Fragmentation trees reloaded

被引:153
作者
Boecker, Sebastian [1 ]
Duehrkop, Kai [1 ]
机构
[1] Univ Jena, Ernst Abbe Pl 2, D-07743 Jena, Germany
关键词
Mass spectrometry; Metabolites; Natural products; Computational methods; Fragmentation trees; FLIGHT MASS-SPECTROMETRY; METABOLITE IDENTIFICATION; ACCURATE MASS; STRUCTURAL SIMILARITY; SPECTRAL SIMILARITY; MOLECULAR FORMULAS; METABOLOMICS; ANNOTATION; PREDICTION; DATABASE;
D O I
10.1186/s13321-016-0116-8
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Background: Untargeted metabolomics commonly uses liquid chromatography mass spectrometry to measure abundances of metabolites; subsequent tandem mass spectrometry is used to derive information about individual compounds. One of the bottlenecks in this experimental setup is the interpretation of fragmentation spectra to accurately and efficiently identify compounds. Fragmentation trees have become a powerful tool for the interpretation of tandem mass spectrometry data of small molecules. These trees are determined from the data using combinatorial optimization, and aim at explaining the experimental data via fragmentation cascades. Fragmentation tree computation does not require spectral or structural databases. To obtain biochemically meaningful trees, one needs an elaborate optimization function (scoring). Results: We present a new scoring for computing fragmentation trees, transforming the combinatorial optimization into a Maximum A Posteriori estimator. We demonstrate the superiority of the new scoring for two tasks: both for the de novo identification of molecular formulas of unknown compounds, and for searching a database for structurally similar compounds, our method SIRIUS 3, performs significantly better than the previous version of our method, as well as other methods for this task. Conclusion: SIRIUS 3 can be a part of an untargeted metabolomics workflow, allowing researchers to investigate unknowns using automated computational methods.
引用
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页数:26
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