Abstract

Daqinglong Decoction (DQLD), a traditional Chinese medicine (TCM) prescription firstly recorded in Shang han lun (the treatise on febrile diseases), has been used hundreds of years for the clinical treatment of influenza. However, the chemical composition and therapeutic mechanism of this prescription are unclear. UPLC-Q-TOF/MS was employed to analyze the chemical compounds in both methanol and boiling water extracts of DQLD. The compounds were then screened, characterized, and filtered using the TCMSP, TCMIP, TCM-ID and SymMap database, with a focus on their oral bioavailability and drug-likeness values. The resulting data were analyzed and optimized using the R language platform, Autodock and Gromacs software to identify biological processes and pathways. A total of 121 compounds were identified, of which 5 showed good binding ability to influenza virus targets (1L1B, IL10, CASP3, STAT3, TNF, and others). The active ingredient-target-influenza virus pathway was constructed using a network drug target analysis model prediction of DQLD, which was mainly enriched in Human cytomegalovirus infection, PI3K-Akt, HIF-1, and other signaling pathways through 1L1B, IL10 and other targets. Those pathways highly correlated to the body’s inflammatory response, improve immunity, and exert anti-influenza virus effects. In summary, this study demonstrated that DQLD's active ingredients can effectively bind to influenza virus targets and exert anti-influenza virus effects by reducing inflammation and improving immunity through Human cytomegalovirus infection, PI3K-Akt and HIF-1 signaling pathways. These findings offer important insights into the potential mechanisms of action of DQLD and its potential use as a TCM against influenza and other viral infections. Communicated by Ramaswamy H. Sarma

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