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2016-04-15 - Article/Dans un journal avec peer-review - Anglais - 8 page(s)

Randazzo Giuseppe Marco, Tonoli David, Hambye Stéphanie , Guillarme Davy, Jeanneret Fabienne, Nurisso Alessandra, Goracci Laura, Boccard Julien, Rudaz Serge, "Prediction of retention time in reversed-phase liquid chromatography as a tool for steroid identification" in Analytica Chimica Acta

  • Edition : Elsevier, Amsterdam (The Netherlands)
  • Codes CREF : Chimie analytique (DI1314), Pharmacocinétique (DI3431), Sciences pharmaceutiques (DI3400), Techniques séparatives (DI2729)
  • Unités de recherche UMONS : Analyse pharmaceutique (M130)
  • Instituts UMONS : Institut des Sciences et Technologies de la Santé (Santé)

Abstract(s) :

(Anglais) The untargeted profiling of steroids constitutes a growing research field because of their importance as biomarkers of endocrine disruption. New technologies in analytical chemistry, such as ultra high-pressure liquid chromatography coupled with mass spectrometry (MS), offer the possibility of a fast and sensitive analysis. Nevertheless, difficulties regarding steroid identification are encountered when considering isotopomeric steroids. Thus, the use of retention times is of great help for the unambiguous identification of steroids. In this context, starting from the linear solvent strength (LSS) theory, quantitative structure retention relationship (QSRR) models, based on a dataset composed of 91 endogenous steroids and VolSurf + descriptors combined with a new dedicated molecular fingerprint, were developed to predict retention times of steroid structures in any gradient mode conditions. Satisfactory performance was obtained during nested cross-validation with a predictive ability (Q2) of 0.92. The generalisation ability of the model was further confirmed by an average error of 4.4% in external prediction. This allowed the list of candidates associated with identical monoisotopic masses to be strongly reduced, facilitating definitive steroid identification.