An Integrated Systems Pharmacology Approach Combining Bioinformatics, Untargeted Metabolomics and Molecular Dynamics to Unveil the Anti-Aging Mechanisms of Tephroseris flammea

Abstract

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.