Skin aging, driven by oxidative stress, UV exposure, inflammation, and extracellular matrix degradation, necessitates the discovery of safer, multi-target natural products. We established an integrated pipeline combining UHPLC–MS/MS metabolomics, computational methods (network pharmacology, molecular docking, and dynamics simulation), and in vitro bioassays to efficiently discover and mechanistically characterize anti-aging compounds from novel botanical sources. We applied this pipeline to identify and evaluate Tephroseris flammea, a previously unassessed plant. Metabolomic profiling identified 21 compounds, including flavonoids, phenylpropanoids, and pyrrolizidine alkaloids. These compounds were linked via network pharmacology to 226 skin-aging-related targets, primarily involving inflammation (via AKT1, RELA) and matrix degradation (via MAPK3). Molecular docking and 100 ns molecular dynamics simulations confirmed stable ligand-target interactions with favorable binding energies. Validating these in silico predictions, the T. flammea extract demonstrated significant antioxidant activity and effectively suppressed key inflammatory mediators (IL-6, TNF-α, COX-2) and MMP-1 levels in UVB-exposed fibroblasts, notably without significant cytotoxicity. Collectively, this study validates the utility of our pipeline to mechanistically characterize complex botanicals, revealing that T. flammea contains multifunctional compounds modulating critical inflammatory and matrix-regulatory cascades. This work validates our pipeline for identifying novel, mechanistically defined ingredients from complex botanical sources.

Oxidative stress, UV exposure, inflammation, and extracellular matrix degradation collectively drive skin aging, underscoring the need for safe, multi-target therapeutic options. We developed and applied an integrated analytical pipeline combining UHPLC–MS/MS metabolomics, computational analyses (network pharmacology, molecular docking, and molecular dynamics simulation), and experimental bioassays to efficiently identify and characterize novel natural products with anti-aging potential. This workflow was applied to Melampyrum roseum Maxim., a previously unassessed hemiparasitic plant of the Orobanchaceae family, to elucidate its bioactive potential against skin aging. UHPLC–MS/MS profiling annotated 13 secondary metabolites, predominantly flavone aglycones, iridoid glycosides, and phenylpropanoid derivatives. Network pharmacology analysis linked these metabolites to 172 potential skin-aging-associated targets, mainly within inflammatory, ECM, and oxidative-stress pathways. Molecular docking and 100-ns molecular dynamics simulations confirmed stable ligand-target interactions with favorable binding energies, particularly with AKT1, EGFR, PTGS2 and XDH. Validating these predictions, the M. roseum extract demonstrated significant antioxidant activity and effectively suppressed key inflammatory mediators (IL-6, TNF-α, COX-2) and MMP-1 levels in UVB-exposed fibroblasts, notably without significant cytotoxicity. Collectively, these findings demonstrate that M. roseum harbors multifunctional metabolites that modulate key inflammatory and matrix-regulatory pathways, providing preliminary mechanistic evidence for its potential as a promising candidate for natural anti-aging applications.