HiTIME: An efficient model-selection approach for the detection of unknown drug metabolites in LC-MS data

Abstract

The identification of metabolites plays an important role in understanding drug efficacy and safety however these compounds are often difficult to identify in complex mixtures. One approach to identify drug metabolites involves utilising differentially isotopically labelled drug compounds to create unique isotopic signals that can be detected by liquid chromatography-mass spectrometry (LC-MS). User-friendly, efficient, computational tools that allow selective detection of these signals are lacking. We have developed an efficient open-source software tool called HiTIME (High-Resolution Twin-Ion Metabolite Extraction) which filters twin-ion signals in LC-MS data. The intensity of each data poi..