Network Pharmacology-Guided Identification of Antiaging Targets of Lavandula Flower Bioactives Using LC–MS/MS and Molecular Simulation Approaches - Syafnir, Livia; Fajarwati, Kania; Faizal, Ibnu Dharsono; Fakih, Taufik Muhammad (Fakultas Farmasi, Universitas Surabaya, 2026)
Lavandula flowers are widely used in cosmetic and dermatological formulations, yet the molecular basis of their antiaging activity remains incompletely understood. This study aimed to elucidate the antiaging potential of lavandula flower bioactives through LC–MS/MS-based metabolite profiling integrated with network pharmacology and molecular docking analysis. Metabolites were characterized using LC–MS/MS and annotated based on accurate mass and fragmentation patterns. Predicted targets of selected metabolites were obtained using in silico target prediction and intersected with antiaging-related genes to construct protein–protein interaction networks and identify key regulatory pathways. Molecular docking was performed to evaluate binding affinity and interaction modes between prioritized metabolites against JAK2. LC–MS/MS analysis revealed a diverse chemical profile dominated by carveol (16.12%), methylumbelliferone (8.77%), camphor (3.97%), and two late-eluting high-molecular-weight metabolites contributing 29.86% and 35.36% of the total peak area. Network pharmacology highlighted convergence on kinase-driven signaling, extracellular matrix regulation, inflammatory response, and oxidative stress pathways relevant to skin aging. The docking results against JAK2 showed that the substituted pyridin-4-ol derivative exhibited the strongest affinity among Lavandula metabolites (ΔG = −8.81 kcal/mol), followed by the piperidinyl-substituted trienone (ΔG = −7.92 kcal/mol), while methylumbelliferone (ΔG = −5.93 kcal/ mol) and ferulic acid (ΔG = −5.53 kcal/mol) displayed moderate binding. Lavandula flower bioactives exhibit antiaging potential through multitarget modulation of signaling and matrix-associated proteins, supported by quantitative metabolite profiling and docking-validated target engagement.