Accurate Prediction of Ion Mobility Collision Cross-Section Using Ion’s Polarizability and Molecular Mass with Limited Data.

We extend our congratulations to Dr. Pattipong Wisanpitayakorn and Assoc. Prof. Dr. Sakda Khoomrung of the Siriraj Center of Research Excellence in Metabolomic and Systems Biology (SiCORE-MSB), Faculty of Medicine Siriraj Hospital, Mahidol University, for their new research publication in the Journal of Chemical Information and Modeling on February 23, 2024. The publication can be accessed via this link:

In this study, the research team has identified and validated that ions’ polarizability and mass-to-charge ratio (m/z) exhibit the most significant predictive power for traveling-wave IM CCS values compared to other physicochemical properties of ions. Building upon this finding, the team demonstrated that a precisely predicted CCS database customized for each experimental setup can be constructed, even with limited datasets. These discoveries bolster confidence in compound annotation via ion mobility mass spectrometry, offering substantial benefits to metabolomics and lipidomics research.
Furthermore, this article was selected as the supplementary cover for the March 11, 2024, issue of the Journal of Chemical Information and Modeling, accessible at