PubChemLite for Exposomics with Predicted Collision Cross Section Values

PubChemLite for Exposomics is a curated subset of PubChem compiled from 10 annotation categories relevant to environmental exposure science. The dataset, created by Emma Schymanski at the University of Luxembourg, includes predicted collision cross section (CCS) values for 8 adducts, provided by the CCSbase project. This version was released on 1 January 2021, with a newer version available for monthly download.

Use Cases

• Compound identification in mass spectrometry based on predicted CCS values for 8 adducts.
• Exposure screening and prioritization based on chemical annotations from 10 categories like ToxicityInfo and FoodRelated.
• Training or validating computational mass spectrometry tools using the structured chemical annotations and predicted properties.

Strengths

• Integrates predicted CCS values for 8 specific adducts ([M+H]+, [M+K]+, etc.) from the CCSbase project.
• Curated from 10 major PubChem annotation categories including AgroChemInfo, ToxicityInfo, and DrugMedicInfo.
• Entries have been processed to remove substances that cause errors in tools like MetFrag, enhancing usability for specific applications.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale modeling.
• The specific version described is from January 2021, though a newer, monthly-updated version is noted.

Provenance

Source

PubChem, curated by University of Luxembourg researchers with CCS predictions from CCSbase.

Collection Method

Subset selected from PubChem Classification Browser categories, with CCS values predicted by a published model.

Time Range

Snapshot from 1 January 2021.

Freshness

The described snapshot is from 1 January 2021; a newer version updates monthly.