Investigating the Mechanism of Qu Du Qiang Fei 1 Hao Fang Formula against Coronavirus Disease 2019 Based on Network Pharmacology Method
Yuan-Hua Wang, He-Yang Zhou, Jin-Yun Ma, Gui-Qing Ding, Hua Yu, Prof Yong-Sheng Jin, Prof Xiao-Dong Cheng
World Journal of Traditional Chinese Medicine, doi:10.4103/2311-8571.395061
IntroductIon Coronavirus disease 2019 (COVID-19) is a pulmonary infectious disease induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that seriously threatens human life and health. The classic clinical symptoms of COVID-19 are fever, headache, dyspnea, pneumonia, and dry cough. Some patients develop progressive respiratory failure caused by alveolar injury or even death. [1] According to the statistics from the World Health Organization ( https:// www.who.int/ ), as of August 2022, 589 million people have been diagnosed with COVID-19 globally, with over 6.4 million deaths and an upward trend in the number of cases in some countries and regions. However, specific drugs have not been
Conflicts of interest There are no conflicts of interest.
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DOI record:
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"abstract": "<jats:title>Abstract</jats:title>\n <jats:sec>\n <jats:title>Objective:</jats:title>\n <jats:p>\n <jats:italic toggle=\"yes\">Qu Du Qiang Fei 1 Hao Fang</jats:italic> (QDQF1) is a novel Chinese herbal medicine formula used to treat coronavirus disease 2019 (COVID-19). However, the pharmacological mechanisms of action of QDQF1 remain unclear. The objective of this study was to identify the effective ingredients and biological targets of QDQF1 for COVID-19 treatment.</jats:p>\n </jats:sec>\n <jats:sec>\n <jats:title>Materials and Methods:</jats:title>\n <jats:p>The effective ingredients and mechanisms of action of QDQF1 were analyzed by using network pharmacology methods, which included an analysis of the effective ingredients and corresponding targets, COVID-19-related target acquisition, compound-target network analyses, protein-protein interaction network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses, and molecular docking studies.</jats:p>\n </jats:sec>\n <jats:sec>\n <jats:title>Results:</jats:title>\n <jats:p>In total, 288 effective QDQF1 ingredients were identified. We identified 51 core targets from the 148 targets through an overlap between putative QDQF1 targets and COVID-19-related targets. Six key components, including formononetin, kaempferol, luteolin, naringenin, quercetin, and wogonin were identified through component-target network analyses. GO functional enrichment analysis of the core targets revealed 1296 items, while KEGG pathway enrichment analysis identified 148 signaling pathways. Nine central targets (CCL2, CXCL8, IL1B, IL6, MAPK1, MAPK3, MAPK8, STAT3, and TNF) related to the COVID-19 pathway were identified in the KEGG pathway enrichment analysis. Furthermore, molecular docking analysis suggested that the docking scores of the six key components to the nine central targets were better than those to remdesivir.</jats:p>\n </jats:sec>\n <jats:sec>\n <jats:title>Conclusions:</jats:title>\n <jats:p>QDQF1 may regulate multiple immune-and inflammation-related targets to inhibit the progression of severe acute respiratory syndrome coronavirus 2, and thus, may be suitable for the treatment of COVID-19.</jats:p>\n </jats:sec>",
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