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A versatile toolkit for drug metabolism studies with GNPS2: from drug development to clinical monitoring

Authors
Yu, Jun SangKwak, Young BeomKee, Kyung HwaWang, MingxunKim, Dong HyunDorrestein, Pieter C.Kang, Kyo BinYoo, Hye Hyun
Issue Date
Sep-2025
Publisher
NATURE PORTFOLIO
Citation
NATURE PROTOCOLS
Indexed
SCIE
SCOPUS
Journal Title
NATURE PROTOCOLS
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/126525
DOI
10.1038/s41596-025-01237-6
ISSN
1754-2189
1750-2799
Abstract
Metabolism is a fundamental process that shapes the pharmacological and toxicological profiles of drugs, making metabolite identification and analysis critical in drug development and biological research. Global Natural Products Social Networking (GNPS) is a community-driven infrastructure for mass spectrometry data analysis, storage and knowledge dissemination. GNPS2 is an improved version of the platform offering higher processing speeds, improved data analysis tools and a more intuitive user interface. Molecular networking based on tandem mass spectrometry spectral alignments, combined with other tools in the GNPS2 analysis environment, enables the discovery of candidate drug metabolites without prior knowledge, even from complex biological matrices. This protocol represents an extension of a previously established protocol for fundamental molecular networking in GNPS, with a specific focus on metabolism studies. This article uses the example of the drug sildenafil to identify candidate metabolites obtained from liquid chromatography-quadrupole time-of-flight mass spectrometry analysis of liver microsomal fractions and mice plasma to guide the reader through a step-by-step process consisting of five GNPS2-based analytical workflows. It demonstrates how the tools in GNPS2 can be used not only to identify candidate drug metabolites from in vitro studies but also to evaluate the translational relevance of these in vitro findings to humans by using reverse metabolomics. We provide a step-by-step analytical approach based on published studies to showcase how GNPS2 can be effectively applied in drug metabolism studies.
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