Exploring the Underlying Mechanisms of Qingxing Granules Treating H1N1 Influenza Based on Network Pharmacology and Experimental Validation
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Published:2024-06-05
Issue:6
Volume:17
Page:731
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ISSN:1424-8247
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Container-title:Pharmaceuticals
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language:en
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Short-container-title:Pharmaceuticals
Author:
Du Hujun1, Zhang Lianying1, Sun Haoxiang1, Zheng Shaoqin2, Zhang Hongying12, Yuan Shijia1, Zhou Jiuyao3ORCID, Fang Zihao4, Song Jianping1, Mei Manxue3ORCID, Deng Changsheng1
Affiliation:
1. Artemisinin Research Center, Guangzhou University of Chinese Medicine, Guangzhou 510405, China 2. Sci-Tech Industrial Park, Guangzhou University of Chinese Medicine, Guangzhou 510330, China 3. Department of Pharmacology, School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510330, China 4. The Eighth Clinical Medical School, Guangzhou University of Chinese Medicine, Guangzhou 510405, China
Abstract
Background: H1N1 is one of the major subtypes of influenza A virus (IAV) that causes seasonal influenza, posing a serious threat to human health. A traditional Chinese medicine combination called Qingxing granules (QX) is utilized clinically to treat epidemic influenza. However, its chemical components are complex, and the potential pharmacological mechanisms are still unknown. Methods: QX’s effective components were gathered from the TCMSP database based on two criteria: drug-likeness (DL ≥ 0.18) and oral bioavailability (OB ≥ 30%). SwissADME was used to predict potential targets of effective components, and Cytoscape was used to create a “Herb-Component-Target” network for QX. In addition, targets associated with H1N1 were gathered from the databases GeneCards, OMIM, and GEO. Targets associated with autophagy were retrieved from the KEGG, HAMdb, and HADb databases. Intersection targets for QX, H1N1 influenza, and autophagy were identified using Venn diagrams. Afterward, key targets were screened using Cytoscape’s protein–protein interaction networks built using the database STRING. Biological functions and signaling pathways of overlapping targets were observed through GO analysis and KEGG enrichment analysis. The main chemical components of QX were determined by high-performance liquid chromatography (HPLC), followed by molecular docking. Finally, the mechanism of QX in treating H1N1 was validated through animal experiments. Results: A total of 786 potential targets and 91 effective components of QX were identified. There were 5420 targets related to H1N1 and 821 autophagy-related targets. The intersection of all targets of QX, H1N1, and autophagy yielded 75 intersecting targets. Ultimately, 10 core targets were selected: BCL2, CASP3, NFKB1, MTOR, JUN, TNF, HSP90AA1, EGFR, HIF1A, and MAPK3. Identification of the main chemical components of QX by HPLC resulted in the separation of seven marker ingredients within 195 min, which are amygdalin, puerarin, baicalin, phillyrin, wogonoside, baicalein, and wogonin. Molecular docking results showed that BCL2, CASP3, NFKB1, and MTOR could bind well with the compounds. In animal studies, QX reduced the degenerative alterations in the lung tissue of H1N1-infected mice by upregulating the expression of p-mTOR/mTOR and p62 and downregulating the expression of LC3, which inhibited autophagy. Conclusions: According to this study’s network pharmacology analysis and experimental confirmation, QX may be able to treat H1N1 infection by regulating autophagy, lowering the expression of LC3, and increasing the expression of p62 and p-mTOR/mTOR.
Funder
National Administration of Traditional Chinese Medicine International Cooperation Project Guangdong Provincial Department of Science and Technology National Natural Science Foundation of China
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