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<p>The increasing diversity of illicit substances, including novel psychoactive substances, poses growing challenges for their detection and structural annotation in forensic and toxicological workflows. This Data Descriptor documents the deposition of a high-resolution LC–MS/MS spectral dataset of 286 prohibited substances and their metabolites spanning nine major drug classes in the GNPS/MassIVE public repository. Using GNPS molecular networking, the dataset was organized into a molecular network termed the Illicit Drug Network, facilitating structure-based classification, compound dereplication, and annotation of structurally related analogs. This openly accessible resource is intended to support screening workflows in forensic toxicology, anti-doping control, customs inspection, and criminal investigation.</p>

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A GNPS-based MS/MS molecular networking dataset of 286 prohibited substances and metabolites for forensic and toxicological applications

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月5日

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  • Yejin Kim,
  • Hyeyoung Choi,
  • Juhyun Sim,
  • Jiyeong Jo,
  • Jun Sang Yu,
  • Hye Hyun Yoo

摘要

The increasing diversity of illicit substances, including novel psychoactive substances, poses growing challenges for their detection and structural annotation in forensic and toxicological workflows. This Data Descriptor documents the deposition of a high-resolution LC–MS/MS spectral dataset of 286 prohibited substances and their metabolites spanning nine major drug classes in the GNPS/MassIVE public repository. Using GNPS molecular networking, the dataset was organized into a molecular network termed the Illicit Drug Network, facilitating structure-based classification, compound dereplication, and annotation of structurally related analogs. This openly accessible resource is intended to support screening workflows in forensic toxicology, anti-doping control, customs inspection, and criminal investigation.