We have assembled a comprehensive collision cross section (CCS) database covering a wide range of chemical space, such as small molecules, drugs, metabolites, lipids, peptides, carbohydrates, etc. The CCS measurements in the database were made on a variety of instruments (both drift tube and traveling wave) using nitrogen as the drift gas. The instrument platform and method for each CCS measurement are specified for each entry for user’s reference. Using this database, we have built a high-performance and comprehensive machine learning-based CCS prediction model on diverse chemical structures. To allow easy access of the database and the prediction model, we have assembled the combined CCS database and the prediction model into a convenient web interface at https://CCSbase.net.

Interactive visualization and query of the comprehensive CCS database:

High-performance CCS prediction using SMILE structure: