Integrating metabolomics and network pharmacology to assess the effects of quercetin on lung inflammatory injury induced by human respiratory syncytial virus

Abstract

Quercetin (QR) has significant anti-respiratory syncytial virus (RSV) effects. However, its therapeutic mechanism has not been thoroughly explored. In this study, a lung inflammatory injury model caused by RSV was established in mice. Untargeted lung tissue metabolomics was used to identify differential metabolites and metabolic pathways. Network pharmacology was used to predict potential therapeutic targets of QR and analyze biological functions and pathways modulated by QR. By overlapping the results of the metabolomics and the network pharmacology analyses, the common targets of QR that were likely to be involved in the amelioration of RSV-induced lung inflammatory injury by QR were identified. Metabolomics analysis identified 52 differential metabolites and 244 corresponding targets, while network pharmacology analysis identified 126 potential targets of QR. By intersecting these 244 targets with the 126 targets, hypoxanthine–guanine phosphoribosyltransferase (HPRT1), thymidine phosphorylase (TYMP), lactoperoxidase (LPO), myeloperoxidase (MPO), and cytochrome P450 19A1 (CYP19A1) were identified as the common targets. The key targets, HPRT1, TYMP, LPO, and MPO, were components of purine metabolic pathways. The present study demonstrated that QR effectively ameliorated RSV-induced lung inflammatory injury in the established mouse model. Combining metabolomics and network pharmacology showed that the anti-RSV effect of QR was closely associated with purine metabolism pathways.

Danggui Jixueteng decoction for the treatment of myelosuppression after chemotherapy: A combined metabolomics and network pharmacology analysis

“…Chemometrics simulated the geometric and energy matching of molecules to identify optimal binding modes between small molecule ligands and biological macromolecule receptors [ 8 ]. The advancement of computer-aided technologies like network pharmacology and molecular docking has compensated for the long cycle, high effort, and low efficiency of traditional TCM research techniques, significantly enhancing the development of new pharmaceuticals [ 9 ]. Systems biology, crucial in metabolomics technology, analyzes metabolite changes in human fluids, tissues, and organs, providing insights into pathogenic mechanisms and therapeutic actions [ 10 , 11 ].…”