Simulating Collision-Induced Dissociation Tandem Mass Spectrometry (CID-MS/MS) for the Blood Exposome Database Using...

Area of Science:

• Computational Chemistry
• Analytical Chemistry
• Environmental Health

Background:

• Many chemicals in exposome databases lack essential mass spectral data due to unavailable reference standards.
• Expanding spectral libraries is crucial for accurate compound identification in exposomics research.

Purpose of the Study:

• To utilize computational chemistry to generate mass spectral data for compounds lacking experimental spectra.
• To develop and validate a scalable computational framework for extending spectral libraries.

Main Methods:

• Employed quantum-chemistry-based software (QCxMS) to generate collision-induced dissociation mass spectra for 121 compounds from the Blood Exposome Database.
• Developed a computational framework integrating QCxMS with parameter selection strategies and coverage criteria.
• Systematically explored protomeric isomers and applied sequential parameter combinations based on molecular structures.

Main Results:

• Generated high-quality in silico spectra for 81 compounds, achieving 71% spectral coverage.
• Validated spectra using entropy similarity scores (≥700) and matching fragment ions against the NIST23 library.
• Demonstrated the importance of optimizing simulation parameters and considering protomeric diversity for spectral quality.

Conclusions:

• The developed workflow offers a practical and cost-effective strategy to augment mass spectral data for the Blood Exposome Database.
• This approach supports spectral library expansion, enhancing compound annotation capabilities in exposomics.
• Optimized computational methods are vital for advancing chemical identification in environmental health studies.