Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 427461
Title Substructure-based annotation of high-resolution multistage MSn spectral trees
Author(s) Ridder, L.O.; Hooft, J.J.J. van der; Verhoeven, S.; Vos, R.C.H. de; Schaik, R. van; Vervoort, Jacques
Source Rapid Communications in Mass Spectrometry 26 (2012)20. - ISSN 0951-4198 - p. 2461 - 2471.
DOI https://doi.org/10.1002/rcm.6364
Department(s) Biochemistry
PRI BIOS Applied Metabolic Systems
EPS-1
VLAG
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) tandem mass-spectrometry - metabolite identification - discriminating signals - fragmentation trees - accurate mass - metabolomics - dissociation - elucidation - information - software
Abstract RATIONALE High-resolution multistage MSn data contains detailed information that can be used for structural elucidation of compounds observed in metabolomics studies. However, full exploitation of this complex data requires significant analysis efforts by human experts. In silico methods currently used to support data annotation by assigning substructures of candidate molecules are limited to a single level of MS fragmentation. METHODS We present an extended substructure-based approach which allows annotation of hierarchical spectral trees obtained from high-resolution multistage MSn experiments. The algorithm yields a hierarchical tree of substructures of a candidate molecule to explain the fragment peaks observed at consecutive levels of the multistage MSn spectral tree. A matching score is calculated that indicates how well the candidate structure can explain the observed hierarchical fragmentation pattern. RESULTS The method is applied to MSn spectral trees of a set of compounds representing important chemical classes in metabolomics. Based on the calculated score, the correct molecules were successfully prioritized among extensive sets of candidates structures retrieved from the PubChem database. CONCLUSIONS The results indicate that the inclusion of subsequent levels of fragmentation in the automatic annotation of MSn data improves the identification of the correct compounds. We show that, especially in the case of lower mass accuracy, this improvement is not only due to the inclusion of additional fragment ions in the analysis, but also to the specific hierarchical information present in the MSn spectral trees. This method may significantly reduce the time required by MS experts to analyze complex MSn data. Copyright (c)proves 2012 John Wiley & Sons, Ltd.
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