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@ARTICLE{Majewsky:132658,
      author       = {M. Majewsky and D. Castel and L. Le Dret and P. Johann$^*$
                      and D. Jones$^*$ and S. Pfister$^*$ and W. E. Haefeli and J.
                      Burhenne},
      title        = {{S}ystematic identification of suspected anthelmintic
                      benzimidazole metabolites using {LC}-{MS}/{MS}.},
      journal      = {Journal of pharmaceutical and biomedical analysis},
      volume       = {151},
      issn         = {0731-7085},
      address      = {New York, NY [u.a.]},
      publisher    = {Science Direct},
      reportid     = {DKFZ-2018-00318},
      pages        = {151 - 158},
      year         = {2018},
      abstract     = {Metabolite reference standards are often not available,
                      which results in a lack of MS/MS spectra for library
                      matching. Consequently, the identification of suspected
                      metabolites proves to be challenging. The present study aims
                      at structurally elucidating the MS/MS fragmentation behavior
                      of selected benzimidazole anthelmintics to theoretically
                      predict characteristic product ions for rapid and systematic
                      tentative metabolite identification. A set of common
                      characteristic product ions was identified from accurate
                      mass MS/MS experiments for five parent compounds. It was
                      hypothesized that the mass shift of any metabolic
                      transformation at the parent molecule also is observable in
                      the mass spectrum of the corresponding metabolite. This was
                      tested and verified with six metabolite reference standards
                      and subsequently, formulated as a general prediction scheme.
                      The approach was integrated into a rapid MSeQTOF workflow
                      and tested in mouse plasma for mebendazole and its
                      metabolites. The presented scheme allows the prediction of
                      characteristic product ions for suspected unknown
                      metabolites. These can be matched with measured product ions
                      of suspected metabolites for tentative identification. The
                      theoretically predicted spectra can contribute to the
                      tentative identification of unknown compounds in non-target
                      and suspect screening approaches.},
      cin          = {B062 / L101},
      ddc          = {610},
      cid          = {I:(DE-He78)B062-20160331 / I:(DE-He78)L101-20160331},
      pnm          = {312 - Functional and structural genomics (POF3-312)},
      pid          = {G:(DE-HGF)POF3-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:29328982},
      doi          = {10.1016/j.jpba.2017.12.056},
      url          = {https://inrepo02.dkfz.de/record/132658},
}