基于网络药理学和分子对接的蒙古黄芪、当归治疗间质性肺疾病机制预测

Jun Du, Jian Hao, Wei Wei
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Results : 59 active ingredients that can be druggable were chosen from AM, 67 active ingredients were chosen from AS. 77 overlapping target genes for AM and ILD and 36 overlapping target genes for AS and ILD were acquired. The hub targets of AM were PTGS2, PTGS1,CDK2, MAOA, ESR1, TOP2A, GSK3B, ESR2, PPARG, NOS2, The hub targets of AS were PTGS2, GABRA1, PTGS1, CHRM1, SLC6A2, ADRA1B, ADRAIA, ADRB2, CHRM3, GABRA2, CHRM2. Quercetin, kaempferol, daidzein, pavilion, 7-Hydroxycoumarin, and 5-Hydroxycoumarin were the main active ingredients which have more effective targets. Prediction of the protein-protein interaction network showed PTGS2, GSK3B, PPARG, etc., were the important predicted targets. The enriched KEGG pathways, including the Immune System, Metabolism of lipids and lipoproteins, Cytokine Signaling in the Immune system, Generic Transcription Pathway, The interleukin pathway, Metabolism of proteins, PI3K-Akt signaling pathway, Metabolic pathways, Innate Immune System, Neuroactive ligand-receptor interaction, Metabolism, GPCR downstream signaling, Amine ligand-binding receptors, Class A/1, Calcium signaling pathway. Molecular docking showed that quercetin, kaempferol, daidzein, pavilion, 7-Hydroxycoumarin, 5-Hydroxycoumarin had good binding activities with PTGS2 and GSK3B, which mainly mediated PI3K/Akt and other important signaling pathways in the pathogenesis of ILD. Conclusion : The components in AS and AM share some common targets, such as PTGS2. AM and AS may ameliorate ILD through the PI3K-Akt signaling pathway which is mediated by GSK3B. 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Methods : We screened the ingredients of AM and AS in PubMed, the Web of Science, China National Knowledge Infrastructure (CNKI) Databases, etc. Then obtained the potential effective components. By sharing the same molecular with ILD, we got the possible target genes for ILD treatment and constructed components–targets–disease network with Cytoscape software. The CTD (Comparative Toxicogenomics Database) database was used for GO and KEGG enrichment analysis of these target genes. Results : 59 active ingredients that can be druggable were chosen from AM, 67 active ingredients were chosen from AS. 77 overlapping target genes for AM and ILD and 36 overlapping target genes for AS and ILD were acquired. The hub targets of AM were PTGS2, PTGS1,CDK2, MAOA, ESR1, TOP2A, GSK3B, ESR2, PPARG, NOS2, The hub targets of AS were PTGS2, GABRA1, PTGS1, CHRM1, SLC6A2, ADRA1B, ADRAIA, ADRB2, CHRM3, GABRA2, CHRM2. Quercetin, kaempferol, daidzein, pavilion, 7-Hydroxycoumarin, and 5-Hydroxycoumarin were the main active ingredients which have more effective targets. Prediction of the protein-protein interaction network showed PTGS2, GSK3B, PPARG, etc., were the important predicted targets. The enriched KEGG pathways, including the Immune System, Metabolism of lipids and lipoproteins, Cytokine Signaling in the Immune system, Generic Transcription Pathway, The interleukin pathway, Metabolism of proteins, PI3K-Akt signaling pathway, Metabolic pathways, Innate Immune System, Neuroactive ligand-receptor interaction, Metabolism, GPCR downstream signaling, Amine ligand-binding receptors, Class A/1, Calcium signaling pathway. Molecular docking showed that quercetin, kaempferol, daidzein, pavilion, 7-Hydroxycoumarin, 5-Hydroxycoumarin had good binding activities with PTGS2 and GSK3B, which mainly mediated PI3K/Akt and other important signaling pathways in the pathogenesis of ILD. 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Mechanism prediction of Astragalus mongholicus Bunge and Angelica sinensis Diels in treating interstitial lung disease based on network pharmacology and molecular docking
Objective : To investigate the mechanism by which Astragalus mongholicus Bunge (AM), and Angelica sinensis Diels (AS) act in interstitial lung disease (ILD) based on computational prediction. Methods : We screened the ingredients of AM and AS in PubMed, the Web of Science, China National Knowledge Infrastructure (CNKI) Databases, etc. Then obtained the potential effective components. By sharing the same molecular with ILD, we got the possible target genes for ILD treatment and constructed components–targets–disease network with Cytoscape software. The CTD (Comparative Toxicogenomics Database) database was used for GO and KEGG enrichment analysis of these target genes. Results : 59 active ingredients that can be druggable were chosen from AM, 67 active ingredients were chosen from AS. 77 overlapping target genes for AM and ILD and 36 overlapping target genes for AS and ILD were acquired. The hub targets of AM were PTGS2, PTGS1,CDK2, MAOA, ESR1, TOP2A, GSK3B, ESR2, PPARG, NOS2, The hub targets of AS were PTGS2, GABRA1, PTGS1, CHRM1, SLC6A2, ADRA1B, ADRAIA, ADRB2, CHRM3, GABRA2, CHRM2. Quercetin, kaempferol, daidzein, pavilion, 7-Hydroxycoumarin, and 5-Hydroxycoumarin were the main active ingredients which have more effective targets. Prediction of the protein-protein interaction network showed PTGS2, GSK3B, PPARG, etc., were the important predicted targets. The enriched KEGG pathways, including the Immune System, Metabolism of lipids and lipoproteins, Cytokine Signaling in the Immune system, Generic Transcription Pathway, The interleukin pathway, Metabolism of proteins, PI3K-Akt signaling pathway, Metabolic pathways, Innate Immune System, Neuroactive ligand-receptor interaction, Metabolism, GPCR downstream signaling, Amine ligand-binding receptors, Class A/1, Calcium signaling pathway. Molecular docking showed that quercetin, kaempferol, daidzein, pavilion, 7-Hydroxycoumarin, 5-Hydroxycoumarin had good binding activities with PTGS2 and GSK3B, which mainly mediated PI3K/Akt and other important signaling pathways in the pathogenesis of ILD. Conclusion : The components in AS and AM share some common targets, such as PTGS2. AM and AS may ameliorate ILD through the PI3K-Akt signaling pathway which is mediated by GSK3B. PTGS2, PPARG may also be vital target genes in the treatment of ILD with AM and AS.
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