GNPS Feature-Based Molecular Networking as a Tool to Visualize Metabolic Toxicity from Drug–Drug Interactions: A Case Study with Methamphetamine and Ethanol

Feature-Based Molecular Networking (FBMN) on the Global Natural Products Social Molecular Networking (GNPS) platform offers a transformative framework for visualizing drug-drug interaction (DDI)-driven metabolic reprogramming that conventional analytical approaches fail to capture. Here, we demonstrate its application as a novel strategy to resolve complex metabolic alterations arising from DDI-induced toxicity. Using FBMN-integrated MS² mapping, we established a proof-of-concept workflow to elucidate large-scale metabolic transitions and pathway rewiring. As a model system, co-administration of methamphetamine (MA) and ethanol (EtOH)─a combination known to potentiate toxicity─was analyzed through liquid chromatography-quadrupole time-of-flight mass spectrometry. Merging MS² spectra across multiple collision energies revealed diagnostic fragment ions that enabled network connectivity and comprehensive annotation of 21 MA-related features, including glucuronide conjugates and in-source fragments. FBMN visualization uncovered an EtOH-driven metabolic shift, characterized by suppression of benzene ring hydroxylation and the emergence of <i>N</i>-acetylamphetamine and novel glucuronidated metabolites. Collectively, these findings establish GNPS-FBMN as a powerful and generalizable analytical strategy for delineating DDI-associated metabolic reprogramming, providing mechanistic insight into the metabolic basis of toxicity arising from drug combinations.