scholarly journals The Methodological Trends of Traditional Herbal Medicine Employing Network Pharmacology

Biomolecules ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 362 ◽  
Author(s):  
Won-Yung Lee ◽  
Choong-Yeol Lee ◽  
Youn-Sub Kim ◽  
Chang-Eop Kim
Keyword(s):  
Herbal Medicine ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Systems Pharmacology ◽  
Traditional Herbal Medicine ◽  
Affiliation Networks ◽  
Target Network ◽  
Analysis Platform ◽  
Combining Methods ◽  
Compound Target

Natural products, including traditional herbal medicine (THM), are known to exert their therapeutic effects by acting on multiple targets, so researchers have employed network pharmacology methods to decipher the potential mechanisms of THM. To conduct THM-network pharmacology (THM-NP) studies, researchers have employed different tools and databases for constructing and analyzing herb–compound–target networks. In this study, we attempted to capture the methodological trends in THM-NP research. We identified the tools and databases employed to conduct THM-NP studies and visualized their combinatorial patterns. We also constructed co-author and affiliation networks to further understand how the methodologies are employed among researchers. The results showed that the number of THM-NP studies and employed databases/tools have been dramatically increased in the last decade, and there are characteristic patterns in combining methods of each analysis step in THM-NP studies. Overall, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was the most frequently employed network pharmacology database in THM-NP studies. Among the processes involved in THM-NP research, the methodology for constructing a compound–target network has shown the greatest change over time. In summary, our analysis describes comprehensive methodological trends and current ideas in research design for network pharmacology researchers.

scholarly journals Systematic Elucidation of the Mechanism of Sappan Lignum in the Treatment of Diabetic Peripheral Neuropathy Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiaomin Kang ◽  
De Jin ◽  
Yuqing Zhang ◽  
Rongrong Zhou ◽  
Yuehong Zhang ◽  
...  
Keyword(s):  
Peripheral Neuropathy ◽  
Diabetic Peripheral Neuropathy ◽  
Target Prediction ◽  
Scientific Basis ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Physical And Mental Health ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Compound Target

Background. Diabetic peripheral neuropathy (DPN) is one of the most common chronic complications of diabetes, which seriously affects the physical and mental health of patients. Sappan Lignum (SL) is effective in treating DPN. Previous reports have shown that SL has a clear hypoglycemic and anti-inflammatory effect. However, the study of SL in the treatment of DPN is still limited and rare. Objective. To investigate the mechanism of SL in the treatment of DPN based on network pharmacology. Methods. The active ingredients of SL were screened by related databases. The compound targets were collected by the target prediction platforms. The DPN-related targets were gathered through disease databases. The intersection targets were obtained by uploading the compound targets and disease targets to Venny 2.1.0, and a compound-target network was constructed by Cytoscape3.7.2. The protein-protein interaction (PPI) relationships were obtained by the STRING11.0 database. Genome Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the DAVID6.8 database. Molecular docking of key compounds and core targets was performed by DockThor. Results. A total of 29 compounds and 51 intersection targets with potential therapeutic effects on DPN were obtained. The compound-target network construction resulted in four key compounds: protostemonine, 3-deoxysappanchalcone, 7,3′,4′-trihydroxy-3-benzyl-2H-chromene, and o-12′-methylergocornine. PPI network analysis yielded 10 core targets: AKT1, MAPK3, CXCL8, TNF, OPRM1, MTOR, STAT3, MAPK8, SIRT1, and HSP90AA1. KEGG analysis resulted in 82 signaling pathways ( P < 0.05 ), including insulin resistance, HIF-1 signaling pathway, and type II diabetes. The docking results indicated that the main active compounds could stably bind to core targets. Conclusion. SL had the mechanism of multiple ingredients, multiple targets, and multiple pathways in the treatment of DPN. This study provided a scientific basis for further research on the treatment of DPN with SL and its extracts.

Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

2019 ◽  
Vol 22 (6) ◽  
pp. 411-420 ◽  
Author(s):  
Xian-Jun Wu ◽  
Xin-Bin Zhou ◽  
Chen Chen ◽  
Wei Mao
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Pathway Enrichment ◽  
Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

scholarly journals Network Pharmacology-Based Study of the Underlying Mechanisms of Huangqi Sijunzi Decoction for Alzheimer’s Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wei Zhang ◽  
Mingti Lv ◽  
Yating Shi ◽  
Yonghui Mu ◽  
Zhaoyang Yao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neuroprotective Effect ◽  
Signalling Pathway ◽  
Signalling Pathways ◽  
Network Pharmacology ◽  
Neuroprotective Effects ◽  
Target Network ◽  
Compound Target

Background. Huangqi Sijunzi decoction (HQSJZD) is a commonly used conventional Chinese herbal medicine prescription for invigorating Qi, tonifying Yang, and removing dampness. Modern pharmacology and clinical applications of HQSJZD have shown that it has a certain curative effect on Alzheimer’s disease (AD). Methods. The active components and targets of HQSJZD were searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The genes corresponding to the targets were retrieved using UniProt and GeneCard database. The herb-compound-target network and protein-protein interaction (PPI) network were constructed by Cytoscape. The core targets of HQSJZD were analysed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The main active compounds of HQSJZD were docked with acetylcholinesterase (AChE). In vitro experiments were conducted to detect the inhibitory and neuroprotective effects of AChE. Results. Compound-target network mainly contained 132 compounds and 255 corresponding targets. The main compounds contained quercetin, kaempferol, formononetin, isorhamnetin, hederagenin, and calycosin. Key targets contained AChE, PTGS2, PPARG, IL-1B, GSK3B, etc. There were 1708 GO items in GO enrichment analysis and 310 signalling pathways in KEGG, mainly including the cAMP signalling pathway, the vascular endothelial growth factor (VEGF) signalling pathway, serotonergic synapses, the calcium signalling pathway, type II diabetes mellitus, arginine and proline metabolism, and the longevity regulating pathway. Molecular docking showed that hederagenin and formononetin were the top 2 compounds of HQSJZD, which had a high affinity with AChE. And formononetin has a good neuroprotective effect, which can improve the oxidative damage of nerve cells. Conclusion. HQSJZD was found to have the potential to treat AD by targeting multiple AD-related targets. Formononetin and hederagenin in HQSJZD may regulate multiple signalling pathways through AChE, which might play a therapeutic role in AD.

scholarly journals Network Pharmacology-Based Investigation into the Mechanisms of Quyushengxin Formula for the Treatment of Ulcerative Colitis

2019 ◽  
Vol 2019 ◽  
pp. 1-22
Author(s):  
Haojie Yang ◽  
Ying Li ◽  
Sichen Shen ◽  
Dan Gan ◽  
Changpeng Han ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Bioactive Compounds ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Disease Network ◽  
Pathway Network ◽  
Similarity Algorithm ◽  
Target Network ◽  
Target Disease ◽  
Compound Target

Objective. Ulcerative colitis (UC) is a chronic idiopathic inflammatory bowel disease whose treatment strategies remain unsatisfactory. This study aims to investigate the mechanisms of Quyushengxin formula acting on UC based on network pharmacology. Methods. Ingredients of the main herbs in Quyushengxin formula were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Absorption, distribution, metabolism, and excretion properties of all ingredients were evaluated for screening out candidate bioactive compounds in Quyushengxin formula. Weighted ensemble similarity algorithm was applied for predicting direct targets of bioactive ingredients. Functional enrichment analyses were performed for the targets. In addition, compound-target network, target-disease network, and target-pathway network were established via Cytoscape 3.6.0 software. Results. A total of 41 bioactive compounds in Quyushengxin formula were selected out from the TCMSP database. These bioactive compounds were predicted to target 94 potential proteins by weighted ensemble similarity algorithm. Functional analysis suggested these targets were closely related with inflammatory- and immune-related biological progresses. Furthermore, the results of compound-target network, target-disease network, and target-pathway network indicated that the therapeutic effects of Quyushengxin on UC may be achieved through the synergistic and additive effects. Conclusion. Quyushengxin may act on immune and inflammation-related targets to suppress UC progression in a synergistic and additive manner.

scholarly journals Exploring the Pharmacological Mechanism of the modified Chinese medicine formulas “Shenfu-Linguizhugan decoction” treating Dilated cardiomyopathy Based on Network Pharmacology

2020 ◽  
Author(s):  
Wuxia Quan ◽  
Yandong Miao
Keyword(s):  
Gene Expression ◽  
Chinese Medicine ◽  
Dilated Cardiomyopathy ◽  
Target Genes ◽  
Muscle Disease ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Bioactive Components ◽  
Ppi Network ◽  
Compound Target

Abstract Background: Dilated cardiomyopathy (DCM) is a non-ischaemic cardiac muscle disease with structural and functional myocardial aberration can lead to extensive morbidity and mortality due to complications in particular heart failure and arrhythmia. Two classic Chinese medicine formulas, Shenfu decoction and Linguizhugan decoction, were both shown to exert therapeutic effects on heart disease. Thus, modified Shenfu and Linguizhugan decoction (SFLGZGD) is recommended for treatment DCM. However, its chemical and pharmacological characteristics remain to be elucidated. In the current study, a network pharmacology approach was applied to characterize the action mechanism and target genes of SFLGZGD on DCM.Methods: The gene expression of DCM was obtained from the Gene Expression Omnibus (GEO). All compounds were obtained from the correlative databases, and active mixture were selected according to their oral bioavailability (OB) and drug-likeness (DL) index. The potential targets of SFLGZGD were obtained from the traditional Chinese medicine systems pharmacology (TCMSP) database. The compound-target and target-pathway networks were constructed. The protein-protein interactive (PPI) network generated by R software was visualized by Cytoscape, and the topology scores, functional regions, and gene annotations were analyzed using plugins of Bisogenet and CytoNCA. The potential pathways related to target genes were determined by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.Results: A total of 963 differentially expressed genes (DEGs), including 538 upregulated genes and 425 downregulated, were obtained from GSE19303. A total of 636 ingredients in SFLGZGD were obtained, among which, 93 were chosen as bioactive components. The compound-target network included 10 bioactive components and 18 potential targets and a total of 1939 genes obtained in the PPI network, among them, a total of 16 genes were screened out. Moreover,129 terms on the GO analysis and six pathways obtained. Among these potential targets, EGFR, CDKN1A, MMP1, COL1A1, COL3A1, MMP3, ICAM1, and HSPB1 were identified as relatively high-degree targets.Conclusions: The network pharmacology-based approach in the current study has shown promising potential in identifying major therapeutic targets from TCM formulations. Besides, our study suggested that network pharmacology prediction may provide a useful tool for describing the molecular mechanism of SFLGZGD on DCM.

scholarly journals A network pharmacology-based approach to explore potential targets of Caesalpinia pulcherima: an updated prototype in drug discovery

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nikhil S. Sakle ◽  
Shweta A. More ◽  
Santosh N. Mokale
Keyword(s):  
Breast Cancer ◽  
Target Genes ◽  
Docking Study ◽  
Network Pharmacology ◽  
Egfr Expression ◽  
Target Network ◽  
Anti Fungal ◽  
Compound Target

Abstract Caesalpinia pulcherima (CP) is a traditional herb used for the treatment of asthma, bronchitis, cancer, anti-bacterial, anti-fungal and as abortifacient. In the present study, bioactive components and potential targets in the treatment of breast cancer validated through in silico, in vitro and in vivo approach. The results for the analysis were as among 29 components, only four components were found active for further study which proved the use of CP as a multi-target herb for betterment of clinical uses. The results found by PPI states that our network has significant interactions which include the ESR-1, ESR-2, ESRRA, MET, VEGF, FGF, PI3K, PDK-1, MAPK, PLK-1, NEK-2, and GRK. Compound-target network involves 4 active compound and 150 target genes which elucidate the mechanisms of drug action in breast cancer treatment. Furthermore, on the basis of the above results the important proteins were fetched for the docking study which helps in predicting the possible interaction between components and targets. The results of the western blotting showed that CP regulates ER and EGFR expression in MCF-7 cell. In addition to this animal experimentation showed that CP significantly improved immunohistological status in MNU induced carcinoma rats. Network pharmacology approach not only helps us to confirm the study of the chosen target but also gave an idea of compound-target network as well as pathways associated to the CP for treating the complex metabolic condition as breast cancer and they importance for experimental verification.

scholarly journals Network Pharmacology Strategy to Investigate the Pharmacological Mechanism of Siwu Decoction on Primary Dysmenorrhea and Molecular Docking Verification

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dandan Jiang ◽  
Xiaoyan Wang ◽  
Lijun Tian ◽  
Yufeng Zhang
Keyword(s):  
Molecular Docking ◽  
Target Genes ◽  
Network Pharmacology ◽  
Primary Dysmenorrhea ◽  
Ppi Network ◽  
Active Compounds ◽  
Docking Simulations ◽  
Active Target ◽  
Target Network ◽  
Compound Target

Objective. To study the pharmacological mechanisms of Siwu decoction (SWD) on primary dysmenorrhea (PDM) and verify with molecular docking. Methods. The  Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was utilized to acquire the active compounds and their corresponding target genes. The GeneCards database was utilized in the search for target genes that were associated with PDM. The intersection genes from the active target genes of SWD and those associated with PDM represented the active target genes of SWD that act on PDM. The Gene Ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were both carried out by RGUI 3.6.1 and Cytoscape 3.6.0 software. Cytoscape was also utilized for creating a compound-target network, and a protein-protein interaction (PPI) network was created through the STRING database. Molecular docking simulations of the macromolecular protein target receptors and their corresponding compounds were performed using AutoDockTool 1.5.6 and AutoDock Vina software. Results. We identified 14 active compounds as well as 97 active target genes of SWD by using the TCMSP. We compared the 97 active target genes of SWD to the 299 target genes related to PDM, and 23 active target genes for SWD that act on PDM which correlated with 11 active compounds were detected. The compound-target network as well as the PPI network were created, in addition to selecting the most essential compounds and their targets in order to create a key compound-target network. The most essential compounds were kaempferol, beta-sitosterol, stigmasterol, and myricanone. The key targets were AKT1, PTGS2, ESR1, AHR, CASP3, and PGR. Lastly, molecular docking was used to confirm binding of the target with its corresponding compound. Conclusion. The pharmacological mechanisms of SWD that act on PDM were investigated, and the active compounds in the SWD for treating PDM were further verified.

scholarly journals Exploring Molecular Mechanism of Traditional Chinese Medicine Euphorbiae Semen on Reversing of Multidrug Resistance in Leukemia Based on Network Pharmacology Strategy and Molecular Docking Technology

2020 ◽  
Author(s):  
Xiao Song ◽  
Fei Guo ◽  
Xiao-Chen Sun ◽  
Shu-Yue Wang ◽  
Yao-Hui Yuan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Biological Functions ◽  
Active Compounds ◽  
The Core ◽  
The World ◽  
Target Network ◽  
Compound Target

Abstract Background: Leukemia was listed by the World Health Organization as one of the five most intractable diseases in the world. The multi-drug resistance (MDR) of leukemia cells limits the efficacy of anti-tumor drugs and is the major reason for the chemotherapy failure and recurrence of leukemia chemotherapy. Some studies have shown that Euphorbiae semen (ES) possesses the characteristics of new therapeutic drugs for MDR. However, the molecular mechanisms and active compounds have not yet been fully clarified. Therefore, there is a need for explore its active compounds and demonstrate its mechanisms through network pharmacology and molecular docking technology.Method: First, the TCMSP database was searched and screened the active compounds of the ES, supplemented with compounds verified by literature, so as to further identify the core compounds in the active ingredient. Simultaneously, the TCMSP and Swiss database were searched to the targets of active compounds, and the targets of reverses leukemia multidrug resistance (RL-MDR) were screened in the relevant databases, such as GeneCards and DrugBank. Then, the targets of active compounds were intersected with RL-MDR targets to obtain potential targets of ES acting on MDR. The compound–target network was constructed by Cytoscape. The target protein–protein interaction network was built using STRING and Cytoscape database. Second, the R language and DAVID database were used to analyse Gene Ontology (GO) biological functions analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathways enrichment. Finally, molecular docking method was utilized to investigate the binding activity between the core targets and the active compounds of ES.Results: Compound–target network mainly contained 22 compounds and 81 corresponding targets. Finally, seven components in ES were selected and 10 core targets were identified; Key targets contained JUN, CASP3, MAOA, AR, PPARG, DRD2, ADRA2A, CHRM2, PTGS2 and MAPK14. GO enrichment analysis indicated the main biological functions of potential genes of ES in the treatment of MDR. KEGG pathway enrichment analysis showed the main pathways, mainly including apoptosis, pathways in cancer, p53 signaling pathway, VEGF signaling pathway, TNF signaling pathway and PI3K–Akt signaling pathway. Finally, we chose the top 10 common targets for molecular docking with the 7 active compounds of ES. The results of molecular docking indicated that the compounds of ES, which had good affinity with targets. Conclusion: The molecular mechanism of ES in the treatment of MDR showed the synergistic reaction of multi-compound, multi-target, and multi-pathway of traditional Chinese medicine, which provided ideas for further clinical research.

scholarly journals The Research on Huanglian Jiedu Decoction against Atopic Dermatitis

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Yu-Bin Xu
Keyword(s):  
Atopic Dermatitis ◽  
Mendelian Inheritance ◽  
Network Pharmacology ◽  
Control Group ◽  
Network Graph ◽  
Comparative Toxicogenomics Database ◽  
Target Network ◽  
Analysis Platform ◽  
Related Pathway

Objective. Study on the pharmacodynamic basis and mechanism of Huanglian Jiedu Decoction against atopic dermatitis (AD). Methods. Based on network pharmacology, the targets of Huanglian Jiedu Decoction and AD were screened by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), SwissTargetPrediction databases, and the database of Online Mendelian Inheritance in Man (OMIM), Therapeutic Targets Database (TTD) and the Comparative Toxicogenomics Database (CTD); then, “chemical composition-target-related pathway-disease target” network graph of Huanglian Jiedu Decoction against AD was constructed by using STRING and Cytoscape software. In combination with in vitro experiments, the levels of IL-4, IL-6, and IL-10 in T cells were determined by ELISA; the pharmacodynamic basis and mechanism of Huanglian Jiedu Decoction against AD were preliminarily explored. Results. 81 active ingredients in Huanglian Jiedu Decoction were screened by network pharmacology, 31 of which were related to atopic dermatitis, corresponding to 12 target proteins. A total of 14 pathways were obtained by KEGG pathway analysis, and 8 were associated with atopic dermatitis. Compared with the control group, 20 and 40 µg/ml of Huanglian Jiedu Decoction could significantly reduce the contents of IL-4, IL-6, and IL-10 in T lymphocytes of mice with atopic dermatitis ( p < 0.01 ). Conclusion. Huanglian Jiedu Decoction can act against AD by multicomponent, multitarget, and multichannel mode of action.

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