Exploring the pharmacological mechanism of Yanghe Decoction on HER2-positive breast cancer by a network pharmacology approach

Postoperative Yanghe decoction regimen improves outcomes for idiopathic granulomatous mastitis: A retrospective cohort study

The etiology of idiopathic granulomatous mastitis (IGM), a rare inflammatory breast disease, is not understood. There is no consensus regarding the treatment of IGM. The purpose of this study was to determine the efficacy of surgery combined with traditional Chinese medicine for the treatment of IGM.We retrospectively analyzed 53 patients of IGM who were treated with surgical excision at our hospital. Group A (n = 25) included patients treated with only surgery, and Group B included patients treated with surgery combined with postoperative Yanghe decoction. The clinical data were compared between the 2 groups, including demographics, clinical characteristics, and outcomes.All patients were female with a mean age of 34.6 ± 5.9 years. There were no significant differences between the groups regarding preoperative demographics or clinical characteristics. The follow-up time was comparable between the groups (13.2 ± 10.0 vs 12.0 ± 10.2 months). Patients in Group B had shorter complete remission (CR) times than patients in Group A (76.1 ± 15.2 vs 84.0 ± 12.2 days; P < .05). The CR rate was higher in Group B than in Group A (96.4% vs 76.0%; P < .05), and the recurrence rate was lower in Group B than in Group A (0% vs 16.0%; P < .05).The postoperative Yanghe decoction regimen was associated with more rapid recovery after IGM surgery. Surgical management combined with postoperative oral Yanghe decoction treatment yielded a higher CR rate and lower recurrence rate than surgery alone. The effect of traditional Chinese medicine in IGM treatment requires further study.

Systems pharmacology in combination with proteomics reveals underlying mechanisms of Xihuang pill against triple-negative breast cancer

Xihuang pill (XHP), a traditional Chinese herbal formula, has been clinically used as an adjuvant therapy against triple-negative breast cancer (TNBC) via inhibiting cancer cell invasion and proliferation, as well as promoting cancer cell apoptosis. However, its anti-TNBC bio-active ingredients and possible mechanisms are still unclear. Herein, the hub bio-active compounds and underlying mechanisms of XHP against TNBC were systematically elucidated by integrating systems pharmacology approach and in vitro proteomics analysis. Using systems pharmacology analysis and molecular docking evaluation, 28 bio-active compounds and 10 potential therapeutic targets of XHP were identified. Functional analysis showed that the core therapeutic targets against TNBC were mainly involved in epidermal growth factor receptor (EGFR)-phosphatidylinositol 3-kinase (PI3K)-AKT signaling pathway to prevent cancer cell proliferation and angiogenesis, as well as to enhance cancer cell apoptosis. The in vitro proteomics analysis identified 153 differentially expressed proteins (DEPs), including HASP90AA1, AKT1, and EGFR, which were also identified as therapeutic targets against TNBC through systems pharmacology analysis. Protein function analysis showed that the DEPs were mainly involved in PI3K-AKT signaling pathway, which was consistent with the result of systems pharmacology, suggesting the reliability of systems pharmacology analysis. Taken together, these findings uncover the underlying mechanism of XHP against TNBC, and provide a scientific method for the rational development of traditional Chinese medicine.

Network Pharmacology-Based Strategy Reveals the Effects of Hedysarum multijugum Maxim.-Radix Salviae Compound on Oxidative Capacity and Cardiomyocyte Apoptosis in Rats with Diabetic Cardiomyopathy

Objective

To explore the effects of the Hedysarum multijugum Maxim.-Radix Salviae compound (Huangqi-Danshen Compound (HDC)) on oxidative capacity and cardiomyocyte apoptosis in rats with diabetic cardiomyopathy by a network pharmacology-based strategy.

Methods

Traditional Chinese Medicine (TCM)@Taiwan, TCM Systems Pharmacology Database and Analysis Platform (TCMSP), TCM Integrated Database (TCMID), and High-Performance Liquid Chromatography (HPLC) technology were used to obtain and screen HDC's active components, and the PharmMapper database was used to predict HDC human target protein targets. The DCM genes were collected from the GeneCards and OMIM databases, and the network was constructed and analyzed by Cytoscape 3.7.1 and the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Finally, HDC was used to intervene in diabetic cardiomyopathy (DCM) model rats, and important biological processes and signaling pathways were verified using techniques such as immunohistochemistry.

Results

A total of 176 of HDC's active components and 442 potential targets were obtained. The results of network analysis show that HDC can regulate DCM-related biological processes (such as negative regulation of the apoptotic process, response to hypoxia, the steroid hormone-mediated signaling pathway, cellular iron ion homeostasis, and positive regulation of phosphatidylinositol 3-kinase signaling) and signaling pathways (such as the HIF-1 signaling pathway, the estrogen signaling pathway, insulin resistance, the PPAR signaling pathway, the VEGF signaling pathway, and the PI3K-Akt signaling pathway). Animal experiments show that HDC can reduce fasting plasma glucose (FPG), HbA1c, and malondialdehyde (MDA) and increase superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) (P < 0.05). The results of immunohistochemistry showed that HDC can regulate the protein expression of apoptosis-related signaling pathways in DCM rats (P < 0.05).

Conclusion

It was initially revealed that HDC improves DCM through its antiapoptotic and anti-inflammatory effects. HDC may play a therapeutic role by improving cardiomyocyte apoptosis in DCM rats.

Identification of Target Genes Related to Sulfasalazine in Triple-Negative Breast Cancer Through Network Pharmacology

Background

The anti-inflammatory drug sulfasalazine (SAS) has been confirmed to inhibit the growth of triple-negative breast cancer (TNBC), but the mechanism is not clear. The aim of this study was to use network pharmacology to find relevant pathways of SAS in TNBC patients.

Material/Methods

Through screening of the GeneCards, CTD, and ParmMapper databases, potential genes related to SAS and TNBC were identified. In addition, gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed using the R programming language. Protein–protein interaction networks were constructed using Cytoscape. The Kaplan-Meier plotter screened genes related to TNBC prognosis. TNBC patient gene expression profiles and clinical data were downloaded from The Cancer Genome Atlas database. A heatmap was generated using the R programming language that presents the expression of potential target genes in patients with TNBC.

Results

Eighty potential target genes were identified through multiple databases. The bioinformatical analyses predicted the interrelationships, potential pathways, and molecular functions of the genes from multiple aspects, which are associated with physiological processes such as the inflammatory response, metabolism of reactive oxygen species (ROS), and regulation of proteins in the matrix metalloproteinase (MMP) family. Survival analysis showed that 12 genes were correlated with TNBC prognosis. Heatmapping showed that genes such as those encoding members of the MMP family were differentially expressed in TNBC tissues and normal tissues.

Conclusions

Our analysis revealed that the main reasons for the inhibitory effect of SAS on TNBC cells may be inhibition of the inflammatory response and MMP family members and activation of ROS.

Network pharmacology-based identification for therapeutic mechanisms of Dangguikushen pill in acne vulgaris

The Dangguikushen (DGKS) pill is a proprietary traditional Chinese medicine that has shown superior efficacy in the treatment of acne vulgaris for many years. A network pharmacology-based analysis was performed to explore the potential anti-acne compounds, core therapeutic targets, and the main pathways, involved in the DGKS pill bioactivity. The matching results between the predicted targets of the DGKS pill and the well-known targets of acne vulgaris were collected, followed by network establishment using protein-protein interaction (PPI) data. Cytoscape was utilized to analyze the network and screen the core targets. Furthermore, the Database for Annotation, Visualization and Integrated Discovery (DAVID), and ClueGO were used for the enrichment analysis of the Kyoto Encyclopedia of Genes and Genomics (KEGG) pathways and Gene Ontology biological processes (GO-BP). Finally, the "compound-target-pathway" network was constructed. This approach identified 19 active compounds, 46 therapeutic targets, and 12 core therapeutic targets of the DGKS pill. The biological processes were primarily related to reactive oxygen species (ROS) metabolic process, gland morphogenesis, and female gonad development. The DGKS pill was significantly associated with eight pathways including the PI3K-Akt, TNF, NF-kappa B, and p53 signaling pathways. DGKS pill might have a synergistic effect on the inhibition of excessive sebaceous lipogenesis and sebocyte differentiation, and likewise, anti-inflammatory effects via the different signaling pathways (PI3K-Akt, TNF, NF-kappa B, and p53).

Network Pharmacology-Based Prediction and Verification of the Active Ingredients and Potential Targets of Zuojinwan for Treating Colorectal Cancer

Background

Zuojinwan (ZJW), a famous Chinese medicine formula, has been widely used to treat colorectal cancer (CRC). However, its bioactive compounds, potential targets, and molecular mechanism remain largely elusive.

Aim

A network pharmacology-based strategy combined with molecular docking studies and in vitro validation were employed to investigate bioactive compounds, potential targets, and molecular mechanism of ZJW against CRC.

Materials and Methods

Bioactive compounds and potential targets of ZJW, as well as related genes of CRC, were acquired from public databases. Important ingredients, potential targets, and signaling pathways were determined through bioinformatics analysis, including protein-protein interaction (PPI), the Gene Ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Subsequently, molecular docking and cell experiments were performed to further verify the findings.

Results

A total of 36 bioactive ingredients of ZJW and 163 gene targets of ZJW were identified. The network analysis revealed that quercetin, baicalein, wogonin, beta-sitosterol, and isorhamnetin may be candidate agents. The AKT1, JUN, CDKN1A, BCL2L1, and NCOA1 could become potential drug targets. The KEGG indicated that PI3K-AKT signaling pathway may play an important role in the effect of ZJW against CRC. Molecular docking suggested that quercetin, baicalein, and wogonin combined well with AKT1 and JUN. The in vitro experiment showed that quercetin, the most important ingredient of ZJW, could induce apoptosis of HCT116 cells through PI3K-Akt signaling pathway. This finding was congruent with the prediction obtained through the network pharmacology approach.

Conclusion

This study comprehensively illuminated the active ingredients, potential targets, and molecular mechanism of ZJW against CRC. It also provided a promising approach to uncover the scientific basis and therapeutic mechanism of traditional Chinese medicine (TCM) formula treating for disease.

Exploring the mechanism of Shengmai Yin for coronary heart disease based on systematic pharmacology and chemoinformatics

OBJECTIVE

To explore the mechanism of Shengmai Yin (SMY) for coronary heart disease (CHD) by systemic pharmacology and chemoinformatics.

METHODS

Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), traditional Chinese medicine integrative database (TCMID) and the traditional Chinese medicine (TCM) Database@Taiwan were used to screen and predict the bioactive components of SMY. Pharmmapper were utilized to predict the potential targets of SMY, the TCMSP was utilized to obtain the known targets of SMY. The Genecards and OMIM database were utilized to collect CHD genes. Cytoscape was then used for network construction and analysis, and DAVID was used for Gene Ontology (GO) and pathway enrichment analysis. After that, animal experiments were then performed to further validate the results of systemic pharmacology and chemoinformatics.

RESULTS

Three major networks were constructed: (1) CHD genes' protein-protein interaction (PPI) network; (2) SMY-CHD PPI network; (3) SMY known target-CHD PPI network. The other networks are minor networks generated by analyzing the three major networks. Experimental results showed that compared with the model group, the Shengmai injection (SMI) can reduce the myocardial injury score and the activities of serum aspartate aminoconvertase (AST), CK and lactate dehydrogenase (LDH) in rats (P<0.05), and reduce serum lipid peroxide (LPO) content and increase serum superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities in myocardial infarction rats (P<0.05). SMI can also decrease the expression of MMP-9 mRNA and increase that of TIMP-1 mRNA (P<0.01).

CONCLUSION

SMY may regulate the signaling pathways (such as PPAR, FoxO, VEGF signaling), biological processes (such as angiogenesis, blood pressure formation, inflammatory response) and targets (such as AKT1, EGFR, MAPK1) so as to play a therapeutic role in CHD.

Exploring Mechanism of Key Chinese Herbal Medicine on Breast Cancer by Data Mining and Network Pharmacology Methods

OBJECTIVE

To screen the key Chinese Herbal Medicines (KCHMs) against breast cancer by data mining, and analyze the potential mechanism of KCHMs using network pharmacology method.

METHODS

Clinical prescriptions consisted of CHMs for treating breast cancer were screened, and then Traditional Chinese Medicine Inheritance Support System (TCMISS) was applied to obtain the KCHMs. Subsequently, active ingredients and corresponding target genes of KCHMs were searched by Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database, and target genes of breast cancer were collected using OMIM and MalaCards. After that, the overlapping target genes of KCHMs and breast cancer were screened, and the protein-protein interaction (PPI) network was built. In addition, a network of "KCHMs-active ingredients-breast cancer-targets" was constructed by Cytoscape 3.7.1. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis were performed with Database for Annotation, Visualization and Integrated Discovery (DAVID) database to reveal the action mechanism of KCHMs.

RESULTS

A total of 7 KCHMs were identified, whose active ingredients include quercetin, luteolin, nobiletin, kaempferol, isorhamnetin, naringenin, and be-ta-sitosterol, etc. Based on protein-protein interaction analysis, core targets were ESR1, MYC, CCND1, EGFR, CASP3, ERBB2, etc. Several KEGG pathways (e.g, PI3K-Akt, p53, ErbB, and HIF-1 signaling pathways) were found.

CONCLUSION

Based on the combination of the data mining method and network pharmacology approach, the therapeutic effect of KCHMs on breast cancer may be realized by acting on target genes and signaling pathways related to the formation and progression of breast cancer.

Exploring the Regulation Mechanism of Xihuang Pill, Olibanum and β-Boswellic Acid on the Biomolecular Network of Triple-Negative Breast Cancer Based on Transcriptomics and Chemical Informatics Methodology

Background

Xihuang Pill (XHP) is mainly used to treat “Ru Yan (breast cancer)”. Evidence-based medical evidence and showed that XHP improves the efficacy of chemotherapy and reduced chemotherapy-induced toxicity in breast cancer patients. However, the mechanism of XHP against breast cancer is not clear.

Methods

The effect of XHP extract on cell half-inhibitory concentration (IC50) and cell viability of MD-MB-231 cells was detected by CCK-8 method. The cell inhibition rate of MDA-MB-453 cells were detected by MTT method. Apoptosis was detected by flow cytometry, cell transfer ability was detected by Transwell method, and cell proliferation ability was detected by colony formation assay. The expression of Notch1, β-catenin and c-myc mRNA in MDA-MB-453 cells were detected by real-time fluorescence quantitative PCR. Then, chemical informatics and transcriptomics methodology was utilized to predict the potential compounds and targets of XHP, and collect triple negative breast cancer (TNBC) genes and the data of Olibanum and β-boswellic acid intervention MD-MB-231 cells (from GSE102891). The cytoscape software was utilized to undergo network construction and network analysis. Finally, the data from the network analysis was imported into the DAVID database for enrichment analysis of signaling pathways and biological processes.

Results

The IC50 was 15.08 g/L (for MD-MB-231 cells). After interfering with MD-MB-231 cells with 15.08 g/L XHP extract for 72 h, compared with the control group, the cell viability, migration and proliferation was significantly decreased, while early apoptosis and late apoptosis were significantly increased (P < 0.01). After interfering with MDA-MB-453 cells with 6 g/L XHP extract for 72 h, compared with the control group, the cell inhibition and apoptosis rate increased, while the expression of Notch1, β-catenin and c-myc mRNA decreased. (P < 0.05). The chemical informatics and transcriptomics analysis showed that four networks were constructed and analyzed: (1) potential compounds-potential targets network of XHP; (2) XHP-TNBC PPI network; (3) DEGs PPI network of Olibanum-treated MD-MB 231 cells; (4) DEGs PPI network of β-boswellic acid -treated MD-MB 231 cells. Several anti-TNBC biological processes, signaling pathways, targets and so on were obtained.

Conclusion

XHP may exert anti-TNBC effects through regulating biological processes, signaling pathways, targets found in this study.

GC-MS based comparative metabolomic analysis of MCF-7 and MDA-MB-231 cancer cells treated with Tamoxifen and/or Paclitaxel

Breast cancer cells MCF-7 and MDA-MB-231 were treated with Tamoxifen (5 μM) or Paclitaxel (1 μM) or with a combination of the two drugs. Herein, we have employed gas chromatography coupled with mass spectroscopy to identify metabolic changes occurring as response to different drug treatments. We report the identification of sixty-one metabolites and overall the two studied cell lines showed a distinct metabolomic profile from each other. Further data analysis indicates that a total of 30 metabolites were significantly differentially abundant in MCF-7 drug-treated cells, most of the metabolic changes occurred when cells were treated with either Tamoxifen (15) or Paclitaxel (25). On the other side, a total of 31 metabolites were significantly differentially abundant in MDA-MB-31 cells with drug treatment. Similarly, to MCF-7 most of the metabolic changes occurred when cells were treated with either Tamoxifen (19) or Paclitaxel (20). In conclusion, this report demonstrates that Tamoxifen and/or Paclitaxel treatment have a pronounced effect on the main metabolic pathways in both breast cancer (BC) cell lines (MCF-7 and MDA-MB231), which could be used as a foundation for future investigations to understand the possible effect of these drugs on different metabolic pathways. SIGNIFICANCE: Metabolic profiling of cancer cells is a promising tool in tumor diagnosis, biomarker discovery and drug treatment protocols, since cancer cells exhibit altered metabolism when compared to normal cells. Although numerous studies have reported the use of various OMICs applications to investigate breast cancer cells, very few of these have performed thorough screening of metabolites in such cells. Our investigation highlights the first study to characterize MCF7 and MDA-MB-231 cancer cells treated with Tamoxifen and/or Paclitaxel and to identify the affected metabolic pathways. Such findings might play an important role in revealing the molecular bases of the underlying mechanism of action of these two frontline anti-breast cancer drugs.

Bioinformatics and experimental studies of anti-leukemic activity from 6-gingerol demonstrate its role in p53 mediated apoptosis pathway

6-gingerol is a traditional medicine that possesses anti-cancer activity against several types of cancer. However, the mechanism of action still remains unclear. Therefore, this study explored the effects of 6-gingerol on anti-leukemic mechanisms in NB4, MOLT4, and Raji leukemic cell. Results indicated that 6-gingerol inhibited cell proliferation and induced cell apoptosis in these 3 cell lines. Moreover, 6-gingerol was shown to increase the mRNA expression of the caspase family thereby suggesting that 6-gingerol induced apoptosis through the caspase-dependent pathway. To explore the signaling pathway regulating 6-gingerol induced apoptosis, we utilized and integrated the network pharmacology approach together with experimental investigations. Targets of 6-gingerol were identified from ChEMBL and STITCH databases, which were used for constructing the protein-protein interaction (PPI) network. Results from the PPI network indicated that p53 was a key regulator. Moreover, it was found that 6-gingerol could increase the levels of p53 mRNA in all leukemic cell lines. Thus, 6-gingerol has shown to have anti-cancer activity. In addition, p53, BAX and BCL2 could be involved in the apoptosis pathway of these leukemic cells. This study is anticipated to be useful for the development of 6-gingerol as an anti-leukemic drug in the future.

Systematic Elucidation of the Potential Mechanisms of Core Chinese Materia Medicas in Treating Liver Cancer Based on Network Pharmacology

Objective

In this study, the data mining method was used to screen the core Chinese materia medicas (CCMMs) against primary liver cancer (PLC), and the potential mechanisms of CCMMs in treating PLC were analyzed based on network pharmacology.

Methods

Traditional Chinese medicine (TCM) prescriptions for treating PLC were obtained from a famous TCM doctor in Shenzhen, China. According to the data mining technique, the TCM Inheritance Support System (TCMISS) was applied to excavate the CCMMs in the prescriptions. Then, bioactive ingredients and corresponding targets of CCMMs were collected using three different TCM online databases, and target genes of PLC were obtained from GeneCards and OMIM. Afterwards, common targets of CCMMs and PLC were screened. Furthermore, a network of CCMMs bioactive ingredients and common target gene was constructed by Cytoscape 3.7.1, and gene ontology (GO) and signaling pathways analyses were performed to explain the mechanism of CCMMs in treating PLC. Besides, protein-protein interaction (PPI) analysis was used to identify key target genes of CCMMs, and the prognostic value of key target genes was verified using survival analysis.

Results

A total of 15 high-frequency Chinese materia medica combinations were found, and CCMMs (including Paeoniae Radix Alba, Radix Bupleuri, Macrocephalae Rhizoma, Coicis Semen, Poria, and Curcumae Radix) were identified by TCMISS. A total of 40 bioactive ingredients (e.g., quercetin, kaempferol, and naringenin) of CCMMs were obtained, and 202 common target genes of CCMMs and PLC were screened. GO analysis indicated that biological processes of CCMMs were mainly involved in response to drug, response to ethanol, etc. Pathway analysis demonstrated that CCMMs exerted its antitumor effects by acting on multiple signaling pathways, including PI3K-Akt, TNF, and MAPK pathways. Also, some key target genes of CCMMs were determined by PPI analysis, and four genes (MAPK3, VEGFA, EGF, and EGFR) were found to be correlated with survival in PLC patients.

Conclusion

Based on data mining and network pharmacology methods, our results showed that the therapeutic effect of CCMMs on PLC may be realized by acting on multitargets and multipathways related to the occurrence and development of PLC.

Applications of Network Pharmacology in Traditional Chinese Medicine Research

Human diseases, especially infectious ones, have been evolving constantly. However, their treatment strategies are not developing quickly. Some diseases are caused by a variety of factors with very complex pathologies, and the use of a single drug cannot solve these problems. Traditional Chinese Medicine (TCM) medication is a unique treatment method in China. TCM formulae contain multiple herbs with multitarget, multichannel, and multilink characteristics. In recent years, with the flourishing development of network pharmacology, a new method for searching therapeutic drugs has emerged. The multitarget action in network pharmacology is consistent with the complex mechanisms of disease and drug action. Using network pharmacology to understand TCM is an emerging trend.

Network pharmacology-based study on the mechanism of Yiganling capsule in hepatitis B treatment

Background

Yiganling (YGL) capsule is a traditional Chinese medicine preparation consisting of eight herbs that has been clinically proven to have a favorable treatment effect on Hepatitis B (HB). However, due to its multiple targets and multi-pharmacological effects, the mechanisms of YGL capsule in the treatment of HB are unknown.

Methods

First, the chemical constituents of YGL capsules were obtained from the Chinese medicine database, and YGL capsules were constructed. Second, active compounds were screened by the ADME model. The target fishing model was used to screen the corresponding targets of active compounds and to construct a compounds and compound targets network. Using human disease databases and literature mining, we systematically identified genes associated with HB, constructed disease-specific protein-protein interaction networks, and performed clustering and enrichment analyses of these networks. These networks were then merged to obtain a compound-disease target network, and cluster and enrichment analyses were performed on the compound-disease target network to acquire a compounds-disease targets-mechanism network and a clustering network.

Results

We successfully built eight pharmacological network diagrams, including four primary networks and other network maps. The four dominating network maps included a HB disease-associated protein-protein interaction network, a YGL capsule compounds-target network, a YGL capsule ingredient target-HB disease target network, and a YGL-HB disease mechanism network. Other networks included a pathway of HB disease targets, the HB disease protein-protein interaction cluster analysis network, and the YGL-HB target clustering network.

Conclusion

This study successfully forecasted, illuminated, and confirmed the synergistic effects of HB disease molecules and discovered the potential of HB relevant targets, clusters, and target-related biological processes and signaling pathways. Our research not only provides theoretical support for the molecular and pharmacological mechanisms of YGL capsule in HB treatment, but also provides new research methods for the study of the other traditional Chinese medicinal compounds.

A Network Pharmacology-Based Strategy For Predicting Active Ingredients And Potential Targets Of LiuWei DiHuang Pill In Treating Type 2 Diabetes Mellitus

Background

Traditional Chinese medicine (TCM) formulations have proven to be advantageous in clinical treatment and prevention of disease. LiuWei DiHuang Pill (LWDH Pill) is a TCM that was employed to treat type 2 diabetes mellitus (T2DM). However, a holistic network pharmacology approach to understanding the active ingredients and the therapeutic mechanisms underlying T2DM has not been pursued.

Methods

A network pharmacology approach including drug-likeness evaluation, oral bioavailability prediction, virtual docking, and network analysis has been used to predict the active ingredients and potential targets of LWDH Pill in the treatment of type 2 diabetes.

Results

The comprehensive network pharmacology approach was successfully to identify 45 active ingredients in LWDH Pill. 45 active ingredients hit by 163 potential targets related to T2DM. Ten of the more highly predictive components (such as :quercetin, Kaempferol, Stigmasterol, beta-sitosterol, Kadsurenone, Diosgenin, hancinone C, Hederagenin, Garcinone B, Isofucosterol) are involved in anti-inflammatory, anti-oxidative stress, and the reduction of beta cell damage. LWDH Pill may play a role in the treatment of T2DM and its complications (atherosclerosis and nephropathy) through the AGE-RAGE signaling pathway, TNF signaling pathway, and NF-kappa B signaling pathway.

Conclusion

Based on a systematic network pharmacology approach, our works successfully predict the active ingredients and potential targets of LWDH Pill for application to T2DM and helps to illustrate mechanism of action on a comprehensive level. This study provides identify key genes and pathway associated with the prognosis and pathogenesis of T2DM from new insights, which also demonstrates a feasible method for the research of chemical basis and pharmacology in LWDH Pill.

Systematic Pharmacological Methodology to Explore the Pharmacological Mechanism of Siwu Decoction for Osteoporosis

Osteoporosis is an important health problem worldwide. Siwu decoction (SWD) and its modification have a good clinical effect on osteoporosis. However, the molecular mechanism of SWD on osteoporosis has not been thoroughly explained. A systematic pharmacological methodology was utilized to predict the active compounds and potential targets of SWD, collect the genes of osteoporosis and the known targets of SWD, and analyze the osteoporosis and SWD's network. Five networks were constructed and analyzed: (1) Osteoporosis genes' protein-protein interaction (PPI) network; (2) Compound-compound target network of SWD; (3) SWD-osteoporosis PPI network; (4) Compound-known target network of SWD; and (5) SWD known target- osteoporosis PPI network. Several osteoporosis and treatment-related targets (eg.,. HSP90AB1, FGFR1, HRAS, GRB2, and PGF), clusters, biological processes, and signaling pathways (e.g., PI3K-Akt signaling pathway, insulin signaling pathway, MAPK signaling pathway and FoxO signaling pathway) were found. The therapeutic effect of SWD on osteoporosis may be achieved by interfering with the biological processes and signaling pathways related to the development of osteoporosis.

Investigating the regulation mechanism of baicalin on triple negative breast cancer's biological network by a systematic biological strategy

OBJECTIVE

To investigate the regulation mechanism of baicalin on triple negative breast cancer (TNBC)'s biological network by a systematic biological strategy and cytology experiment.

METHODS

A systematic biological methodology is utilized to predict the potential targets of baicalin, collect the genes of TNBC, and analyze the TNBC and baicalin's network. After the systematic biological analysis is performed, the cytology experiment, real-time quantitative PCR (qPCR) is used to validate the key biological processes and signaling pathways.

RESULTS

After systematic biological analysis, two networks were constructed and analyzed: (1) TNBC network; (2) Baicalin-TNBC protein-protein interaction (PPI) network. Several TNBC-related, treatment-related targets, clusters, signaling pathways and biological processes were found. Cytology experiment shows that baicalin can inhibit the proliferation, migration and invasion of breast cancer MDA-MB-231 cells in vitro (P < 0.05). The results of qPCR showed that baicalin increase the expression of E-cadherin mRNA, and decrease the expression of vimentin, β-catenin, c-Myc and MMP-7 mRNA in LPS-induced breast cancer MDA-MB-231 cells (P < 0.05).

CONCLUSION

Baicalin may achieve anti-tumor effects through regulating the targets, biological processes and pathways found in this research.

Exploring Pharmacological Mechanisms of Xiang Ju Tablets in the Treatment of Allergic Rhinitis via a Network Pharmacology Approach

In this study, allergic rhinitis (AR) disease targets and Xiang Ju tablet-associated targets were determined through the use of databases for the identification of putative therapeutic targets and then combined. After the production of a putative therapeutic target interaction network for Xiang Ju tablets against AR, topological analysis was used to determine the core targets of Xiang Ju tablets in AR treatment. For all putative therapeutic targets, analyses of biological function and pathway enrichment were performed to optimize the biological processes and key signaling pathways of Xiang Ju tablets in AR treatment. The top 5 therapeutic targets of Xiang Ju tablets in AR treatment were identified and included CXCL8, IL1B, IL6, IL10, and TNF. The biological processes, molecular functions, and cell composition related to the use of Xiang Ju tablets in AR treatment were predominantly associated with cytokine production, regulation of protein secretion, and regulation of peptide secretion; cytokine activity, cytokine receptor binding, and receptor ligand activity; and platelet alpha granule lumen, collagen-containing extracellular matrix, and platelet alpha granule. In addition, the top 64 key signaling pathways were identified.

Uncovering the pharmacological mechanism of Carthamus tinctorius L. on cardiovascular disease by a systems pharmacology approach

Carthamus tinctorius L. is widely used in traditional Chinese medicines for the treatment of cardiovascular disease. However, our current understanding of the molecular mechanisms supporting its clinical application still lags behind. In this study, a systems pharmacology approach integrating drug-likeness evaluation, oral bioavailability prediction, target exploration, GO enrichment analysis, KEGG pathway performance and network construction was adopted to explore its therapeutic mechanism. A total of 21 active ingredients contained in Carthamus tinctorius L. and 113 major proteins were screened out as effective players in the treatment of cardiovascular disease through some related pathways. And the association among the active ingredients, major hubs and main pathways was investigated, implying the potential biological progression of Carthamus tinctorius L. acting on cardiovascular disease. Importantly, the majority of hubs and pathways were found to be highly related with platelet activation process. Core genes that can be regulated by Carthamus tinctorius L. in platelet activation pathway were PRKACA, PIK3R1, MAPK1, PPP1CC, PIK3CA and SYK, and they may play a central role in suppressing platelet aggregation. The systems pharmacology approach used in this study may provide a feasible tool to clarify the mechanism of traditional Chinese medicines and further develop their therapeutic potentials.

A Network Pharmacology Study on the Active Ingredients and Potential Targets of Tripterygium wilfordii Hook for Treatment of Rheumatoid Arthritis

Traditional Chinese medicine has specific effect on some chronic diseases in clinic, especially in rheumatic diseases. Tripterygium wilfordii Hook (TWH) is a traditional Chinese medicine commonly used in the treatment of rheumatoid arthritis (RA); the unique therapeutic effect has been confirmed by a large number of research papers. TWH has many compounds that lead to its active compounds. However, the potential targets and pharmacological and molecular mechanism of its action treatment of rheumatic diseases are not entirely clear. Therefore, the network pharmacology approach is needed to further study and explore its treatment mechanism. We have successfully set up 10 networks, including four major networks and other networks. Four major networks include rheumatoid arthritis disease network, compound-compound target network of TWH, TWH compound target-rheumatoid arthritis disease network, and TWH-rheumatoid arthritis disease-mechanism network. Other networks consist of RA disease and TWH related targets clusters, biological processes, and pathways network. Our study successfully predicted, explained, and confirmed the TWH of RA disease molecular synergy and found the potential of RA related targets, cluster, biological process, and pathways. This study not only provides prompts to the researcher who explores pharmacological and biological molecular mechanism of TWH applying to RA disease, but also proves a feasible method for discovering potential activated compounds from Chinese herbs.

Network Pharmacology in Research of Chinese Medicine Formula: Methodology, Application and Prospective

Chinese medicine (CM) is usually prescribed as CM formula to treat disease. The lack of effective research approach makes it difficult to elucidate the molecular mechanisms of CM formula owing to its complicated chemical compounds. Network pharmacology is increasingly applied in CM formula research in recent years, which is identified suitable for the study of CM formula. In this review, we summarized the methodology of network pharmacology, including network construction, network analysis and network verification. The aim of constructing a network is to achieve the interaction between the bioactive compounds and targets and the interaction between various targets, and then find out and validate the key nodes via network analysis and network verification. Besides, we reviewed the application in CM formula research, mainly including targets discovery, bioactive compounds screening, toxicity evaluation, mechanism research and quality control research. Finally, we proposed prospective in the future and limitations of network pharmacology, expecting to provide new strategy and thinking on study for CM formula.

Network Pharmacology Databases for Traditional Chinese Medicine: Review and Assessment

The research field of systems biology has greatly advanced and, as a result, the concept of network pharmacology has been developed. This advancement, in turn, has shifted the paradigm from a “one-target, one-drug” mode to a “network-target, multiple-component-therapeutics” mode. Network pharmacology is more effective for establishing a “compound-protein/gene-disease” network and revealing the regulation principles of small molecules in a high-throughput manner. This approach makes it very powerful for the analysis of drug combinations, especially Traditional Chinese Medicine (TCM) preparations. In this work, we first summarized the databases and tools currently used for TCM research. Second, we focused on several representative applications of network pharmacology for TCM research, including studies on TCM compatibility, TCM target prediction, and TCM network toxicology research. Third, we compared the general statistics of several current TCM databases and evaluated and compared the search results of these databases based on 10 famous herbs. In summary, network pharmacology is a rational approach for TCM studies, and with the development of TCM research, powerful and comprehensive TCM databases have emerged but need further improvements. Additionally, given that several diseases could be treated by TCMs, with the mediation of gut microbiota, future studies should focus on both the microbiome and TCMs to better understand and treat microbiome-related diseases.

Network Pharmacology and Bioinformatics Approach Reveals the Therapeutic Mechanism of Action of Baicalein in Hepatocellular Carcinoma

Liver cancer is the fourth leading cause of cancer death worldwide, and hepatocellular carcinoma (HCC) accounts for the greatest proportion of these deaths. Baicalein, a flavonoid isolated from the root of Scutellariae radix, is considered a potential candidate to treat HCC. However, the underlying molecular mechanisms remain poorly understood. In the present study, a network pharmacological approach was combined with microarray data (GSE95504) acquired from the Gene Expression Omnibus database to reveal the therapeutic mechanisms of action of baicalein at a systemic level. We identified 38 baicalein targets and 76 differently expressed genes (DEGs) following treatment with baicalein, including 55 upregulated and 21 downregulated genes. The DEGs were significantly enriched in the biological functions of apoptosis, endoplasmic reticulum stress, and PERK-mediated unfolded protein response. Protein-protein interaction (PPI) network construction and topological screening revealed a core module of PPIs including two baicalein targets, TP53 and CDK1, and two downregulated DEGs, HSPA1A and HSPA1B. Expression and survival data for these genes in the module derived from Gene Expression Profiling Interactive Analysis (GEPIA) were subjected to Kaplan–Meier analysis of overall survival and disease-free survival. Overexpression of CDK1, BRCA1, TUBB, HSPA1A, HSPA1B, and HSPA4 was associated with significantly worse overall survival, while overexpression of CDK1, CLU7, BRCA1, and TUBB was associated with significantly worse disease-free survival. These data suggest that baicalein exerts therapeutic effects against HCC via a PPI network involving TP53, CDK1, HSPA1A, and HSPA1B.

Pairwise combinations of chemical compounds that delay yeast chronological aging through different signaling pathways display synergistic effects on the extent of aging delay

We have recently discovered six plant extracts that delay yeast chronological aging. Most of them affect different nodes, edges and modules of an evolutionarily conserved network of longevity regulation that integrates certain signaling pathways and protein kinases; this network is also under control of such aging-delaying chemical compounds as spermidine and resveratrol. We have previously shown that, if a strain carrying an aging-delaying single-gene mutation affecting a certain node, edge or module of the network is exposed to some of the six plant extracts, the mutation and the plant extract enhance aging-delaying efficiencies of each other so that their combination has a synergistic effect on the extent of aging delay. We therefore hypothesized that a pairwise combination of two aging-delaying plant extracts or a combination of one of these plant extracts and spermidine or resveratrol may have a synergistic effect on the extent of aging delay only if each component of this combination targets a different element of the network. To test our hypothesis, we assessed longevity-extending efficiencies of all possible pairwise combinations of the six plant extracts or of one of them and spermidine or resveratrol in chronologically aging yeast. In support of our hypothesis, we show that only pairwise combinations of naturally-occurring chemical compounds that slow aging through different nodes, edges and modules of the network delay aging in a synergistic manner.

Network pharmacology and RNA sequencing studies on triterpenoid saponins from Bupleurum chinense for the treatment of breast cancer

Breast cancer remains the most commonly diagnosed malignancy among women, which is frequently associated with adverse side-effects and high metastasis. Bupleurum chinense DC. has been empirically and extensively used as the core prescription for more than half of Chinese formulations for the adjuvant therapy of breast cancer, and its biological activity against breast cancer has been proven by both in vitro and in vivo experiments. Saikosaponin compounds are the characteristic constituent of B. chinense, which exhibit significant cytotoxicity toward several cancer cells. However, the specific mechanisms of these compounds in the treatment of breast cancer have not been comprehensively understood. Therefore, we aimed to determine more potentially therapeutic targets and investigate the biological mechanisms of B. chinense. In the present study, we adopted network pharmacology and bioinformatics analysis to facilitate this requirement. Consequently, the network analysis revealed that saikosaponin-f (39), saikosaponin-d (14), saikosaponin-c (26), saikosaponin-h (54), saikosaponin-g (41), 3′′,6′′-O-diacetylsaikosaponin-d (20), 11α-methoxy-saikosaponin-f (40), and 6′′-O-acetylsaikosaponin-b₁ (48) might play important roles in the treatment of breast cancer. In addition, the apoptosis regulator Bcl-2 (BCL-2), C-X-C chemokine receptor type 4 (CXCR4), probable ATP-dependent RNA helicase DDX5 (DDX5), protein kinase C alpha (PRKCA), and proto-oncogene tyrosine-protein kinase Src (SRC) were the potential therapeutic targets that exhibited intense interactions. Mechanistically, a gene enrichment analysis revealed that the action of B. chinense against breast cancer was achieved by the regulation of several biological signaling pathways, such as pathways in cancer, PI3K-Akt signaling pathway, EGFR tyrosine kinase inhibitor resistance, microRNAs in cancer, etc. More importantly, we verified that the predictions involving saikosaponin-d by the cytotoxicity assay, apoptosis analysis, and RNA sequencing methods were partly consistent with those obtained from the network pharmacology prediction.

The network pharmacology and RNA sequencing studies were used to explore potential therapeutic targets and biological mechanisms of B. chinense for the treatment of breast cancer.

Uncovering the mechanism of Maxing Ganshi Decoction on asthma from a systematic perspective: A network pharmacology study

Maxing Ganshi Decoction (MXGSD) is used widely for asthma over thousands of years, but its underlying pharmacological mechanisms remain unclear. In this study, systematic and comprehensive network pharmacology was utilized for the first time to reveal the potential pharmacological mechanisms of MXGSD on asthma. Specifically, we collected 141 bioactive components from the 600 components in MXGSD, which shared 52 targets common to asthma-related ones. In-depth network analysis of these 52 common targets indicated that asthma might be a manifestation of systemic neuro-immuno-inflammatory dysfunction in the respiratory system, and MXGSD could treat asthma through relieving airway inflammation, improving airway remodeling, and increasing drug responsiveness. After further cluster and enrichment analysis of the protein-protein interaction network of MXGSD bioactive component targets and asthma-related targets, we found that the neurotrophin signaling pathway, estrogen signaling pathway, PI3K-Akt signaling pathway, and ErbB signaling pathway might serve as the key points and principal pathways of MXGSD gene therapy for asthma from a systemic and holistic perspective, and also provides a novel idea for the development of new drugs for asthma.

Investigate the mechanisms of Chinese medicine Fuzhengkangai towards EGFR mutation-positive lung adenocarcinomas by network pharmacology

BACKGROUND

Chinese traditional herbal medicine Fuzhengkangai (FZKA) formulation combination with gefitinib can overcome drug resistance and improve the prognosis of lung adenocarcinoma patients. However, the pharmacological and molecular mechanisms underlying the active ingredients, potential targets, and overcome drug resistance of the drug are still unclear. Therefore, it is necessary to explore the molecular mechanism of FZKA.

METHODS

A systems pharmacology and bioinformatics-based approach was employed to investigate the molecular pathogenesis of EGFR-TKI resistance with clinically effective herb formula. The differential gene expressions between EGFR-TKI sensitive and resistance cell lines were calculated and used to find overlap from targets as core targets. The prognosis of core targets was validated from the cancer genome atlas (TCGA) database by Cox regression. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment is applied to analysis core targets for revealing mechanism in biology.

RESULTS

The results showed that 35 active compounds of FZKA can interact with eight core targets proteins (ADRB2, BCL2, CDKN1A, HTR2C, KCNMA1, PLA2G4A, PRKCA and LYZ). The risk score of them were associated with overall survival and relapse free time (HR = 6.604, 95% CI: 2.314-18.850; HR = 5.132, 95% CI: 1.531-17.220). The pathway enrichment suggested that they involved in EGFR-TKI resistance and non-small cell lung cancer pathways, which directly affect EGFR-TKI resistance. The molecular docking showed that licochalcone a and beta-sitosterol can closely bind two targets (BCL2 and PRKCA) that involved in EGFR-TKI resistance pathway.

CONCLUSIONS

This study provided a workflow for understanding mechanism of CHM for against drug resistance.

Exploring the potential pharmacodynamic material basis and pharmacologic mechanism of the Fufang-Xialian-Capsule in chronic atrophic gastritis by network pharmacology approach based on the components absorbed into the blood

In this study, a new network pharmacology approach based on the components absorbed into the blood was used to investigate the pharmacodynamic material basis and the pharmacologic mechanism of the Fufang-Xialian-Capsule (FXL) in treating chronic atrophic gastritis (CAG). Initially, we confirmed the components absorbed into the blood by ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Then, the network approach, which was based on the results of components absorbed into the blood, was used to analyse the pharmacodynamic material basis and the pharmacologic mechanism of FXL on treating CAG. As a result, 22 absorbed components were found in rat plasma. Given the results of the absorption analysis of the components, eight pathways associated with CAG development were found. The targets linked to these pathways are the drug targets of FXL in CAG treatment. The components associated with these targets are the potential pharmacodynamic material basis and exert synergy in regulating pathways during CAG treatment.

Exploring the Pharmacological Mechanism of Danzhi Xiaoyao Powder on ER-Positive Breast Cancer by a Network Pharmacology Approach

Background

Breast cancer is the most common malignancy among women worldwide, but the long-term endocrine therapy is frequently associated with adverse side effects. Danzhi Xiaoyao powder (DXP) is a herbal formula that has an effect on breast cancer, especially ER-positive breast cancer. However, the active compounds, potential targets, and pharmacological and molecular mechanism of its action against cancer remain unclear.

Methods

A network pharmacology approach comprising drug-likeness evaluation, oral bioavailability prediction, Caco-2 permeability prediction, multiple compound target prediction, multiple known target collection, breast cancer genes collection, and network analysis has been used in this study.

Results

Four networks are set up—namely, ER-positive breast cancer network, compound-compound target network of DXP, DXP-ER-positive breast cancer network, and compound-known target-ER-positive breast cancer network. Some ER-positive breast cancer and DXP related targets, clusters, biological processes, and pathways, and several potential anticancer compounds are found.

Conclusion

This network analysis successfully predicted, illuminated, and confirmed the molecular synergy of DXP for ER-positive breast cancer, got potential anticancer active compounds, and found the potential ER-positive breast cancer associated targets, cluster, biological processes, and pathways. This work also provides clues to the researcher who explores ethnopharmacological or/and herbal medicine's or even multidrugs' various synergies.

Ethnopharmacological implications of quantitative and network analysis for traditional knowledge regarding the medicinal use of animals by indigenous people in Wolchulsan National Park, Korea

ETHNOPHARMACOLOGICAL RELEVANCE

The purpose of this study was to record, analyze, and identify ethnopharmacological implications for oral traditional knowledge regarding the medicinal use of animals by indigenous people living in Wolchulsan National Park, Korea.

MATERIALS AND METHODS

Data were collected through interviews, informal meetings, open and group discussions, and observations guided by semi-structured questionnaires. Data were analyzed via quantitative analysis of informant consensus factor and fidelity level, and network analysis, including centrality and clustering analysis.

RESULTS

A total of 46 families, 59 genera, and 60 species of animals, as well as 373 methods of usage, were recorded. Fish comprised 31.7% of the total animal species recorded, followed by mammals at 20.0%, arthropods at 18.3%, and mollusks at 11.7%. Of these animals, 48.0% were utilized as food and 46.1% for medicinal use. Quantitative analysis showed that the category with the highest degree of consensus from informants was veterinary ailments (informant consensus factor value, 0.96). This was followed by poisonings (0.93), pains (0.92), genitourinary system disorders (0.91), cuts and wounds (0.89), and other medical conditions. The lowest degree of consensus was for skin diseases and disorders (0.57). There were 8 species of animals with a fidelity level of 100%, after eliminating from the animals analyzed that were mentioned only once. Finally, using network analysis, Gallus gallus domesticus and Gloydius brevicaudus were defined as species with meaningful medicinal use, while lack of vigor and lung diseases were defined as significant ailments in the study area.

CONCLUSION

This study validates that local communities use animals not only for food but also for medicinal purposes as crucial therapeutic measures. Therefore, the conservation of fauna and preservation of traditional knowledge need to be seriously considered to maintain the health and well-being of the local communities. Network analysis clarified the series of ailments for which each animal species is preferentially used and helped confirm the order of priority when prescribing animal components for medicinal use. The traditional knowledge recorded in the present study will provide the basic data to develop new medicines for the bioindustry.

A Network Pharmacology Approach to Uncover the Multiple Mechanisms of Hedyotis diffusa Willd. on Colorectal Cancer

Background

As one of the most frequently diagnosed cancer diseases globally, colorectal cancer (CRC) remains an important cause of cancer-related death. Although the traditional Chinese herb Hedyotis diffusa Willd. (HDW) has been proven to be effective for treating CRC in clinical practice, its definite mechanisms have not been completely deciphered.

Objective

The aim of our research is to systematically explore the multiple mechanisms of HDW on CRC.

Methods

This study adopted the network pharmacology approach, which was mainly composed of active component gathering, target prediction, CRC gene collection, network analysis, and gene enrichment analysis.

Results

The network analysis showed that 10 targets might be the therapeutic targets of HDW on CRC, namely, HRAS, PIK3CA, KRAS, TP53, APC, BRAF, GSK3B, CDK2, AKT1, and RAF1. The gene enrichment analysis implied that HDW probably benefits patients with CRC by modulating pathways related to cancers, infectious diseases, endocrine system, immune system, nervous system, signal transduction, cellular community, and cell motility.

Conclusions

This study partially verified and predicted the pharmacological and molecular mechanism of HDW against CRC from a holistic perspective, which will also lay a foundation for the further experimental research and clinical rational application of HDW.

Systematic Understanding of the Mechanism of Baicalin against Ischemic Stroke through a Network Pharmacology Approach

Ischemic stroke is accompanied by high mortality and morbidity rates. At present, there is no effective clinical treatment. Alternatively, traditional Chinese medicine has been widely used in China and Japan for the treatment of ischemic stroke. Baicalin is a flavonoid extracted from Scutellaria baicalensis that has been shown to be effective against ischemic stroke; however, its mechanism has not been fully elucidated. Based on network pharmacology, we explored the potential mechanism of baicalin on a system level. After obtaining baicalin structural information from the PubChem database, an approach combined with literature mining and PharmMapper prediction was used to uncover baicalin targets. Ischemic stroke-related targets were gathered with the help of DrugBank, Online Mendelian Inheritance in Man (OMIM), Genetic Association Database (GAD), and Therapeutic Target Database (TTD). Protein-protein interaction (PPI) networks were constructed through the Cytoscape plugin BisoGenet and analyzed by topological methods. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out via the Database for Annotation, Visualization, and Integrated Discovery (DAVID) server. We obtained a total of 386 potential targets and 5 signaling pathways, including mitogen-activated protein kinase (MAPK), phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT), hypoxia-inducible factor-1 (HIF-1), nuclear factor kappa B (NF-κB), and forkhead box (FOXO) signaling pathways. GO analysis showed that these targets were associated with antiapoptosis, antioxidative stress, anti-inflammation, and other physiopathological processes that are involved in anti-ischemic stroke effects. In summary, the mechanism of baicalin against ischemic stroke involved multiple targets and signaling pathways. Our study provides a network pharmacology framework for future research on traditional Chinese medicine.

Uncovering the Pharmacological Mechanism of Astragalus Salvia Compound on Pregnancy-Induced Hypertension Syndrome by a Network Pharmacology Approach

To uncover the pharmacological mechanism of Astragalus Salvia compound (ASC) on pregnancy-induced hypertension syndrome (PIH), to provide useful information for clinical, as well as to connect the basic and clinical by a network pharmacological approach, we used network pharmacological approach. We collected ASC's compounds by traditional Chinese Medicine databases, and input them into PharmMapper to got their targets. Then we acquired PIH targets from Genecards and OMIM, collected the interactions of all the targets and other human proteins via String and INACT. We also constructed the network by Cytoscape and analyze it by MCODE so as to get clusters. Finally, we put all the targets of clusters into DAVID to do GO enrichment analysis. After these, four networks are constructed by Cytoscape; they are PIH network, compound-compound target network of ASC, ASC-PIH network, and compound target-PIH target-other human proteins' PPI network. According to the results, we think that ASC may directly regulate several biological processes and their genes in "endothelial cell activation and injury" and "placental or trophoblast cell ischemia" models to treat PIH. And it may indirectly act on the rest of the biological process to treat PIH or may not.