Mechanistic insights into targeting caspase-3 activation and alveolar macrophage pyroptosis by Ephedra and bitter almond compounds for treating pediatric pneumonia via network pharmacology and bioinformatics.

This study investigates the molecular mechanism of Ma Huang-Ku Xing Ren, a traditional Chinese medicine formula, in treating pediatric pneumonia. The focus is on the regulation of caspase-3 activation and reduction of alveolar macrophage necrosis through network pharmacology and bioinformatics analyses of Ephedra and bitter almond components. Active compounds and targets from ephedrine and bitter almond were obtained using TCMSP, TCMID, and GeneCards databases, identifying pediatric pneumonia-related genes. A protein-protein interaction (PPI) network was constructed, and core targets were screened. GO and KEGG pathway enrichment analyses identified relevant genes and pathways. An acute pneumonia mouse model was created using the lipopolysaccharide (LPS) inhalation method, with caspase-3 overexpression induced by a lentivirus. The mice were treated with Ephedra and bitter almond through gastric lavage. Lung tissue damage, inflammatory markers (IL-18 and IL-1β), and cell death-related gene activation were assessed through H&E staining, ELISA, western blot, flow cytometry, and immunofluorescence. The study identified 128 active compounds and 121 gene targets from Ephedra and bitter almond. The PPI network revealed 13 core proteins, and pathway analysis indicated involvement in inflammation, apoptosis, and cell necrosis, particularly the caspase-3 pathway. In vivo results showed that Ephedra and bitter almond treatment significantly mitigated LPS-induced lung injury in mice, reducing lung injury scores and inflammatory marker levels. It also decreased caspase-3 activity and cell death in alveolar macrophages. In conclusion, the active ingredients of Ma Huang-Ku Xing Ren, particularly targeting caspase-3, may effectively treat pediatric pneumonia by reducing apoptosis in alveolar macrophages, as demonstrated by both network pharmacology, bioinformatics analyses, and experimental data.