PubChemLite Plus Collision Cross Section (CCS) Values for Enhanced Interpretation of Nontarget Environmental Data

Area of Science:

• Environmental Science
• Metabolomics
• Exposomics
• Computational Chemistry

Background:

• Identifying relevant chemicals is challenging in large chemical databases for environmental and exposomics research using nontarget high resolution mass spectrometry (NT-HRMS).
• Existing chemical databases contain millions of compounds, many irrelevant to specific research needs, hindering efficient data interpretation.

Purpose of the Study:

• To create a dynamic, curated chemical collection, PubChemLite for Exposomics, to support environmental, metabolomics, and exposomics research.
• To provide researchers with tools and data for interpreting candidate chemical hits from NT-HRMS analyses.

Main Methods:

• Compiled PubChemLite from ten PubChem annotation categories.
• Enhanced the collection with patent, literature, and annotation counts, predicted partition coefficient (logP), and predicted collision cross section (CCS) values using CCSbase.
• Developed a new interface for browsing the collection, including historical data trends, and archived monthly versions on Zenodo under a CC-BY license.

Main Results:

• Established PubChemLite for Exposomics, a publicly accessible and dynamic chemical collection.
• Integrated predicted physicochemical properties (logP, CCS) to aid chemical identification.
• Ensured reproducibility and accessibility through open data, code, and regular archiving.

Conclusions:

• PubChemLite for Exposomics facilitates chemical identification in environmental and exposomics studies.
• The collection supports reproducible research through open science principles and accessible data.
• Future developments aim to increase the availability of experimental CCS values and expand the collection's utility.