Simulating Collision-Induced Dissociation Tandem Mass Spectrometry (CID-MS/MS) for the Blood Exposome Database Using Quantum Chemistry Methods - A Pilot Study

A significant number of compounds in exposome databases and chemical inventories lack mass spectral data due to the nonavailability of reference standards. To address this limitation, computational chemistry methods can be utilized to extend mass spectral libraries for a set of chemicals. In this pilot study, we employed quantum-chemistry-based software QCxMS to generate collision-induced dissociation mass spectra for 121 compounds from the Blood Exposome Database. We developed a scalable computational framework that integrates QCxMS and additional tools, utilizing a grid-based parameter selection strategy and defined coverage criteria. Our approach systematically explored protomeric isomers and applied predefined parameter combination sets sequentially based on molecular structures. This workflow produced high-quality <i>in silico</i> spectra for 81 compounds that achieved entropy similarity scores ≥700 and at least two matching fragment ions against the NIST23 library, yielding 71% spectral coverage. These results highlight the importance of optimizing simulation parameters and accounting for protomeric diversity to enhance the spectral quality and computational efficiency. This workflow provides a practical strategy to add mass spectral data for most compounds in the Blood Exposome Database at reasonable computational cost, supporting the spectral library expansion for improved compound annotation in exposomics.

Authors

Institutions

Publication Details

Journal
Journal of the American Society for Mass Spectrometry
Published
2025-08-28
DOI
https://doi.org/10.1021/jasms.5c00179
Citations
1
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.81

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simulating Collision-Induced Dissociation Tandem Mass Spectrometry (CID-MS/MS) for the Blood Exposome Database Using Quantum Chemistry Methods - A Pilot Study

Jesi Lee, Dinesh Kumar Barupal
1 citations
Journal of the American Society for Mass Spectrometry
Metabolomics and Mass Spectrometry Studies
0.81
article

Simulating Collision-Induced Dissociation Tandem Mass Spectrometry (CID-MS/MS) for the Blood Exposome Database Using Quantum Chemistry Methods - A Pilot Study

Jesi Lee, Dinesh Kumar Barupal
article en
1 citations

Abstract

A significant number of compounds in exposome databases and chemical inventories lack mass spectral data due to the nonavailability of reference standards. To address this limitation, computational chemistry methods can be utilized to extend mass spectral libraries for a set of chemicals. In this pilot study, we employed quantum-chemistry-based software QCxMS to generate collision-induced dissociation mass spectra for 121 compounds from the Blood Exposome Database. We developed a scalable computational framework that integrates QCxMS and additional tools, utilizing a grid-based parameter selection strategy and defined coverage criteria. Our approach systematically explored protomeric isomers and applied predefined parameter combination sets sequentially based on molecular structures. This workflow produced high-quality <i>in silico</i> spectra for 81 compounds that achieved entropy similarity scores ≥700 and at least two matching fragment ions against the NIST23 library, yielding 71% spectral coverage. These results highlight the importance of optimizing simulation parameters and accounting for protomeric diversity to enhance the spectral quality and computational efficiency. This workflow provides a practical strategy to add mass spectral data for most compounds in the Blood Exposome Database at reasonable computational cost, supporting the spectral library expansion for improved compound annotation in exposomics.

Journal of the American Society for Mass SpectrometryVol. 36(10)
Paediatric Integrated Cancer Service (AU), Icahn School of Medicine at Mount Sinai (US)
National Institute of Environmental Health Sciences, National Center for Advancing Translational Sciences
Openalex Percentile: Top 24%
Metabolomics and Mass Spectrometry Studies
0.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.