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Peer-reviewedCC BY 4.0International Journal of Molecular Sciences

Parameter-Based Prioritization of Time-Resolved LC–HRMS Ion Tracks for Untargeted Reaction Monitoring

  • Igor Ilyasov1
  • Arcady Braun2,3
  • Vera Olicheva1
  • Valery Goman1
  • Victoria Grikh4
  • Anastasiya Zhevlakova1
  • Irina Selivanova1
  • Vladimir Beloborodov1
4 affiliations
  1. 1Department of Chemistry, Nelyubin Institute of Pharmacy, Sechenov First Moscow State Medical University, Trubetskaya Street 8/2, 119048 Moscow, Russia
  2. 2Department of Chemistry, Lomonosov Moscow State University, 27/1 Lomonosovsky Avenue, 119991 Moscow, Russia
  3. 3Lomonosov Institute of Fine Chemical Technologies, MIREA—Russian Technological University, 119571 Moscow, Russia
  4. 4Department of Analytical, Physical and Colloidal Chemistry, Nelyubin Institute of Pharmacy, Sechenov First Moscow State Medical University, Trubetskaya Street 8/2, 119048 Moscow, Russia
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Abstract

Herein, an automated, parameter-based workflow is introduced for processing time-resolved high-resolution mass spectrometry (HRMS) data. Its utility is demonstrated using the reaction between the ABTS•+ radical cation and the polyphenolic antioxidant naringenin. Data were collected using HRMS coupled to high-performance liquid chromatography (HPLC) in negative ion mode. The algorithm compares sequential time-resolved HRMS measurements to generate kinetic curves and calculate parameters for every detected species. Based on these curves and parameters, we can tentatively classify each species as a reagent, intermediate, or product. The algorithm was implemented as Java-based software. As a result, extensive data arrays of 1.3 million m/z-intensity pairs per experimental series were processed automatically. The workflow generated manageable candidate sets in each replicate series. Cross-replicate matching using a 5 ppm mass tolerance retained 29 ion tracks consistently detected in all three reaction runs for subsequent analysis. These ions can then be examined manually to identify compound structures. Overall, the approach provides a screening tool for untargeted reaction monitoring and supports subsequent structural annotation in complex chemical systems.

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Cite

BibTeXRIS
BibTeX
@article{ilyasov2026parameterbased,
  title = {{Parameter-Based Prioritization of Time-Resolved LC–HRMS Ion Tracks for Untargeted Reaction Monitoring}},
  author = {Igor Ilyasov and Arcady Braun and Vera Olicheva and Valery Goman and Victoria Grikh and Anastasiya Zhevlakova and Irina Selivanova and Vladimir Beloborodov},
  journal = {International Journal of Molecular Sciences},
  year = {2026},
  month = oct,
  doi = {10.3390/ijms27198852},
  url = {https://www.mdpi.com/1422-0067/27/19/8852},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Parameter-Based Prioritization of Time-Resolved LC–HRMS Ion Tracks for Untargeted Reaction Monitoring
AU  - Igor Ilyasov
AU  - Arcady Braun
AU  - Vera Olicheva
AU  - Valery Goman
AU  - Victoria Grikh
AU  - Anastasiya Zhevlakova
AU  - Irina Selivanova
AU  - Vladimir Beloborodov
PY  - 2026
DA  - 2026/10/04
JO  - International Journal of Molecular Sciences
DO  - 10.3390/ijms27198852
UR  - https://www.mdpi.com/1422-0067/27/19/8852
AB  - Herein, an automated, parameter-based workflow is introduced for processing time-resolved high-resolution mass spectrometry (HRMS) data. Its utility is demonstrated using the reaction between the ABTS•+ radical cation and the polyphenolic antioxidant naringenin. Data were collected using HRMS coupled to high-performance liquid chromatography (HPLC) in negative ion mode. The algorithm compares sequential time-resolved HRMS measurements to generate kinetic curves and calculate parameters for every detected species. Based on these curves and parameters, we can tentatively classify each species as a reagent, intermediate, or product. The algorithm was implemented as Java-based software. As a result, extensive data arrays of 1.3 million m/z-intensity pairs per experimental series were processed automatically. The workflow generated manageable candidate sets in each replicate series. Cross-replicate matching using a 5 ppm mass tolerance retained 29 ion tracks consistently detected in all three reaction runs for subsequent analysis. These ions can then be examined manually to identify compound structures. Overall, the approach provides a screening tool for untargeted reaction monitoring and supports subsequent structural annotation in complex chemical systems.
SN  - 1422-0067
ER  -