Multitarget Mechanism of Artemisia Plants to Fight Respiratory Tract Infections Based on Network Pharmacology and Molecular Docking

Objective: To study the mechanism of Artemisia in the treatment of respiratory tract infection (RTI) by network pharmacology and molecular docking. Methods: The active constituents and targets of Artemisia were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Gene Cards database to obtain disease targets associated with RTI. The key targets of intersection were used to construct the protein-protein interaction (PPI) network, and the hub gene was obtained through topological analysis to construct the pharmacology regulation network of traditional Chinese medicine. The key targets were analyzed by R language enrichment, and the regulatory network diagram of the key target function/pathway was constructed. Molecular docking verifies the binding of the drug to the target predicted by network pharmacology. Results: 144 active components of Artemisia regulated 133 target proteins related to RTI, the core components were beta-sitosterol, quercetin, isorhamnetin, artemisinin, etc. Gene ontology enrichment analysis showed that Artemisia regulates receptor ligand activity, cytokine activity, and other molecular functions by acting on membrane region, membrane raft and other cellular structures in the treatment of RTI, thus affecting biological processes such as the response to drugs and bacteria-derived molecules. Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that phosphatidylinositol 3-kinase (PI3K)-protein kinase B (Akt), tumor necrosis factor, interleukin-17 (IL-17) signaling pathway was the main pathway for RTI treatment. The molecular docking method confirmed the high affinity between the active ingredient and the RTI target. Conclusions:Artemisia species, a multitarget medication, has been shown to be a viable therapy option for RTI by network pharmacology techniques based on data mining and molecular docking approaches.