A Novel Chemical-Space-Dependent Strategy for Compound Selection in Non-target LC-HRMS Method Development Using...

Area of Science:

• Environmental Chemistry
• Analytical Chemistry
• Computational Chemistry

Background:

• The virtual chemical space is rapidly expanding, including environmental contaminants.
• Non-targeted analysis (NTA) using LC-HRMS is vital for measuring broad chemical regions.
• Current NTA methods using internal standards struggle with large, diverse chemical spaces.

Purpose of the Study:

• To develop a data-driven strategy for unbiasedly sampling diverse chemical structures for NTA LC-HRMS method development.
• To maximize physicochemical and structural diversity in candidate compound lists.
• To enhance the measurable chemical space coverage for NTA.

Main Methods:

• Utilized a data-driven workflow for unbiased sampling from extensive chemical spaces (e.g., U.S. EPA's CompTox).
• Employed precomputed PubChem descriptors (e.g., molecular weight, XLogP) to maximize diversity.
• Predicted LC-HRMS compatibility using molecular fingerprints for mobility and ionization efficiency.

Main Results:

• Generated measurable compound lists (MCLs) with broad, heterogeneous coverage.
• Achieved greater chemical coverage and predicted LC-HRMS applicability compared to conventional methods.
• Demonstrated enhanced NTA method development, validation, and boundary assessment capabilities.

Conclusions:

• The presented strategy offers a robust framework for expanding NTA's measurable chemical space while preserving diversity.
• This approach provides broader coverage for environmental and exposome contaminant analysis.
• Enables more comprehensive assessment of chemical exposures.