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  • Simultaneous screening of glutathione and cyanide adducts using precursor ion and neutral loss scans-dependent product ion spectral acquisition and data mining tools.

Simultaneous screening of glutathione and cyanide adducts using precursor ion and neutral loss scans-dependent product ion spectral acquisition and data mining tools.

Journal of the American Society for Mass Spectrometry (2012-03-07)
Wenying Jian, Hua-Fen Liu, Weiping Zhao, Elliott Jones, Mingshe Zhu
ABSTRACT

Drugs can be metabolically activated to soft and hard electrophiles, which are readily trapped by glutathione (GSH) and cyanide (CN), respectively. These adducts are often detected and structurally characterized using separate tandem mass spectrometry methods. We describe a new method for simultaneous screening of GSH and CN adducts using precursor ion (PI) and neutral loss (NL) scans-dependent product ion spectral acquisition and data mining tools on an triple quadrupole linear ion trap mass spectrometry. GSH, potassium cyanide, and their stable isotope labeled analogues were incubated with liver microsomes and a test compound. Negative PI scan of m/z 272 for detection of GSH adducts and positive NL scans of 27 and 29 Da for detection of CN adducts were conducted as survey scans to trigger acquisition of enhanced resolution (ER) spectrum and subsequent enhanced product ion (EPI) spectrum. Post-acquisition data mining of EPI data set using NL filters of 129 and 27 Da was then performed to reveal the GSH adducts and CN adducts, respectively. Isotope patterns and EPI spectra of the detected adducts were utilized for identification of their molecular weights and structures. The effectiveness of this method was evaluated by analyzing reactive metabolites of nefazodone formed from rat liver microsomes. In addition to known GSH- and CN-trapped reactive metabolites, several new CN adducts of nefazodone were identified. The results suggested that current approach is highly effective in the analysis of both soft and hard reactive metabolites and can be used as a high-throughput method in drug discovery.