LC-MSMS identification of small molecules: SmileMS, a small molecule identification platform applied to clinical toxicology

Abstract

LLC-MSMS combined with library search approaches is getting popular as an alternative to existing methods in clinical toxicology, for the screening of toxics. Such screenings are traditionally operated in emergency units, where they act as an early diagnostic test of the patient condition. As a result, routine laboratories need robust and easy to use software solutions that can handle the complexity of spectra generated by LCMSMS as well as deliver high quality results in the shortest time possible. In this thesis, we present a small molecule identification platform called SmileMS. This platform was developed to be used in applications based on LC-MSMS identification but also to act as an exploration platform for further investigation in the field of small molecule identification. Throughout the conception of SmileMS, these investigations concerned four areas: the creation scoring models, the handling of spectral libraries, the theoretical fragmentation of molecules, and the setting of engineering strategies enabling software exploration of data