Literature DB >> 30103269

ChemFrag: Chemically meaningful annotation of fragment ion mass spectra.

Jördis-Ann Schüler1,2, Steffen Neumann3,4, Matthias Müller-Hannemann1, Wolfgang Brandt2.   

Abstract

Identification and structural determination of small molecules by mass spectrometry is an important step in chemistry and biochemistry. However, the chemically realistic annotation of a fragment ion spectrum can be a difficult challenge. We developed ChemFrag, for the detection of fragmentation pathways and the annotation of fragment ions with chemically reasonable structures. ChemFrag combines a quantum chemical with a rule-based approach. For different doping substances as test instances, ChemFrag correctly annotates fragment ions. In most cases, the predicted fragments are chemically more realistic than those from purely combinatorial approaches, or approaches based on machine learning. The annotation generated by ChemFrag often coincides with spectra that have been manually annotated by experts. This is a major advance in peak annotation and allows a more precise automatic interpretation of mass spectra.
© 2018 John Wiley & Sons, Ltd.

Keywords:  doping substances; fragment ion annotation; rule-based fragmentation; semi-empirical quantum mechanics

Year:  2018        PMID: 30103269     DOI: 10.1002/jms.4278

Source DB:  PubMed          Journal:  J Mass Spectrom        ISSN: 1076-5174            Impact factor:   1.982


  4 in total

1.  MET: a Java package for fast molecule equivalence testing.

Authors:  Jördis-Ann Schüler; Steffen Rechner; Matthias Müller-Hannemann
Journal:  J Cheminform       Date:  2020-12-17       Impact factor: 5.514

2.  PyFragMS-A Web Tool for the Investigation of the Collision-Induced Fragmentation Pathways.

Authors:  Yury Kostyukevich; Sergey Sosnin; Sergey Osipenko; Oxana Kovaleva; Lidiia Rumiantseva; Albert Kireev; Alexander Zherebker; Maxim Fedorov; Evgeny N Nikolaev
Journal:  ACS Omega       Date:  2022-03-08

Review 3.  Strategies for structure elucidation of small molecules based on LC-MS/MS data from complex biological samples.

Authors:  Zhitao Tian; Fangzhou Liu; Dongqin Li; Alisdair R Fernie; Wei Chen
Journal:  Comput Struct Biotechnol J       Date:  2022-09-07       Impact factor: 6.155

4.  MassGenie: A Transformer-Based Deep Learning Method for Identifying Small Molecules from Their Mass Spectra.

Authors:  Aditya Divyakant Shrivastava; Neil Swainston; Soumitra Samanta; Ivayla Roberts; Marina Wright Muelas; Douglas B Kell
Journal:  Biomolecules       Date:  2021-11-30
  4 in total

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