scholarly journals Evidence of TCM Theory in Treating the Same Disease with Different Methods: Treatment of Pneumonia with Ephedra sinica and Scutellariae Radix as an Example

2020 ◽  
Vol 2020 ◽  
pp. 1-23
Author(s):  
Liping Sun ◽  
Dandan Wang ◽  
Yan Xu ◽  
Wenxiu Qi ◽  
Yanbo Wang
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Future Directions ◽  
Network Construction ◽  
Ephedra Sinica ◽  
Scutellariae Radix ◽  
Tcm Theory ◽  
Global Health Problem

Pneumonia is a serious global health problem and the leading cause of mortality in children. Antibiotics are the main treatment for bacterial pneumonia, but there are serious drug resistance problems. Traditional Chinese medicine (TCM) has been used to treat diseases for thousands of years and has a unique theory. This article takes the treatment of pneumonia with Ephedra sinica as a representative hot medicine and Scutellariae Radix as a representative cold medicine as an example. We explore and explain the theory of treating the same disease with different TCM treatments. Using transcriptomics and network pharmacology methods, GO, KEGG enrichment, and PPI network construction were carried out, demonstrating that Ephedra sinica plays a therapeutic role through the NF-κB and apoptosis signaling pathways targeting PLAU, CD40LG, BLC2L1, CASP7, and CXCL8. The targets of Scutellariae Radix through the IL-17 signaling pathway are MMP9, CXCL8, and MAPK14. Molecular docking technology was also used to verify the results. In short, our results provide evidence for the theory of treating the same disease with different treatments, and we also discuss future directions for traditional Chinese medicine.

scholarly journals Exploring the mechanism of Astragalus membranaceus against uterine fibroids based on network pharmacology

2021 ◽  
Author(s):  
qiu tiantian ◽  
Li DongHua ◽  
Liu Yu ◽  
Gao LiFang ◽  
Wei Chao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Mechanism Of Action ◽  
Regulatory Network ◽  
Drug Targets ◽  
Target Genes ◽  
Uterine Fibroids ◽  
Network Pharmacology ◽  
Ppi Network

Abstract Backgroud: Uterine fibroids (ULs) are the most common benign tumors of the reproductive tract in gynecology and their clinical presentations include menorrhagia, pelvic pressure, dysmenorrhea, and anemia. Surgical resection and the hormonal drug administration are the primary treatment. The plant Astragalus membranaceus (astragalus) has a long history of use in traditional Chinese medicine and studies have shown that it has antitumor effects. However, the role and mechanism of astragalus in ULs are not completely clear. The present study aimed to investigate the astragalus mechanism of action against ULs based on network pharmacology approach, in order to provid insights for the development of a safe and effective drug for the ULs treatment.Methods: The astragalus active ingredients and the potential drug targets were screened by the Traditional Chinese Medicine System Pharmacology Database and Analytical Platform (TCMSP). The gene expression profiles of ULs were obtained from Gene Expression Omnibus (GEO). The intersection of astragalus components target genes and differentially expressed genes between UL and normal patients were obtained using Perl software to provide the astragalus-ULs drug regulatory network. The protein–protein interaction (PPI) network was established using the STRING online database and Cytoscape software, followed by the topological properties analysis of the PPI networks. GO (Gene ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses were conducted by R software. The KEGG relational network was constructed using Cytoscape software. Results: A total of 21 astragalus active ingredients and 406 drug targets were obtained from the TCMSP. Seventeen of these targets overlap with ULs disease targets and were considered potential targets for the ULs treatment by astragalus. The analysis of the regulatory network showed that the astragalus active components with the most targets are quercetin, kaempferol, mangiferin, tetrodotoxin and isorhamnetin. Target genes with the highest Dgree values obtained from the PPI network analysis are estrogen receptor 1 (ESR1), tumor suppressor factor p53 (TP53), neurotrophic tyrosine kinase receptor 1 (NTRK1) and E3 ubiquitin ligase protein (CUL3). GO and KEGG enrichment analyses indicate that these targets are mainly involved in biological processes related to cellular response to reactive oxygen species, oxidative stress and response to lipopolysaccharides. The main signal transduction pathways involved include the IL-17 and TNF signaling pathways, the AGE-RAGE signaling pathway in diabetic complications and proteoglycans in cancer.Conclusions: The present study demonstrates that the astragalus therapeutic use against ULs have multicomponent and multi-target properties, providing a novel approach to further investigate the astragalus mechanism of action in the treatment of ULs.

scholarly journals Network Pharmacology-Based Study on the Mechanism of Scutellariae Radix for Hepatocellular Carcinoma Treatment

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Qian Wang ◽  
Yan Liang ◽  
Can Peng ◽  
Peng Jiang
Keyword(s):  
Hepatocellular Carcinoma ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Mechanistic Study ◽  
Network Pharmacology ◽  
Therapeutic Drug ◽  
Active Components ◽  
Scutellariae Radix

Hepatocellular carcinoma (HCC) is a malignant tumor without effective therapeutic drugs for most patients in advanced stages. Scutellariae Radix (SR) is a well-known anti-inflammatory and anticarcinogenic herbal medicine. However, the mechanism of SR against HCC remains to be clarified. In the present study, network pharmacology was utilized to characterize the mechanism of SR on HCC. The active components of SR and their targets were collected from the traditional Chinese medicine systems pharmacology database and the traditional Chinese medicine integrated database. HCC-related targets were acquired from the liver cancer databases OncoDB.HCC and Liverome. The gene ontology and the Kyoto Encyclopedia of Genes and Genomes pathway were analyzed using the Database for Annotation, Visualization, and Integrated Discovery. Component-component target and protein-protein interaction networks were set up. A total of 143 components of SR were identified, and 37 of them were considered as candidate active components. Fifty targets corresponding to 29 components of SR were mapped with targets of HCC. Functional enrichment analysis indicated that SR exerted an antihepatocarcinoma effect by regulating pathways in cancer, hepatitis B, viral carcinogenesis, and PI3K-Akt signaling. The holistic approach of network pharmacology can provide novel insights into the mechanistic study and therapeutic drug development of SR for HCC treatment.

scholarly journals Network Pharmacology and Molecular Docking Combined to Analyze the Molecular and Pharmacological Mechanism of Pinellia ternata in the Treatment of Hypertension

2021 ◽  
Vol 43 (1) ◽  
pp. 65-78
Author(s):  
Zhaowei Zhai ◽  
Xinru Tao ◽  
Mohammad Murtaza Alami ◽  
Shaohua Shu ◽  
Xuekui Wang
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Western Medicine ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Components ◽  
Pharmacological Mechanism ◽  
Effective Components ◽  
Treatment Of Hypertension

Hypertension is a cardiovascular disease that causes great harm to health and life, affecting the function of important organs and accompanied by a variety of secondary diseases, which need to be treated with drugs for a long time. P. ternata alone or combination with western medicine has played an important role in traditional Chinese medicine. Although P. ternata is used clinically to treat hypertension, its functional molecular mechanism and pharmacological mechanism have not been elucidated. Therefore, in this study, the potentially effective components, and targets of P. ternata in the treatment of hypertension were screened by the method of network pharmacology, and the mechanism of P. ternata in the treatment of hypertension was analyzed by constructing a component-target relationship network, PPI interaction network, targets’ function analysis, and molecular docking. In the study, 12 potentially effective components and 88 targets were screened, and 3 potential protein modules were found and analyzed after constructing a PPI network using targets. In addition, 10 targets were selected as core targets of the PPI network. After that, the targets were analyzed by Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Finally, the molecular docking method is used to study the interaction between the targets and the active components. The above evidence shows that the mechanism of P. ternata in the treatment of hypertension is complicated, as it acts in many ways, mainly by affecting nerve signal transmission, cell proliferation, and apoptosis, calcium channels, and so on. The binding between targets and active components mainly depends on Pi bonds and hydrogen bonds. Using the method of network pharmacology and molecular docking to analyze the mechanism of P. ternata in the treatment of hypertension will help to provide a better scientific basis for the combined use of traditional Chinese medicine and western medicine, and will better help to improve the quality of P. ternata and point out its direction.

scholarly journals Network Pharmacology to Explore the Molecular Mechanisms of Prunella vulgaris for Treating Hashimoto’s Thyroiditis

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiao-xiong Gan ◽  
Lin-kun Zhong ◽  
Fei Shen ◽  
Jian-hua Feng ◽  
Ya-yi Li ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Protein Kinase ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Prunella Vulgaris ◽  
Mitogen Activated Protein

Purpose:Prunella vulgaris (PV), a traditional Chinese medicine, has been used to treat patients with thyroid disease for centuries in China. The purpose of the present study was to investigate its bioactive ingredients and mechanisms against Hashimoto’s thyroiditis (HT) using network pharmacology and molecular docking technology to provide some basis for experimental research.Methods: Ingredients of the PV formula were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Additionally, HT-related genes were retrieved from the UniProt and GeneCards databases. Cytoscape constructed networks for visualization. A protein–protein interaction (PPI) network analysis was constructed, and a PPI network was built using the Search Tool for the Retrieval of Interacting Genes (STRING) database. These key targets of PV were enriched and analyzed by molecular docking verification, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment.Results: The compound–target network included 11 compounds and 66 target genes. Key targets contained Jun proto-oncogene (JUN), hsp90aa1.1 (AKI), mitogen-activated protein kinase 1 (MAPK1), and tumor protein p53 (TP53). The main pathways included the AGE-RAGE signaling pathway, the TNF signaling pathway, the PI3K–Akt signaling pathway, and the mitogen-activated protein kinase signaling pathway. The molecular docking results revealed that the main compound identified in the Prunella vulgaris was luteolin, followed by kaempferol, which had a strong affinity for HT.Conclusion: Molecular docking studies indicated that luteolin and kaempferol were bioactive compounds of PV and might play an essential role in treating HT by regulating multiple signaling pathways.

scholarly journals Study on the Mechanism of Compound Kidney-Invigorating Granule for Osteoporosis based on Network Pharmacology and Experimental Verification

2022 ◽  
Vol 2022 ◽  
pp. 1-20
Author(s):  
Hao Lv ◽  
Jiuxiang Wang ◽  
Yujun Zhu ◽  
Ting Jiang
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Bioactive Compounds ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Hub Genes ◽  
In Cells

Background. This study used a combination of network pharmacology and experimental confirmation to clarify the mechanism of the compound kidney-invigorating granule (CKG) in treating osteoporosis (OP). Methods. The main bioactive compounds and corresponding targets of CKG were collected and screened via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Yet another Traditional Chinese Medicine (YaTCM), and UniProt databases. Disease targets of OP were summarized in GeneCards and the Comparative Toxicogenomics Database (CTD). Targets of CKG for OP were obtained by Venn diagram. The protein-protein interaction (PPI) network was constructed by the STRING database and then screened for hub genes through Cytoscape 3.7.2 software. The Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were analyzed and visualized by R software. Then, CB-Dock was used for molecular docking verification. Finally, we confirmed the antiosteoporosis effect of CKG through animal and cell experiments. Results. A total of 250 putative targets were obtained from 65 bioactive compounds in CKG. Among them, 140 targets were related to OP. Topological analysis of the PPI network yielded 23 hub genes. Enrichment analysis showed the targets of CKG in treating OP might concentrate on the MAPK signaling pathway, the TNF signaling pathway, the PI3K-Akt signaling pathway, etc. The results of molecular docking showed the bioactive components in CKG had good binding ability with the key targets. The experimental results showed that CKG-medicated serum had a promoting effect on proliferating hBMSCs, increasing the expression of AKT, PI3K, ERK1, and IkB in cells and decreasing the expression of IKK in cells. Conclusion. CKG has a complex of multicomponent, multitarget, and multipathway. This study lays the theoretical foundation for further in vitro and in vivo experimental studies and further expands the clinical applications of CKG.

Anti-Respiratory Syncytial Virus Mechanism of Houttuynia cordata Thunb Exploration based on Network Pharmacology

2020 ◽  
Vol 23 ◽  
Author(s):  
Haitao Du ◽  
Jie Ding ◽  
Ping Wang ◽  
Guisheng Zhang ◽  
Dandan WANG ◽  
...  
Keyword(s):  
Respiratory Syncytial Virus ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Compounds ◽  
Houttuynia Cordata ◽  
Syncytial Virus ◽  
Houttuynia Cordata Thunb ◽  
Tract Infections

Background and Objective: : Respiratory Syncytial Virus (RSV) is the leading cause of infant lower respiratory tract infections with no mature vaccines and medicines available. Pneumonia caused by RSV kills many infants every year. There are unique advantages for Traditional Chinese Medicine (TCM) to fight against the virus. Houttuynia cordata Thunb is a commonly used anti-virus medicine in TCM, but its mechanism has not been investigated. The current study explores the anti-RSV mechanism of H. cordata Thunb by means of network pharmacology and bioinformatics. Method: The candidate compounds of H. cordata Thunb and the potential targets were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), PubMed, CNKI, PubChem Database, and Swiss Target Prediction database. Then the potential targets and pathways of H. cordata Thunb against RSV were screened by GeneCards, GenCLiP 3, and NCBI Database. We developed a Protein-Protein Interactions (PPI) Network and Compound-Target-Pathway Network through the Cytoscape software. Furthermore, core targets were preliminary verification by Gene Expression Omnibus (GEO) database by bioinformatics methods. At last, the first 6 pathways were screened out to draw a map of the main target signal pathways. Results:: A total of 12 potentially active compounds and 47 potential interaction targets were screened. PPI Network and data from GEO showed that IL-6, STAT3, TNF, AKT1, PTGS2, SRC, and MAPK3 may play a core role in the antivirus process. KEGG enrichment pathway analysis predicted that H. cordata Thunb exerted its anti-RSV effect by regulating TNF, Rap1, HIF-1, PI3K-Akt, MAPK, and VEGF signaling pathways. Conclusion: : This study preliminarily predicted the main active compounds, targets and related pathways of H. cordata Thunb in the treatment of RSV-induced diseases, which laid a good foundation for further revealing its mechanism.

scholarly journals Utilization Pattern of Traditional Chinese Medicine among Fracture Patients: A Taiwan Hospital-Based Cross-Sectional Study

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Chu-Yao Tseng ◽  
Ching-Wen Huang ◽  
Hsin-Chia Huang ◽  
Wei-Chen Tseng
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Early Period ◽  
Clinic Visit ◽  
Research Database ◽  
Late Period ◽  
Utilization Pattern ◽  
Cross Sectional ◽  
Herbal Products ◽  
Tcm Theory

Traditional Chinese medicine (TCM) divides fracture treatment into three stages. Many TCM herbs and formulas have been used to treat fractures for thousands of years. However, research regarding the Chinese herbal products (CHPs) that should be used at different periods of treatment is still lacking. This study aims to identify the CHPs that should be used at different periods of treatment as well as confirm the TCM theory of fracture periods medicine. We used prescriptions of TCM outpatients with fracture diagnoses analyzed using the Chang Gung Research Database (CGRD) from 2000 to 2015. According to the number of days between the date of the fracture and the clinic visit date, all patients were assigned to one of three groups. Patients with a date gap of 0-13 days were assigned to the early period group; those with a date gap of 14-82 days were assigned to the middle period group; and those with a date gap of 83-182 days were assigned to the late period group. We observed the average number of herbal formulas prescribed by the TCM doctor at each visit was 2.78, and the average number of single herbs prescribed was 6.47. The top three prescriptions in the early fracture period were Zheng-gu-zi-jin-dang, Shu-jing-huo-xue-tang, and Wu-ling-san. In the middle fracture period, the top three formulas were Zheng-gu-zi-jin-dang, Shu-jing-huo-xue-tang, and Zhi-bai-di-huang-wan. In the late fracture period, the top three formulas were Shu-jing-huo-xue-tang, Gui-lu-er-xian-jiao, and Du-huo-ji-sheng-tang. The main single herbs used in the early fracture period were Yan-hu-suo, Gu-sui-bu, and Dan-shen. From the middle to the late period, the most prescribed single herbs were Xu-duan, Gu-sui-bu, and Yan-hu-suo. We concluded that the results showed that the CGRD utilization pattern roughly meets the TCM theory at different fracture periods.

scholarly journals Study on the Mechanism of Lianpu Drink for the Treatment of Chronic Gastritis Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Shuhan Zhou ◽  
Yanjun Duan ◽  
Yu Deng ◽  
Miao Wang ◽  
Chaoqun Huang ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Chronic Gastritis ◽  
Mechanisms Of Action ◽  
Network Pharmacology ◽  
Biological Pathway ◽  
Disease Network ◽  
Target Disease ◽  
Compound Target

Chronic gastritis (CG) places a considerable burden on the healthcare system worldwide. Traditional Chinese Medicine (TCM) formulas characterized by multicompounds and multitargets have been acknowledged with striking effects in the treatment of CG in China’s history. Nevertheless, their accurate mechanisms of action are still ambiguous. In this study, we analyzed the effective compounds, potential targets, and related biological pathway of Lianpu Drink (LPD), a TCM formula which has been reported to have a therapeutic effect on CG, by contrasting a “compound-target-disease” network. According to the results, 92 compounds and 5762 putative targets of LPD were screened; among them, 8 compounds derived from different herbs in LPD and 30 common targets related to LPD and CG were selected as candidate compounds and precision targets, respectively. Meanwhile, the predicted common targets were verified by Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway analysis and pharmacological experiments. The results demonstrated that quercetin, ephedrine, trigonelline, crocetin, and β-sitosterol were major effective compounds of LPD responsible for the CG treatment by inhibiting the activation of the JAK 2-STAT 3 signaling pathway to reduce the expressions of cyclin D1 and Bcl-2 proteins. The study provides evidence for the mechanism of understanding of LPD for the treatment of CG.

scholarly journals Determining novel candidate anti-hepatocellular carcinoma drugs using interaction networks and molecular docking between drug targets and natural compounds of SiNiSan

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10745
Author(s):  
Qin Zhang ◽  
Zhangying Feng ◽  
Mengxi Gao ◽  
Liru Guo
Keyword(s):  
Hepatocellular Carcinoma ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Drug Targets ◽  
Cellular Response ◽  
Hormone Receptors ◽  
Enrichment Analysis ◽  
Stage Iii ◽  
Ppi Network ◽  
P53 Signaling

Background SiNiSan (SNS) is an ancient traditional Chinese medicine (TCM) used to treat liver and spleen deficiencies. We studied the unique advantages of using SNS to treat hepatocellular carcinoma (HCC) with multiple components and targets to determine its potential mechanism of action. Methods The active compounds from the individual herbs in the SNS formula and their targets were mined from Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). HCC-associated targets were collected from the TCGA and GEO databases and samples were collected from patients with stage III hepatocellular carcinoma. A compound-disease target network was constructed, visualized, and analyzed using Cytoscape software. We built a protein-protein interaction (PPI) network using the String database. We enriched and analyzed key targets using GSEA, GO, and KEGG in order to explore their functions. Autodock software was used to simulate the process of SNS molecules acting on HCC targets. Results A total of 113 candidate compounds were taken from SNS, and 64 of the same targets were chosen from HCC and SNS. The predominant targets genes were PTGS2, ESR1, CHEK1, CCNA2, NOS2 and AR; kaempferol and quercetin from SNS were the principal ingredients in HCC treatment. The compounds may work against HCC due to a cellular response to steroid hormones and histone phosphorylation. The P53 signaling pathway was significantly enriched in the gene set GSEA enrichment analysis and differential gene KEGG enrichment analysis. Conclusions Our results showed that the SNS component has a large number of stage III HCC targets. Among the targets, the sex hormone receptors, the AR and ESR1 genes, are the core targets of SNS component and the most active proteins in the PPI network. In addition, quercetin, which has the most targets, can act on the main targets (BAX, CDK1, CCNB1, SERPINE1, CHEK2, and IGFBP3) of the P53 pathway to treat HCC.

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