scholarly journals An Integrative Metabolomic and Network Pharmacology Study Revealing the Regulating Properties of Xihuang Pill That Improves Anlotinib Effects in Lung Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Chunyu Li ◽  
Zhihong Wang ◽  
Wei Chen ◽  
Bo Cao ◽  
Mingyu Zhang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Acid Metabolism ◽  
Interaction Network ◽  
Complementary Therapy ◽  
Underlying Mechanism ◽  
Inhibitory Effect ◽  
Biologically Active ◽  
Untargeted Metabolomics ◽  
Network Pharmacology ◽  
Active Components

Lung cancer ranks as a leading cause of death. Although targeted therapies usually trigger profound initial patient responses, these effects are transient due to drug resistance and severe side effects. Xihuang Pill (XHW) is a popular Chinese medicine formula that might benefit cancer patients when used as a complementary therapy. However, its underlying mechanism when combined with anticancer drugs is not clearly understood. Here, we used an integrated strategy to reveal the regulatory properties of XHW in increasing the antitumor activity of anlotinib in lung cancer. We evaluated the anti-lung cancer effect of XHW combined with anlotinib in mice bearing Lewis lung carcinoma (LLC). We applied untargeted metabolomics to identify the differences metabolism and found that XHW improved the effects of anlotinib on lung cancer. The components and targets related to the effects of XHW treatment on lung cancer were obtained through network pharmacology. Then, by integrating the biologically active components of XHW and anlotinib as well as the treatment-responsive metabolites and their related targets, an interaction network was constructed to evaluate the combination therapy. Finally, important protein candidates for this response were verified by immunohistochemistry of tumor tissues. The results showed that XHW significantly improved the inhibitory effect of anlotinib on tumor growth in LLC-bearing mice. Additionally, 12 differentially-abundant metabolites were identified by untargeted metabolomics in the XHW/anlotinib group compared with the XHW or anlotinib groups, and they were mainly enriched in fatty acid metabolism, lipid metabolism and amino acid metabolism pathways. Anlotinib, 23 components in Shexiang, 2 components in Niuhuang, 30 components in Ruxiang and 60 components in Moyao work together to act on 30 targets to regulate hexadecanoic acid (also named palmitic acid), linoleic acid, lactosylceramide, adrenaline, arachidonic acid and lysoPC(18:1(9Z)). The results of immunohistochemistry showed that XHW combined with anlotinib reduced the expression of PDGFRA in tumors. Overall, the key metabolites of XHW that enhances the efficacy of anlotinib were regulated by a multicomponent and multitarget interaction network. Our results suggested that anlotinib combined with XHW may be a promising strategy for the treatment of lung cancer.

scholarly journals Systematic Analysis of the Multiple Bioactivities of Green Tea through a Network Pharmacology Approach

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Shoude Zhang ◽  
Lei Shan ◽  
Qiao Li ◽  
Xia Wang ◽  
Shiliang Li ◽  
...  
Keyword(s):  
Green Tea ◽  
Homo Sapiens ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Biologically Active ◽  
Network Pharmacology ◽  
Literature Mining ◽  
Pathway Enrichment Analysis ◽  
Active Components ◽  
Systematic Analysis

During the past decades, a number of studies have demonstrated multiple beneficial health effects of green tea. Polyphenolics are the most biologically active components of green tea. Many targets can be targeted or affected by polyphenolics. In this study, we excavated all of the targets of green tea polyphenolics (GTPs) though literature mining and target calculation and analyzed the multiple pharmacology actions of green tea comprehensively through a network pharmacology approach. In the end, a total of 200Homo sapienstargets were identified for fifteen GTPs. These targets were classified into six groups according to their related disease, which included cancer, diabetes, neurodegenerative disease, cardiovascular disease, muscular disease, and inflammation. Moreover, these targets mapped into 143 KEGG pathways, 26 of which were more enriched, as determined though pathway enrichment analysis and target-pathway network analysis. Among the identified pathways, 20 pathways were selected for analyzing the mechanisms of green tea in these diseases. Overall, this study systematically illustrated the mechanisms of the pleiotropic activity of green tea by analyzing the corresponding “drug-target-pathway-disease” interaction network.

scholarly journals Mechanism of Compound Houttuynia Mixture as an Anti-COVID-19 Drug Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110167
Author(s):  
Xing-Pan Wu ◽  
Tian-Shun Wang ◽  
Zi-Xin Yuan ◽  
Yan-Fang Yang ◽  
He-Zhen Wu
Keyword(s):  
Molecular Docking ◽  
Target Prediction ◽  
Interaction Network ◽  
Scientific Basis ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Discovery Studio ◽  
The Core ◽  
Pathway Annotation

Objective To explore the anti-COVID-19 active components and mechanism of Compound Houttuynia mixture by using network pharmacology and molecular docking. Methods First, the main chemical components of Compound Houttuynia mixture were obtained by using the TCMSP database and referring to relevant chemical composition literature. The components were screened for OB ≥30% and DL ≥0.18 as the threshold values. Then Swiss Target Prediction database was used to predict the target of the active components and map the targets of COVID-19 obtained through GeneCards database to obtain the gene pool of the potential target of COVID-19 resistance of the active components of Compound Houttuynia mixture. Next, DAVID database was used for GO enrichment and KEGG pathway annotation of targets function. Cytoscape 3.8.0 software was used to construct a “components-targets-pathways” network. Then String database was used to construct a “protein-protein interaction” network. Finally, the core targets, SARS-COV-2 3 Cl, ACE2 and the core active components of Compound Houttuyna Mixture were imported into the Discovery Studio 2016 Client database for molecular docking verification. Results Eighty-two active compounds, including Xylostosidine, Arctiin, ZINC12153652 and ZINC338038, were screened from Compound Houttuyniae mixture. The key targets involved 128 targets, including MAPK1, MAPK3, MAPK8, MAPK14, TP53, TNF, and IL6. The HIF-1 signaling, VEGF signaling, TNF signaling and another 127 signaling pathways associated with COVID-19 were affected ( P < 0.05). From the results of molecular docking, the binding ability between the selected active components and the core targets was strong. Conclusion Through the combination of network pharmacology and molecular docking technology, this study revealed that the therapeutic effect of Compound Houttuynia mixture on COVID-19 was realized through multiple components, multiple targets and multiple pathways, which provided a certain scientific basis of the clinical application of Compound Houttuynia mixture.

scholarly journals The Underlying Mechanism of Chinese Herb of Regulating Marrow in the Treatment of  Osteonecrosis of the Femoral Head Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xiaojian Wang ◽  
Rui Wang ◽  
Ting Xu ◽  
Hongting Jin ◽  
Peijian Tong ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Active Components ◽  
Pathway Enrichment

Abstract Background The lesion of marrow is a crucial factor in orthopedic diseases, which is recognized by orthopedics-traumatology expert from "Zhe-School of Chinese Medicine". The Chinese herbs of regulating marrow has been widely used to treat osteonecrosis of the femoral head (ONFH) in China, while the interaction mechanisms were still elucidated. Thus, we conducted this study to explore the underlying mechanism of the five highest-frequency Chinese herbs of regulating marrow(HF-CHRM) in the treatment of ONFH with the aid of network pharmacology(NP) and molecular docking(MD). Methods The active components and potential targets of HF-CHRM were obtained through several online databases, such as Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), UniProt database. The gene targets related to ONFH were collected with the help of the OMIM and GeneCards disease-related databases. The "drug- component-target-disease" network and protein-protein interaction(PPI) network of the drug and disease intersecting targets were constructed by using Cytoscape software and the STRING database. R software was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The MD of critical components and targets was carried out using Autodock Vina and Pymol to validate the binding affinity. Results A total of 54 active components, 1074 drug targets and 195 gene targets were obtained. There were 1219 ONFH related targets. 39 drug and disease intersection targets(representative genes: IL6, TP53, VEGFA, ESR1, IL1B) were obtained and considered potential therapeutic targets. 1619 items were obtained by the GO enrichment analysis, including 1517 biological processes, 10 cellular components and 92 molecular functions, which is mainly related to angiogenesis, bone and lipid metabolism and inflammatory reaction. The KEGG pathway enrichment analysis revealed 119 pathways, including AGE-RAGE signaling pathway, PI3K-Akt signaling pathway and IL-17 signaling pathway. MD results showed that quercetin, wogonin, and kaempferol active components had good affinity with IL6, TP53, and VEGFA core proteins. Conclusion The HF-CHRM can treat ONFH by multi-component, multi-target, and multi-pathway comprehensive action.

scholarly journals The FDA-Approved Anti-Asthma Medicine Ciclesonide Inhibits Lung Cancer Stem Cells through Hedgehog Signaling-Mediated SOX2 Regulation

2020 ◽  
Vol 21 (3) ◽  
pp. 1014 ◽  
Author(s):  
Hack Sun Choi ◽  
Su-Lim Kim ◽  
Ji-Hyang Kim ◽  
Dong-Sun Lee
Keyword(s):  
Lung Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Small Interfering Rna ◽  
Hedgehog Signaling ◽  
Underlying Mechanism ◽  
Inhibitory Effect ◽  
Protein Levels ◽  
Lung Cancer Stem Cells ◽  
Interfering Rna

Ciclesonide is an FDA-approved glucocorticoid (GC) used to treat asthma and allergic rhinitis. However, its effects on cancer and cancer stem cells (CSCs) are unknown. Our study focuses on investigating the inhibitory effect of ciclesonide on lung cancer and CSCs and its underlying mechanism. In this study, we showed that ciclesonide inhibits the proliferation of lung cancer cells and the growth of CSCs. Similar glucocorticoids, such as dexamethasone and prednisone, do not inhibit CSC formation. We show that ciclesonide is important for CSC formation through the Hedgehog signaling pathway. Ciclesonide reduces the protein levels of GL1, GL2, and Smoothened (SMO), and a small interfering RNA (siRNA) targeting SMO inhibits tumorsphere formation. Additionally, ciclesonide reduces the transcript and protein levels of SOX2, and an siRNA targeting SOX2 inhibits tumorsphere formation. To regulate breast CSC formation, ciclesonide regulates GL1, GL2, SMO, and SOX2. Our results unveil a novel mechanism involving Hedgehog signaling and SOX2 regulated by ciclesonide in lung CSCs, and also open up the possibility of targeting Hedgehog signaling and SOX2 to prevent lung CSC formation.

scholarly journals A Network Pharmacology-Based Study on the Anti-Lung Cancer Effect of Dipsaci Radix

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Jiayan Wu ◽  
Shengkun Hong ◽  
Xiankuan Xie ◽  
Wangmi Liu
Keyword(s):  
Lung Cancer ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Active Compounds

Objective. Dipsaci Radix (DR) has been used to treat fracture and osteoporosis. Recent reports have shown that myeloid cells from bone marrow can promote the proliferation of lung cancer. However, the action and mechanism of DR has not been well defined in lung cancer. The aim of the present study was to define molecular mechanisms of DR as a potential therapeutic approach to treat lung cancer. Methods. Active compounds of DR with oral bioavailability ≥30% and drug-likeness index ≥0.18 were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform. The potential target genes of the active compounds and bone were identified by PharmMapper and GeneCards, respectively. The compound-target network and protein-protein interaction network were built by Cytoscape software and Search Tool for the Retrieval of Interacting Genes webserver, respectively. GO analysis and pathway enrichment analysis were performed using R software. Results. Our study demonstrated that DR had 6 active compounds, including gentisin, sitosterol, Sylvestroside III, 3,5-Di-O-caffeoylquinic acid, cauloside A, and japonine. There were 254 target genes related to these active compounds as well as to bone. SRC, AKT1, and GRB2 were the top 3 hub genes. Metabolisms and signaling pathways associated with these hub genes were significantly enriched. Conclusions. This study indicated that DR could exhibit the anti-lung cancer effect by affecting multiple targets and multiple pathways. It reflects the traditional Chinese medicine characterized by multicomponents and multitargets. DR could be considered as a candidate for clinical anticancer therapy by regulating bone physiological functions.

scholarly journals Systemic Elucidate The Potential Bioactive Compounds and Hypoglycemic Mechanism of Polygonum Multiflorum Based on Network Pharmacology

2020 ◽  
Author(s):  
Yunfei Song ◽  
Jianbo Yang ◽  
Wenguang Jing ◽  
Qi Wang ◽  
Yue Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Bioactive Compounds ◽  
Acid Metabolism ◽  
Osteoclast Differentiation ◽  
Interaction Network ◽  
Arachidonic Acid Metabolism ◽  
Hypoglycemic Effect ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Polygonum Multiflorum

Abstract Background: Diabetes is a complex metabolic disease characterized by hyperglycemia, plaguing the whole world. However, the action mode of multi-component and multi-target for traditional Chinese medicine (TCM) could be a promising treatment of diabetes mellitus. According to the previous research, the TCM of polygonum multiflorum (PM) showed noteworthy hypoglycemic effect. Up to now, its hypoglycemic active ingredients and mechanism of action are not yet clear. In this study, network pharmacology was employed to elucidate the potential bioactive compounds and hypoglycemic mechanism of Polygonum multiflorum (PM).Methods: First, the compounds with good pharmacokinetic properties were screened from the self-established library of PM, and the targets of these compounds were predicted and collected through database. Relevant targets of diabetes were summarized by searching database. The intersection targets of compound-targets and disease-targets were obtained soon. Secondly, the interaction net between the compounds and the filtered targets was established. These key targets were enriched and analyzed by PPI analysis, molecular docking verification. Finally, the key genes were used to find the biologic pathway and explain the therapeutic mechanism by GO and KEGG analysis. Results: In this study, 29 hypoglycemic components and 63 hypoglycemic targets of PM were filtrated based on online network database. Then the component-target interaction network was constructed and five key components resveratrol, apigenin, kaempferol, quercetin and luteolin were further obtained. Sequential studies turned out, AKT1, EGFR, ESR1, PTGS2, MMP9, MAPK14, and KDR were the common key targets. Docking studies indicated that the bioactive compounds could stably bind the pockets of target proteins. There were 38 metabolic pathways, including regulation of lipolysis in adipocytes, prolactin signaling pathway, TNF signaling pathway, VEGF signaling pathway, FoxO signaling pathway, estrogen signaling pathway, linoleic acid metabolism, Rap1 signaling pathway, arachidonic acid metabolism, and osteoclast differentiation closely connected with the hypoglycemic mechanism of PM.Conclusion: In summary, the study used systems pharmacology to elucidate the main hypoglycemic components and mechanism of PM. The work provided a scientific basis for the further hypoglycemic effect research of PM and its monomer components, but also provided a reference for the secondary development of PM.

scholarly journals Investigation of the Mechanisms of Neuroprotection Mediated by Lobelia Species via Computational Network Pharmacology and Molecular Modeling

2020 ◽  
Author(s):  
Qinfang Zheng ◽  
Liangzi Fang ◽  
Xiaolong Huang ◽  
Ye Wang ◽  
Shuihan Zhang
Keyword(s):  
Molecular Modeling ◽  
Neurodegenerative Diseases ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Docking Studies ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Active Components ◽  
Neuroprotective Actions ◽  
Gaba Transporter 1

Abstract BackgroundSeveral species of the medicinally valuable genus Lobelia (Campanulaceae) exhibit neuroprotection. While the neuroprotective mechanisms of some components (e.g. lobeline, lobelanine, and lobelanidine) belonging to the L. nicotianaefolia or L. inflata are extensively characterized, there remains the need to study and elucidate the mechanism of action of other species and their active components. In this work, we have studied the neuroprotective mechanism of the pharmacokinetically favorable active compounds of 17 Lobelia species.MethodsNetwork pharmacology approach and molecular modeling were employed. We have conducted drug-likeness evaluation, oral bioavailability prediction followed by the Gene Ontology (GO) terms and pathways enrichment analysis, protein-protein and protein-compound interaction network construction and analysis, and molecular docking studies. Five neurodegenerative diseases viz. Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, epilepsy, and Amyotrophic lateral sclerosis along with the common neuroprotection mechanism-associated genes were evaluated.ResultsWe revealed the neuroprotective mechanism of the active ingredients of Lobelia species. Our study strongly indicates that 12 unique active ingredients viz. luteolin, kaempferol, acacetin, chryseriol, norlobelanine, lobelanine, 2-[(2R,6S)-6-[(2R)-2-hydroxy-2-phenylethyl]-1-methylpiperidin-2-yl]-1-phenylethanone, hydroxygenkwanin, lobelanidine, quercetin, and diosmetin regulates 31 targets within multiple signaling pathways. The nitric oxide synthase, brain (NOS1), androgen receptor (ANDR), sodium- and chloride-dependent GABA transporter 1 (SC6A1), apoptosis regulator Bcl-2 (BCL2), RAC-alpha serine/threonine-protein kinase (AKT1), cellular tumor antigen p53, apoptosis regulator BAX, and tumor necrosis factor (TNFA) were identified as the majorly regulated genes. A majority of these target proteins act via several cancer-related pathways proven to have cross-talks with the pathogenesis of neurodegenerative diseases.ConclusionsThis study explains how the active ingredients of the Lobelia species exhibit their neuroprotective actions and provide a reference basis to investigate their pharmacological effects in detail.

scholarly journals A Network Pharmacology Approach to Investigating the Mechanism of Sophorae Flavescentis Radix for the Treatment of Lung Cancer

2020 ◽  
Author(s):  
Le Yu ◽  
Kangyao Yuan ◽  
Jian Zhang ◽  
Jingya Zhao ◽  
Shuchen Pei
Keyword(s):  
Lung Cancer ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Bioactive Components ◽  
Akt Signaling Pathway ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Human Cytomegalovirus Infection ◽  
Protein Protein Interaction Network

Abstract In this study, the bioactive components and predictive targets of Sophorae Flavescentis Radix were investigated by network pharmacology analysis, so as to further elucidate its potential biological mechanism in treating lung cancer. The targets corresponding to lung cancer were obtained by OMIM and Genecards. By intersecting with the targets of Sophorae Flavescentis Radix and lung cancer, the Sophorae Flavescentis Radix-lung cancer targets were obtained. Protein-protein interaction network was constructed by an online database STRING and hub genes were screened by Cytoscape 3.7.0 software. ClusterProfiler package was used to analyze Gene ontology (GO) and KEGG enrichment of the targets in R. A total of 45 bioactive components were screened from Sophorae Flavescentis Radix, corresponding to 482 Sophorae Flavescentis Radix targets and 25019 lung cancer targets. According to the GO and KEGG enrichment analysis, Sophorae Flavescentis Radix played a therapeutic role in treating lung cancer via proteoglycans lung cancer, human cytomegalovirus infection, microRNAs in cancer, PI3K-Akt signaling pathway, etc. Seven hub genes (IL6, CASP3, EGFR, VEGFA, MYC, CCND1 and ESR1) were screened by degree algorithm. In a word, the results of this study may provide novel insights into the mechanisms of Sophorae Flavescentis Radix in treatment of lung cancer.

scholarly journals A Network Pharmacology and Molecular Docking Approach to Investigate the Anticoronavirus-Induced Diseases Effect of Yinqiao Powder Combined With Modified Sangju Decoction

2021 ◽  
Vol 16 (9) ◽  
pp. 1934578X2110352
Author(s):  
Tian-Shun Wang ◽  
Xing-Pan Wu ◽  
Qiu-Yuan Jian ◽  
Yan-Fang Yang ◽  
Wu He-Zhen
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Treatment Strategies ◽  
Interaction Network ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Common Mechanism ◽  
Active Components ◽  
Discovery Studio ◽  
The Core

Severe acute respiratory syndrome (SARS) once caused great harm in China, but now it is the coronavirus disease 2019 (COVID-19) pandemic that has become a huge threat to global health, which raises urgent demand for developing effective treatment strategies to avoid the recurrence of tragedies. Yinqiao powder, combined with modified Sangju decoction (YPCMSD), has been clinically proven to have a good therapeutic effect on COVID-19 in China. This study aimed to analyze the common mechanism of YPCMSD in the treatment of SARS and COVID-19 through network pharmacology and molecular docking and further explore the potential application value of YPCMSD in the treatment of coronavirus infections. Firstly, the active components were collected from the literature and Traditional Chinese Medicine Systems Pharmacology database platform. The COVID-19 and SARS associated targets of the active components were forecasted by the SwissTargetPrediction database and GeneCards. A protein–protein-interaction network was drawn and the core targets were obtained by selecting the targets larger than the average degree. By importing the core targets into database for annotation, visualization, and integrated discovery, enrichment analysis of gene ontology, and construction of a Kyoto Encyclopedia of genes and genomes pathway was conducted. Cytoscape 3.6.1 software was used to construct a “components–targets–pathways” network. Active components were selected to dock with acute respiratory syndrome coronavirus type 2 (SARS-COV-2) 3CL and angiotensin-converting enzyme 2 (ACE2) through Discovery Studio 2016 software. A network of “components–targets–pathways” was successfully constructed, with key targets involving mitogen-activated protein kinase 1, caspase-3 (CASP3), tumor necrosis factor (TNF), and interleukin 6. Major metabolic pathways affected were those in cancer, the hypoxia-inducible factor 1 signaling pathway, the TNF signaling pathway, the Toll-like receptor signaling pathway, and the PI3K-Akt signaling pathway. The core components, such as arctiin, scopolin, linarin, and isovitexin, showed a strong binding ability with SARS-COV-2 3CL and ACE2. We predicted that the mechanism of action of this prescription in the treatment of COVID-19 and SARS might be associated with multicomponents that bind to SARS-COV-2 3CL and ACE2, thereby regulating targets that coexpressed with them and pathways related to inflammation and the immune system.

scholarly journals Systemic elucidation on the potential bioactive compounds and hypoglycemic mechanism of Polygonum multiflorum based on network pharmacology

2020 ◽  
Author(s):  
Yunfei Song ◽  
Jianbo Yang ◽  
Wenguang Jing ◽  
Qi Wang ◽  
Yue Liu ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Bioactive Compounds ◽  
Acid Metabolism ◽  
Osteoclast Differentiation ◽  
Interaction Network ◽  
Arachidonic Acid Metabolism ◽  
Hypoglycemic Effect ◽  
Estrogen Signaling ◽  
Network Pharmacology ◽  
Polygonum Multiflorum

Abstract Background: Diabetes is a complex metabolic disease characterized by hyperglycemia, plaguing the whole world. However, the action mode of multi-component and multi-target for traditional Chinese medicine (TCM) could be a promising treatment of diabetes mellitus. According to the previous research, the TCM of polygonum multiflorum (PM) showed noteworthy hypoglycemic effect. Up to now, its hypoglycemic active ingredients and mechanism of action are not yet clear. In this study, network pharmacology was employed to elucidate the potential bioactive compounds and hypoglycemic mechanism of Polygonum multiflorum (PM).Methods: First, the compounds with good pharmacokinetic properties were screened from the self-established library of PM, and the targets of these compounds were predicted and collected through database. Relevant targets of diabetes were summarized by searching database. The intersection targets of compound-targets and disease-targets were obtained soon. Secondly, the interaction net between the compounds and the filtered targets was established. These key targets were enriched and analyzed by PPI analysis, molecular docking verification. Thirdly, the key genes were used to find the biologic pathway and explain the therapeutic mechanism by GO and KEGG analysis. Lastly, the part of potential bioactive compounds were under enzyme activity inhibition tests.Results: In this study, 29 hypoglycemic components and 63 hypoglycemic targets of PM were filtrated based on online network database. Then the component-target interaction network was constructed and five key components resveratrol, apigenin, kaempferol, quercetin and luteolin were further obtained. Sequential studies turned out, AKT1, EGFR, ESR1, PTGS2, MMP9, MAPK14, and KDR were the common key targets. Docking studies indicated that the bioactive compounds could stably bind the pockets of target proteins. There were 38 metabolic pathways, including regulation of lipolysis in adipocytes, prolactin signaling pathway, TNF signaling pathway, VEGF signaling pathway, FoxO signaling pathway, estrogen signaling pathway, linoleic acid metabolism, Rap1 signaling pathway, arachidonic acid metabolism, and osteoclast differentiation closely connected with the hypoglycemic mechanism of PM.Conclusion: In summary, the study used systems pharmacology to elucidate the main hypoglycemic components and mechanism of PM. The work provided a scientific basis for the further hypoglycemic effect research of PM and its monomer components, but also provided a reference for the secondary development of PM.

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