Literature DB >> 22390817

Identifying the unknowns by aligning fragmentation trees.

Florian Rasche1, Kerstin Scheubert, Franziska Hufsky, Thomas Zichner, Marco Kai, Aleš Svatoš, Sebastian Böcker.   

Abstract

Mass spectrometry allows sensitive, automated, and high-throughput analysis of small molecules. In principle, tandem mass spectrometry allows us to identify "unknown" small molecules not in any database, but the automated interpretation of such data is in its infancy. Fragmentation trees have recently been introduced for the automated analysis of the fragmentation patterns of small molecules. We present a method for the automated comparison of such fragmentation patterns, based on aligning the compounds' fragmentation trees. We cluster compounds based solely on their fragmentation patterns and show a good agreement with known compound classes. Fragmentation pattern similarities are strongly correlated with the chemical similarity of molecules. We present a tool for searching a database for compounds with fragmentation pattern similar to an unknown sample compound. We apply this tool to metabolites from Icelandic poppy. Our method allows fully automated computational identification of small molecules that cannot be found in any database.

Entities:  

Mesh:

Year:  2012        PMID: 22390817     DOI: 10.1021/ac300304u

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  22 in total

1.  Searching molecular structure databases with tandem mass spectra using CSI:FingerID.

Authors:  Kai Dührkop; Huibin Shen; Marvin Meusel; Juho Rousu; Sebastian Böcker
Journal:  Proc Natl Acad Sci U S A       Date:  2015-09-21       Impact factor: 11.205

2.  Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics.

Authors:  Arpana Vaniya; Oliver Fiehn
Journal:  Trends Analyt Chem       Date:  2015-06-01       Impact factor: 12.296

3.  Molecular Formula Identification Using Isotope Pattern Analysis and Calculation of Fragmentation Trees.

Authors:  Kai Dührkop; Franziska Hufsky; Sebastian Böcker
Journal:  Mass Spectrom (Tokyo)       Date:  2014-07-18

4.  Systematic structural characterization of metabolites in Arabidopsis via candidate substrate-product pair networks.

Authors:  Kris Morreel; Yvan Saeys; Oana Dima; Fachuang Lu; Yves Van de Peer; Ruben Vanholme; John Ralph; Bartel Vanholme; Wout Boerjan
Journal:  Plant Cell       Date:  2014-03-31       Impact factor: 11.277

Review 5.  Mass spectrometry of structurally modified DNA.

Authors:  Natalia Tretyakova; Peter W Villalta; Srikanth Kotapati
Journal:  Chem Rev       Date:  2013-02-26       Impact factor: 60.622

Review 6.  Mass spectrometry tools and workflows for revealing microbial chemistry.

Authors:  Tal Luzzatto-Knaan; Alexey V Melnik; Pieter C Dorrestein
Journal:  Analyst       Date:  2015-08-07       Impact factor: 4.616

7.  Structural investigation of ribosomally synthesized natural products by hypothetical structure enumeration and evaluation using tandem MS.

Authors:  Qi Zhang; Manuel Ortega; Yanxiang Shi; Huan Wang; Joel O Melby; Weixin Tang; Douglas A Mitchell; Wilfred A van der Donk
Journal:  Proc Natl Acad Sci U S A       Date:  2014-08-04       Impact factor: 11.205

8.  Recent advances and prospects of computational methods for metabolite identification: a review with emphasis on machine learning approaches.

Authors:  Dai Hai Nguyen; Canh Hao Nguyen; Hiroshi Mamitsuka
Journal:  Brief Bioinform       Date:  2019-11-27       Impact factor: 11.622

Review 9.  Mass spectrometry of natural products: current, emerging and future technologies.

Authors:  Amina Bouslimani; Laura M Sanchez; Neha Garg; Pieter C Dorrestein
Journal:  Nat Prod Rep       Date:  2014-05-07       Impact factor: 13.423

10.  Chemically informed analyses of metabolomics mass spectrometry data with Qemistree.

Authors:  Anupriya Tripathi; Yoshiki Vázquez-Baeza; Julia M Gauglitz; Mingxun Wang; Kai Dührkop; Mélissa Nothias-Esposito; Deepa D Acharya; Madeleine Ernst; Justin J J van der Hooft; Qiyun Zhu; Daniel McDonald; Asker D Brejnrod; Antonio Gonzalez; Jo Handelsman; Markus Fleischauer; Marcus Ludwig; Sebastian Böcker; Louis-Félix Nothias; Rob Knight; Pieter C Dorrestein
Journal:  Nat Chem Biol       Date:  2020-11-16       Impact factor: 15.040

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