Systematic Understanding of Mechanism of Danggui Shaoyao San against Ischemic Stroke Using a Network Pharmacology Approach

Purpose. Danggui Shaoyao San (DSS) was developed to treat the ischemic stroke (IS) in patients and animal models. The purpose of this study was to explore its active compounds and demonstrate its mechanism against IS through network pharmacology, molecular docking, and animal experiment. Methods. All the components of DSS were retrieved from the pharmacology database of TCM system. The genes corresponding to the targets were retrieved using OMIM, CTD database, and TTD database. The herb-compound-target network was constructed by Cytoscape software. The target protein-protein interaction network was built using the STRING database. The core targets of DSS were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Then, we achieved molecular docking between the hub proteins and the key active compounds. Finally, animal experiments were performed to verify the core targets. Triphenyltetrazolium chloride (TTC) staining was used to calculate the infarct size in mice. The protein expression was determined using the Western blot. Results. Compound-target network mainly contained 51 compounds and 315 corresponding targets. Key targets contained MAPK1, SRC, PIK3R1, HRAS, AKT1, RHOA, RAC1, HSP90AA1, and RXRA FN1. There were 417 GO items in GO enrichment analysis ( p < 0.05 ) and 119 signaling pathways ( p < 0.05 ) in KEGG, mainly including negative regulation of apoptosis, steroid hormone-mediated signaling pathway, neutrophil activation, cellular response to oxidative stress, and VEGF signaling pathway. MAPK1, SRC, and PIK3R1 docked with small molecule compounds. According to the Western blot, the expression of p-MAPK 1, p-AKT, and p-SRC was regulated by DSS. Conclusions. This study showed that DSS can treat IS through multiple targets and routes and provided new insights to explore the mechanisms of DSS against IS.

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

10.21203/rs.3.rs-55927/v1 ◽

2020 ◽

Author(s):

Xiao Song ◽

Fei Guo ◽

Xiao-Chen Sun ◽

Shu-Yue Wang ◽

Yao-Hui Yuan ◽

...

Keyword(s):

Molecular Docking ◽

Signaling Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Biological Functions ◽

Active Compounds ◽

The Core ◽

The World ◽

Target Network ◽

Compound Target

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

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Study on the Multitarget Mechanism of Sanmiao Pill on Gouty Arthritis Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/9873739 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Huiqin Qian ◽

Qianqian Jin ◽

Yichen Liu ◽

Ning Wang ◽

Yuru Chu ◽

...

Keyword(s):

Molecular Docking ◽

Signaling Pathway ◽

Gouty Arthritis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Regulation Of Transcription ◽

Receptor Signaling ◽

Active Compounds ◽

Receptor Signaling Pathway ◽

Compound Target

Sanmiao pill (SMP), a Chinese traditional formula, had been used to treat gouty arthritis (GA). However, the active compounds and underlying mechanism remained unclear. Hence, network pharmacology and molecular docking were utilized to explore bioactive compounds and potential mechanism of action of SMP in treating GA. In the study, the compounds of SMP, corresponding targets, and GA-related targets were mined from various pharmacological databases. Then, herb-compound-target, compound-target, PPI, and target-pathway networks were constructed. Ultimately, molecular docking was carried out to verify the predicted results. The results indicated that 47 active compounds, 338 targets, and 144 disease targets were collected. Network analysis implied that Phellodendron chinense Schneid. played a vital role in the whole formula. Moreover, 7 compounds (quercetin, kaempferol, wogonin, rutaecarpine, baicalein, beta-sitosterol, and stigmasterol) and 4 targets (NFKB1, RELA, MAPK1, and TNF) might be the kernel compounds and targets of SMP against GA. According to GOBP and KEGG pathway enrichment analysis and target-pathway network, SMP might exert a therapeutic role in GA by regulating numerous biological processes and pathways, including lipopolysaccharide-mediated signaling pathway, positive regulation of transcription, Toll-like receptor signaling pathway, JAK-STAT signaling pathway, NOD-like receptor signaling pathway, and MAPK signaling pathway. The results of molecular docking showcased that 11 pairs of compound with targets had tight binding strength. Thereinto, 4 compounds of MAPK1 and 5 compounds of NFKB1 possessed a better combination, suggesting that MAPK1 and NFKB1 might be considered as therapeutic targets in treatment of GA. This study verified that SMP had synergistic effect on GA by multicomponents, multitargets, and multipathways.

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

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6662247 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Dandan Jiang ◽

Xiaoyan Wang ◽

Lijun Tian ◽

Yufeng Zhang

Keyword(s):

Molecular Docking ◽

Target Genes ◽

Network Pharmacology ◽

Primary Dysmenorrhea ◽

Ppi Network ◽

Active Compounds ◽

Docking Simulations ◽

Active Target ◽

Target Network ◽

Compound Target

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

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Deciphering the Molecular Targets and Mechanisms of HGWD in the Treatment of Rheumatoid Arthritis via Network Pharmacology and Molecular Docking

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/7151634 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13 ◽

Cited By ~ 1

Author(s):

Wei Liu ◽

Yihua Fan ◽

Chunying Tian ◽

Yue Jin ◽

Shaopeng Du ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Molecular Docking ◽

Signaling Pathway ◽

Differentially Expressed Genes ◽

Target Genes ◽

Differentially Expressed ◽

Network Pharmacology ◽

Active Compounds ◽

Target Proteins ◽

Target Network

Background. Huangqi Guizhi Wuwu Decoction (HGWD) has been applied in the treatment of joint pain for more than 1000 years in China. Currently, most physicians use HGWD to treat rheumatoid arthritis (RA), and it has proved to have high efficacy. Therefore, it is necessary to explore the potential mechanism of action of HGWD in RA treatment based on network pharmacology and molecular docking methods. Methods. The active compounds of HGWD were collected, and their targets were identified from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and DrugBank database, respectively. The RA-related targets were retrieved by analyzing the differentially expressed genes between RA patients and healthy individuals. Subsequently, the compound-target network of HGWD was constructed and visualized through Cytoscape 3.8.0 software. Protein-protein interaction (PPI) network was constructed to explore the potential mechanisms of HGWD on RA using the plugin BisoGenet of Cytoscape 3.8.0 software. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed in R software (Bioconductor, clusterProfiler). Afterward, molecular docking was used to analyze the binding force of the top 10 active compounds with target proteins of VCAM1, CTNNB1, and JUN. Results. Cumulatively, 790 active compounds and 1006 targets of HGWD were identified. A total of 4570 differentially expressed genes of RA with a p value <0.05 and log 2fold change > 0.5 were collected. Moreover, 739 GO entries of HGWD on RA were identified, and 79 pathways were screened based on GO and KEGG analysis. The core target gene of HGWD in RA treatment was JUN. Other key target genes included FOS, CCND1, IL6, E2F2, and ICAM1. It was confirmed that the TNF signaling pathway and IL-17 signaling pathway are important pathways of HGWD in the treatment of RA. The molecular docking results revealed that the top 10 active compounds of HGWD had a strong binding to the target proteins of VCAM1, CTNNB1, and JUN. Conclusion. HGWD has important active compounds such as quercetin, kaempferol, and beta-sitosterol, which exert its therapeutic effect on multiple targets and multiple pathways.

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Exploring the Potential Mechanism of Shennao Fuyuan Tang for Ischemic Stroke Based on Network Pharmacology and Molecular Docking

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6015702 ◽

2021 ◽

Vol 2021 ◽

pp. 1-17

Author(s):

Jia Min Li ◽

Zhen Ni Mu ◽

Tian Tian Zhang ◽

Xin Li ◽

Yan Shang ◽

...

Keyword(s):

Ischemic Stroke ◽

Molecular Docking ◽

Signal Pathway ◽

Biologically Active ◽

Network Pharmacology ◽

Ppi Network ◽

Active Components ◽

The Core ◽

Target Network ◽

Core Components

Background and Objective. Shennao Fuyuan Tang (SNFYT) is an effective herbal formula for ischemic stroke (IS). It has been in China for more than 20 years, but its effective biologically active components and underlying mechanisms remain to be elucidated. This study aimed to investigate the mechanism of action of SNFYT for the treatment of IS from both network pharmacology and molecular docking aspects. Methods. Screen the biologically active components and potential targets of SNFYT through Traditional Chinese Medicine Systems Pharmacology (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID), and related literature. In addition, DrugBank, OMIM, DisGeNET, and the Therapeutic Target Database were searched to explore the therapeutic targets of IS. The cross-targets of SNFYT potential targets and IS treatment targets were taken as candidate gene targets, and GO and KEGG enrichment analyses were performed on the candidate targets. On this basis, the SNFYT-component-target network and protein-protein interaction (PPI) network were constructed using Cytoscape 3.7.2. Finally, AutoDock was used to verify the molecular docking of core components and core targets. Results. We screened out 95 potentially active components and 143 candidate targets. SNFYT-component-target network, PPI network, and Cytoscape analysis identified four core active ingredients and 14 core targets. GO enrichment analyzed 2333 biological processes, 79 cell components, and 149 molecular functions. There are 170 KEGG-related signal pathways P < 0.05 , including the IL-17 signal pathway, TNF signal pathway, and HIF-1 signal pathway. The molecular docking results of the core components and the core targets showed good binding power. Conclusions. SNFYT may achieve the effect of treating ischemic stroke through its anti-inflammatory effect through a signal pathway with core targets as the core.

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Identification of the active substances and mechanisms of ginger for the treatment of colon cancer based on network pharmacology and molecular docking

10.21203/rs.3.rs-38111/v1 ◽

2020 ◽

Author(s):

MengMeng Zhang ◽

Dan Wang ◽

Feng Lu ◽

Rong Zhao ◽

Xun Ye ◽

...

Keyword(s):

Colon Cancer ◽

Molecular Docking ◽

Signaling Pathway ◽

Cellular Response ◽

Protein Localization ◽

Docking Simulation ◽

Estrogen Signaling ◽

Receptor Protein ◽

Network Pharmacology ◽

Active Compounds

Abstract Background: Colon cancer is increasing recently but the high cost and adverse side effects experienced always leads to treatment drop out. Zingiber officinale, commonly known as ginger, is a popular herbal medicine and this study was aimed to identify the active compounds from ginger and to investigate its anti-cancer mechanisms through network pharmacology construction. Results: Ginger compounds were discerned through the TCMSP, which were filtered by the metrics of oral bioavailability and drug likeness, and its related targets were searched. After that, the targets interacting with colon cancer were collected using Genecards, OMIM, and Drugbank databases. Six potential active compounds, 288 interacting targets in addition to 1356 disease-related targets were collected, of which 114 intersection targets were obtained. The PPI network showed that 32 targets including SRC, PIK3R1, and TP53 were identified as key targets. These targets were mainly associated with the biological processes like transmembrane receptor protein tyrosine kinase signaling pathway, regulation of cellular protein localization, cellular response to oxidative stress. KEGG enrichment manifested that ginger probably produced preventive effects against colon cancer by regulating significant signaling pathway like pathway in cancer, hepatitis B, and estrogen signaling pathway. TP53, HSP90AA1, MAPK8, JAK2, CASP3, and ERBB2 could be viewed as the most potential target proteins, which were validated by molecular docking simulation.Conclusion: This study demonstrated the multi-component, multi-target, and multi-pathway characteristics of ginger, providing novel insight for ginger compounds developed as new drug for anti-colon cancer.

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Exploring the Molecular Mechanism of Qing Guang An Granule in Treating Glaucoma Using Network Pharmacology and Molecular Docking

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/8824150 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Chen Ou ◽

Houpan Song ◽

Yasha Zhou ◽

Jun Peng ◽

Qinghua Peng

Keyword(s):

Molecular Docking ◽

Cellular Response ◽

Ovarian Follicle ◽

Enrichment Analysis ◽

New Drugs ◽

Venn Diagram ◽

Network Pharmacology ◽

Active Compounds ◽

Ovarian Follicle Development ◽

Target Network

Background. Qing Guang An Granule (QGAG), a Chinese patent medicine, has been used clinically to treat glaucoma for more than 20 years. Objective. To explore the possible mechanism of treatment of QGAG in glaucoma by using network pharmacology and molecular docking in this study. Methods. Active compounds and targets of each herb in QGAG were retrieved via the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Glaucoma-related targets were acquired from OMIM and DisGeNET database. Key targets of QGAG against glaucoma were acquired by overlapping the above targets via the Venn diagram. Using the DAVID, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the key targets were performed. The docking process was performed using the AutoDock 4.2.6 and AutoDock Vina 1.1.2. Results. The 55 active compounds and 173 targets were obtained and constructed a compound-target network. The 20 key targets of QGAG in treating glaucoma were acquired, and these targets are involved in the apoptotic process, cellular response to hypoxia, negative regulation of cell growth, and ovarian follicle development. The main pathways are p53, HIF-1, PI3K-Akt, and neurotrophin signaling pathway. Conclusion. QGAG may exert a protective effect by acting on the optic nerve at a molecular and systemic level. This study can provide a certain basis for future researches on exploring the QGAG in treating glaucoma and provide new ideas for developing new drugs.

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Research on the Mechanism of Guizhi to Treat Nephrotic Syndrome Based on Network Pharmacology and Molecular Docking Technology

BioMed Research International ◽

10.1155/2021/8141075 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Dan He ◽

Qiang Li ◽

Guangli Du ◽

Jijia Sun ◽

Guofeng Meng ◽

...

Keyword(s):

Nephrotic Syndrome ◽

Molecular Docking ◽

Active Component ◽

Network Pharmacology ◽

Protective Mechanism ◽

Ppi Network ◽

Active Components ◽

Active Compounds ◽

The Core ◽

Target Network

Objective. Nephrotic syndrome (NS) is a common glomerular disease caused by a variety of causes and is the second most common kidney disease. Guizhi is the key drug of Wulingsan in the treatment of NS. However, the action mechanism remains unclear. In this study, network pharmacology and molecular docking were used to explore the underlying molecular mechanism of Guizhi in treating NS. Methods. The active components and targets of Guizhi were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Hitpick, SEA, and Swiss Target Prediction database. The targets related to NS were obtained from the DisGeNET, GeneCards, and OMIM database, and the intersected targets were obtained by Venny2.1.0. Then, active component-target network was constructed using Cytoscape software. And the protein-protein interaction (PPI) network was drawn through the String database and Cytoscape software. Next, Gene Ontology (GO) and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed by DAVID database. And overall network was constructed through Cytoscape. Finally, molecular docking was conducted using Autodock Vina. Results. According to the screening criteria, a total of 8 active compounds and 317 potential targets of Guizhi were chosen. Through the online database, 2125 NS-related targets were identified, and 93 overlapping targets were obtained. In active component-target network, beta-sitosterol, sitosterol, cinnamaldehyde, and peroxyergosterol were the important active components. In PPI network, VEGFA, MAPK3, SRC, PTGS2, and MAPK8 were the core targets. GO and KEGG analyses showed that the main pathways of Guizhi in treating NS involved VEGF, Toll-like receptor, and MAPK signaling pathway. In molecular docking, the active compounds of Guizhi had good affinity with the core targets. Conclusions. In this study, we preliminarily predicted the main active components, targets, and signaling pathways of Guizhi to treat NS, which could provide new ideas for further research on the protective mechanism and clinical application of Guizhi against NS.

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The Mechanism of Compound Danshen Dripping Pills in the Treatment of Diabetic Retinopathy Based on Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-490037/v1 ◽

2021 ◽

Author(s):

Xuedong An ◽

LiYun Duan ◽

YueHong Zhang ◽

De Jin ◽

Shenghui Zhao ◽

...

Keyword(s):

Cluster Analysis ◽

Cell Proliferation ◽

Diabetic Retinopathy ◽

Molecular Docking ◽

Signaling Pathway ◽

Active Ingredient ◽

Network Pharmacology ◽

Asiatic Acid ◽

Active Components ◽

The Core

Abstract BackgroundOur previous randomized, double-blind, placebo-controlled, multi-center clinical study showed that Compound Danshen Dripping Pills (CDDP) had a significant and safe effect in the treatment of diabetic retinopathy (DR), but its mechanism is still unclear, which we would explain based on network pharmacology and molecular docking.MethodThe active ingredients of CDDP (composed of Panax notoginseng, Salvia miltiorrhiza Bge., and Borneol) were searched in the TCMSP database. The validated target and Smiles number of the active ingredient are queried through the PubChem database, and the predicted target of the active ingredient is obtained through the Swisstarget Prediction database. The Drugbank, TTD, and DisGeNET databases were retrieved to obtain the related targets of DR. The core targets were obtained by the cluster analysis function of Cytoscape, and then the Protein-Protein Interaction was performed. The GO and KEGG signal pathways were enriched and clustered in David database. The potential active components and targets were docking with Autodock Vina, and the results were visualized by PyMOL.Result51 active components and 922 validation and prediction targets of CDDP, 715 targets of DR and 154 co-targets were obtained. Cluster analysis showed that there were two clusters, a total of 64 targets. Go and KEGG signal pathway enrichment analysis showed that the top 20 mainly included TNF and HIF-1 signaling pathway. In GO analysis, BP mainly includes positive regulation of smooth muscle cell proliferation and response to hypoxia, CC mainly includes extracellular space and extracellular domain, MF mainly includes protein binding and protein binding recognition. In KEGG database, the key genes in the TNF signaling pathway were TNF, NFkB and VEGF, in HIF-1 signaling pathway were the IL-6, STAT3, HIF1A and VEGF. Molecular docking results showed that all components of CDDP had a certain docking ability with TNF, NFkB, VEGF, IL-6, STAT3 and HIF1A, which of Asiatic acid and Salvianolic acid j was the strongest.Conclusion Based on the network pharmacology and molecular docking, the core active components of CDDP, mainly including Asiatic acid and Salvianolic acid j, which may play a role in regulating cell proliferation and response to inflammation and hypoxia by regulating the binding and recognition of intracellular and extracellular proteins, that is, mainly through TNF signaling pathway and HIF-1 signaling pathway.

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Mechanism of Action of Bu-Fei-Yi-Shen Formula in Treating Chronic Obstructive Pulmonary Disease Based on Network Pharmacology Analysis and Molecular Docking Validation

BioMed Research International ◽

10.1155/2020/9105972 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Longchuan Wu ◽

Yu Chen ◽

Jiao Yi ◽

Yi Zhuang ◽

Lei Cui ◽

...

Keyword(s):

Molecular Docking ◽

Mechanism Of Action ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Chronic Obstructive ◽

Biological Functions ◽

Active Ingredients ◽

Obstructive Pulmonary Disease ◽

The Core ◽

Target Network

Objective. To explore the mechanism of action of Bu-Fei-Yi-Shen formula (BFYSF) in treating chronic obstructive pulmonary disease (COPD) based on network pharmacology analysis and molecular docking validation. Methods. First of all, the pharmacologically active ingredients and corresponding targets in BFYSF were mined by the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the analysis platform, and literature review. Subsequently, the COPD-related targets (including the pathogenic targets and known therapeutic targets) were identified through the TTD, CTD, DisGeNet, and GeneCards databases. Thereafter, Cytoscape was employed to construct the candidate component-target network of BFYSF in the treatment of COPD. Moreover, the cytoHubba plug-in was utilized to calculate the topological parameters of nodes in the network; then, the core components and core targets of BFYSF in the treatment of COPD were extracted according to the degree value (greater than or equal to the median degree values for all nodes in the network) to construct the core network. Further, the Autodock vina software was adopted for molecular docking study on the core active ingredients and core targets, so as to verify the above-mentioned network pharmacology analysis results. Finally, the Omicshare database was applied in enrichment analysis of the biological functions of core targets and the involved signaling pathways. Results. In the core component-target network of BFYSF in treating COPD, there were 30 active ingredients and 37 core targets. Enrichment analysis suggested that these 37 core targets were mainly involved in the regulation of biological functions, such as response to biological and chemical stimuli, multiple cellular life processes, immunity, and metabolism. Besides, multiple pathways, including IL-17, Toll-like receptor (TLR), TNF, and HIF-1, played certain roles in the effect of BFYSF on treating COPD. Conclusion. BFYSF can treat COPD through the multicomponent, multitarget, and multipathway synergistic network, which provides basic data for intensively exploring the mechanism of action of BFYSF in treating COPD.

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