<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Kim M</submitter><funding>Korean National Police Agency</funding><funding>Ministry of Education</funding><funding>Korea Customs Service</funding><funding>Korean National Police University</funding><pagination>69-75</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12809649</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>98(1)</volume><pubmed_abstract>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 MS&lt;sup>2&lt;/sup> 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 MS&lt;sup></pubmed_abstract><journal>Analytical chemistry</journal><pubmed_title>GNPS Feature-Based Molecular Networking as a Tool to Visualize Metabolic Toxicity from Drug-Drug Interactions: A Case Study with Methamphetamine and Ethanol.</pubmed_title><pmcid>PMC12809649</pmcid><funding_grant_id>RS-2023-00242428</funding_grant_id><funding_grant_id>RS-2024-00406234</funding_grant_id><pubmed_authors>Yoo SJ</pubmed_authors><pubmed_authors>Lee S</pubmed_authors><pubmed_authors>Kim JH</pubmed_authors><pubmed_authors>Kim M</pubmed_authors></additional><is_claimable>false</is_claimable><name>GNPS Feature-Based Molecular Networking as a Tool to Visualize Metabolic Toxicity from Drug-Drug Interactions: A Case Study with Methamphetamine and Ethanol.</name><description>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 MS&lt;sup>2&lt;/sup> 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 MS&lt;sup></description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Jan</publication><modification>2026-06-06T16:06:54.667Z</modification><creation>2026-06-02T03:12:24.64Z</creation></dates><accession>S-EPMC12809649</accession><cross_references><pubmed>41481198</pubmed><doi>10.1021/acs.analchem.5c06388</doi></cross_references></HashMap>