Abstract / Summary
Abstract Eriobotrya japonica leaf possesses documented pulmonary anti-inflammatory activity, but the systematic associations between its bioactive constituents, molecular targets, and immune cell states in human pneumonia remain poorly characterized. An integrated multiscale analytical approach combining network pharmacology, single-cell transcriptomics, machine learning, and molecular dynamics simulations was applied to identify core host-response genes linked to the pharmacological activity of E. japonica leaf in pneumonia and prioritize key constituent-target protein pairs. Candidate bioactive constituents and their putative targets were screened via network pharmacology. Targets overlapping with pneumonia-associated genes were subjected to protein–protein interaction network construction and functional enrichment analysis. Single-cell RNA-sequencing data of peripheral blood mononuclear cells from 8 patients with community-acquired pneumonia and 4 non-infectious controls were analyzed using donors as independent biological replicates. Pseudobulk differential expression, UCell gene-set scoring, and weighted expression scoring were performed to characterize disease-associated expression profiles and cellular origins of candidate genes. Stable features were selected via least absolute shrinkage and selection operator regression and random forest, and validated in an independent peripheral-blood transcriptomic cohort. Molecular docking and 100 ns molecular dynamics simulations assessed binding affinity and conformational stability. Eighteen candidate bioactive constituents and 356 pneumonia-associated intersecting genes were identified, yielding a robust Core-5 target panel (CTSD, PTGS2, CDK1, CCNA2, SELP). CTSD and PTGS2 localized predominantly to CD14⁺ monocytes, with CTSD significantly upregulated in disease. PTGS2-EGCG exhibited the lowest docking scoreand favorable conformational stability in simulations. These findings narrow the broad molecular associations between E. japonica leaf and pneumonia to prioritized evidence-based candidate relationships, providing a rigorous basis for mechanistic elucidation and targeted functional validation of the PTGS2-EGCG pair.