

31. Malhi GS, Mann JJ. Depression. Lancet. 2018; 392: 2299-2312

Wang N, Wang X, He M, Zheng W, Cai X, et al. (2022) Network Pharmacology-Based Pharmacological Mechanisms of Ginseng for Depression in Post-COVID 19. J Neurol Disord Stroke 9(2): 1196.

Received : 15 Jun 2022
Accepted : 29 Dec 2022
Published : 30 Dec 2022
Journals
Annals of Otolaryngology and Rhinology
ISSN : 2379-948X
Launched : 2014
JSM Schizophrenia
Launched : 2016
Journal of Nausea
Launched : 2020
JSM Internal Medicine
Launched : 2016
JSM Hepatitis
Launched : 2016
JSM Oro Facial Surgeries
ISSN : 2578-3211
Launched : 2016
Journal of Human Nutrition and Food Science
ISSN : 2333-6706
Launched : 2013
JSM Regenerative Medicine and Bioengineering
ISSN : 2379-0490
Launched : 2013
JSM Spine
ISSN : 2578-3181
Launched : 2016
Archives of Palliative Care
ISSN : 2573-1165
Launched : 2016
JSM Nutritional Disorders
ISSN : 2578-3203
Launched : 2017
Annals of Neurodegenerative Disorders
ISSN : 2476-2032
Launched : 2016
Journal of Fever
ISSN : 2641-7782
Launched : 2017
JSM Bone Marrow Research
ISSN : 2578-3351
Launched : 2016
JSM Mathematics and Statistics
ISSN : 2578-3173
Launched : 2014
Journal of Autoimmunity and Research
ISSN : 2573-1173
Launched : 2014
JSM Arthritis
ISSN : 2475-9155
Launched : 2016
JSM Head and Neck Cancer-Cases and Reviews
ISSN : 2573-1610
Launched : 2016
JSM General Surgery Cases and Images
ISSN : 2573-1564
Launched : 2016
JSM Anatomy and Physiology
ISSN : 2573-1262
Launched : 2016
JSM Dental Surgery
ISSN : 2573-1548
Launched : 2016
Annals of Emergency Surgery
ISSN : 2573-1017
Launched : 2016
Annals of Mens Health and Wellness
ISSN : 2641-7707
Launched : 2017
Journal of Preventive Medicine and Health Care
ISSN : 2576-0084
Launched : 2018
Journal of Chronic Diseases and Management
ISSN : 2573-1300
Launched : 2016
Annals of Vaccines and Immunization
ISSN : 2378-9379
Launched : 2014
JSM Heart Surgery Cases and Images
ISSN : 2578-3157
Launched : 2016
Annals of Reproductive Medicine and Treatment
ISSN : 2573-1092
Launched : 2016
JSM Brain Science
ISSN : 2573-1289
Launched : 2016
JSM Biomarkers
ISSN : 2578-3815
Launched : 2014
JSM Biology
ISSN : 2475-9392
Launched : 2016
Archives of Stem Cell and Research
ISSN : 2578-3580
Launched : 2014
Annals of Clinical and Medical Microbiology
ISSN : 2578-3629
Launched : 2014
JSM Pediatric Surgery
ISSN : 2578-3149
Launched : 2017
Journal of Memory Disorder and Rehabilitation
ISSN : 2578-319X
Launched : 2016
JSM Tropical Medicine and Research
ISSN : 2578-3165
Launched : 2016
JSM Head and Face Medicine
ISSN : 2578-3793
Launched : 2016
JSM Cardiothoracic Surgery
ISSN : 2573-1297
Launched : 2016
JSM Bone and Joint Diseases
ISSN : 2578-3351
Launched : 2017
JSM Bioavailability and Bioequivalence
ISSN : 2641-7812
Launched : 2017
JSM Atherosclerosis
ISSN : 2573-1270
Launched : 2016
Journal of Genitourinary Disorders
ISSN : 2641-7790
Launched : 2017
Journal of Fractures and Sprains
ISSN : 2578-3831
Launched : 2016
Journal of Autism and Epilepsy
ISSN : 2641-7774
Launched : 2016
Annals of Marine Biology and Research
ISSN : 2573-105X
Launched : 2014
JSM Health Education & Primary Health Care
ISSN : 2578-3777
Launched : 2016
JSM Communication Disorders
ISSN : 2578-3807
Launched : 2016
Annals of Musculoskeletal Disorders
ISSN : 2578-3599
Launched : 2016
Annals of Virology and Research
ISSN : 2573-1122
Launched : 2014
JSM Renal Medicine
ISSN : 2573-1637
Launched : 2016
Journal of Muscle Health
ISSN : 2578-3823
Launched : 2016
JSM Genetics and Genomics
ISSN : 2334-1823
Launched : 2013
JSM Anxiety and Depression
ISSN : 2475-9139
Launched : 2016
Clinical Journal of Heart Diseases
ISSN : 2641-7766
Launched : 2016
Annals of Medicinal Chemistry and Research
ISSN : 2378-9336
Launched : 2014
JSM Pain and Management
ISSN : 2578-3378
Launched : 2016
JSM Women's Health
ISSN : 2578-3696
Launched : 2016
Clinical Research in HIV or AIDS
ISSN : 2374-0094
Launched : 2013
Journal of Endocrinology, Diabetes and Obesity
ISSN : 2333-6692
Launched : 2013
Journal of Substance Abuse and Alcoholism
ISSN : 2373-9363
Launched : 2013
JSM Neurosurgery and Spine
ISSN : 2373-9479
Launched : 2013
Journal of Liver and Clinical Research
ISSN : 2379-0830
Launched : 2014
Journal of Drug Design and Research
ISSN : 2379-089X
Launched : 2014
JSM Clinical Oncology and Research
ISSN : 2373-938X
Launched : 2013
JSM Bioinformatics, Genomics and Proteomics
ISSN : 2576-1102
Launched : 2014
JSM Chemistry
ISSN : 2334-1831
Launched : 2013
Journal of Trauma and Care
ISSN : 2573-1246
Launched : 2014
JSM Surgical Oncology and Research
ISSN : 2578-3688
Launched : 2016
Annals of Food Processing and Preservation
ISSN : 2573-1033
Launched : 2016
Journal of Radiology and Radiation Therapy
ISSN : 2333-7095
Launched : 2013
JSM Physical Medicine and Rehabilitation
ISSN : 2578-3572
Launched : 2016
Annals of Clinical Pathology
ISSN : 2373-9282
Launched : 2013
Annals of Cardiovascular Diseases
ISSN : 2641-7731
Launched : 2016
Journal of Behavior
ISSN : 2576-0076
Launched : 2016
Annals of Clinical and Experimental Metabolism
ISSN : 2572-2492
Launched : 2016
Clinical Research in Infectious Diseases
ISSN : 2379-0636
Launched : 2013
JSM Microbiology
ISSN : 2333-6455
Launched : 2013
Journal of Urology and Research
ISSN : 2379-951X
Launched : 2014
Journal of Family Medicine and Community Health
ISSN : 2379-0547
Launched : 2013
Annals of Pregnancy and Care
ISSN : 2578-336X
Launched : 2017
JSM Cell and Developmental Biology
ISSN : 2379-061X
Launched : 2013
Annals of Aquaculture and Research
ISSN : 2379-0881
Launched : 2014
Clinical Research in Pulmonology
ISSN : 2333-6625
Launched : 2013
Journal of Immunology and Clinical Research
ISSN : 2333-6714
Launched : 2013
Annals of Forensic Research and Analysis
ISSN : 2378-9476
Launched : 2014
JSM Biochemistry and Molecular Biology
ISSN : 2333-7109
Launched : 2013
Annals of Breast Cancer Research
ISSN : 2641-7685
Launched : 2016
Annals of Gerontology and Geriatric Research
ISSN : 2378-9409
Launched : 2014
Journal of Sleep Medicine and Disorders
ISSN : 2379-0822
Launched : 2014
JSM Burns and Trauma
ISSN : 2475-9406
Launched : 2016
Chemical Engineering and Process Techniques
ISSN : 2333-6633
Launched : 2013
Annals of Clinical Cytology and Pathology
ISSN : 2475-9430
Launched : 2014
JSM Allergy and Asthma
ISSN : 2573-1254
Launched : 2016
Annals of Sports Medicine and Research
ISSN : 2379-0571
Launched : 2014
JSM Sexual Medicine
ISSN : 2578-3718
Launched : 2016
Annals of Vascular Medicine and Research
ISSN : 2378-9344
Launched : 2014
JSM Biotechnology and Biomedical Engineering
ISSN : 2333-7117
Launched : 2013
Journal of Hematology and Transfusion
ISSN : 2333-6684
Launched : 2013
JSM Environmental Science and Ecology
ISSN : 2333-7141
Launched : 2013
Journal of Cardiology and Clinical Research
ISSN : 2333-6676
Launched : 2013
JSM Nanotechnology and Nanomedicine
ISSN : 2334-1815
Launched : 2013
Journal of Ear, Nose and Throat Disorders
ISSN : 2475-9473
Launched : 2016
JSM Ophthalmology
ISSN : 2333-6447
Launched : 2013
Journal of Pharmacology and Clinical Toxicology
ISSN : 2333-7079
Launched : 2013
Annals of Psychiatry and Mental Health
ISSN : 2374-0124
Launched : 2013
Medical Journal of Obstetrics and Gynecology
ISSN : 2333-6439
Launched : 2013
Annals of Pediatrics and Child Health
ISSN : 2373-9312
Launched : 2013
JSM Clinical Pharmaceutics
ISSN : 2379-9498
Launched : 2014
JSM Foot and Ankle
ISSN : 2475-9112
Launched : 2016
JSM Alzheimer's Disease and Related Dementia
ISSN : 2378-9565
Launched : 2014
Journal of Addiction Medicine and Therapy
ISSN : 2333-665X
Launched : 2013
Journal of Veterinary Medicine and Research
ISSN : 2378-931X
Launched : 2013
Annals of Public Health and Research
ISSN : 2378-9328
Launched : 2014
Annals of Orthopedics and Rheumatology
ISSN : 2373-9290
Launched : 2013
Journal of Clinical Nephrology and Research
ISSN : 2379-0652
Launched : 2014
Annals of Community Medicine and Practice
ISSN : 2475-9465
Launched : 2014
Annals of Biometrics and Biostatistics
ISSN : 2374-0116
Launched : 2013
JSM Clinical Case Reports
ISSN : 2373-9819
Launched : 2013
Journal of Cancer Biology and Research
ISSN : 2373-9436
Launched : 2013
Journal of Surgery and Transplantation Science
ISSN : 2379-0911
Launched : 2013
Journal of Dermatology and Clinical Research
ISSN : 2373-9371
Launched : 2013
JSM Gastroenterology and Hepatology
ISSN : 2373-9487
Launched : 2013
TEST Journal of Dentistry
ISSN : 1234-5678
Launched : 2014
Annals of Nursing and Practice
ISSN : 2379-9501
Launched : 2014
JSM Dentistry
ISSN : 2333-7133
Launched : 2013
Author Information X