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<p>Translating mass spectra into chemical structures is a central challenge in exposomics, making it difficult to quickly track the millions of chemicals found in humans and the environment. Unlike metabolomics, key problems in developing models for chemicals with a larger molecular space include data scarcity, model complexity and proper query strategy. Here we present a molecular structure generator (MSGo) that can generate structures directly from mass spectra and discover unknown polyfluorinated chemicals in the exposome. Trained with only virtual spectra using a transformer neural network, MSGo correctly identified 48% of structures in a validation set and was better at discovering new polyfluorinated chemicals in wastewater samples reported in the literature than experts. Applying probability-oriented masking to the virtual spectra is key to MSGo’s performance. Rapid discovery of chemicals with limited experimental mass spectral data using automated tools such as MSGo is key to tackling the current unknown polyfluorinated chemical crisis.</p>

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Pseudodata-based molecular structure generator to reveal unknown chemicals

  • 期刊论文

  • 发表日期：

    2025年11月14日

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  • Nanyang Yu,
  • Zheng Ma,
  • Qi Shao,
  • Laihui Li,
  • Xuebing Wang,
  • Bingcai Pan,
  • Hongxia Yu,
  • Si Wei

摘要

Translating mass spectra into chemical structures is a central challenge in exposomics, making it difficult to quickly track the millions of chemicals found in humans and the environment. Unlike metabolomics, key problems in developing models for chemicals with a larger molecular space include data scarcity, model complexity and proper query strategy. Here we present a molecular structure generator (MSGo) that can generate structures directly from mass spectra and discover unknown polyfluorinated chemicals in the exposome. Trained with only virtual spectra using a transformer neural network, MSGo correctly identified 48% of structures in a validation set and was better at discovering new polyfluorinated chemicals in wastewater samples reported in the literature than experts. Applying probability-oriented masking to the virtual spectra is key to MSGo’s performance. Rapid discovery of chemicals with limited experimental mass spectral data using automated tools such as MSGo is key to tackling the current unknown polyfluorinated chemical crisis.