High-Throughput Measurement and Machine Learning-Based Prediction of Collision Cross Sections for Drugs and Drug Metabolites.

ABSTRACT: Drug metabolite identification is a bottleneck of drug metabolism studies due to the need for time-consuming chromatographic separation and structural confirmation. Ion mobility-mass spectrometry (IM-MS), on the other hand, separates analytes on a rapid (millisecond) time scale and enables the measurement of collision cross section (CCS), a unique physical property related to an ion's gas-phase size and shape, which can be used as an additional parameter for identification of unknowns. A current limitation to the application of IM-MS to the identification of drug metabolites is the lack of reference CCS values. In this work, we assembled a large-scale database of drug and drug metabolite CCS values using high-throughput in vitro drug metabolite generation and a rapid IM-MS analysis with au

SUBMITTER: Ross DH 

PROVIDER: S-EPMC9165597 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature