Enhancing throughput of glutathione adduct formation studies and structural identification using a software-assisted workflow based on high resolution mass spectrometry (HRMS) data 

October 2016.

E.N. Cece-Esencan, F. Fontaine, G. Plasencia, M. Teppner, A. Brink, A. PahlerI. Zamora.


The bioactivation of drugs to Reactive Metabolites (RM) has been related to drug-induced liver injury and hypersensitivity reactions in patients. Therefore, many pharmaceutical companies are investigating the potential to form reactive metabolites in vitro as an integral part of the optimization of drug candidates. A computerassisted workflow to efficiently analyze larger numbers of compounds for the formation of glutathione trappable RM is presented here. A set of 95 compounds with known bioactivation potential was selected for this study.

Incubations with human liver microsomes were prepared with GSH. The acquisition of MS/MS spectra was triggered by ion intensity. MS with singly and doubly charged ions were used for peak detection and MS/MS spectra were used for structural elucidation. A confidence classification system for the GSH peak detection (high, medium, low) was developed based on the detection of characteristic fragment ions or neutral losses and applied to remove potential false positive results. A comparative analysis of the HRMS results with literature data was carried out.

The most frequently observed Neutral Loss (NL) found in singly charged GSH adducts (drug-glutathione conjugates) were, the Neutral Loss (NL, 129 Da) and Fragment Ion (FI, m/z 308) and in the doubly charged ones the Fragment Ion (FI, m/z 130). These NL and FI were used to identify GSH-related drug metabolites. MS/MS spectra were inspected to aid structural elucidations: 17% of drug substrates and 29 % of GSH adduct metabolites were identified with only doubly charged ions, stressing the importance of considering this charge state in the identification workflow.

A total of 41 compounds that form GSH adducts were retrieved from literature (HRMS, identified 28 compounds (68%) in high confidence, and the same result was obtained using precursor ion scan). By the confidence analysis of GSH peaks, the quality of the each GSH adduct was determined. 

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