Literature DB >> 28952028

Similarity of High-Resolution Tandem Mass Spectrometry Spectra of Structurally Related Micropollutants and Transformation Products.

Jennifer E Schollée1,2, Emma L Schymanski3, Michael A Stravs3,4, Rebekka Gulde3, Nikolaos S Thomaidis5, Juliane Hollender3,4.   

Abstract

High-resolution tandem mass spectrometry (HRMS2) with electrospray ionization is frequently applied to study polar organic molecules such as micropollutants. Fragmentation provides structural information to confirm structures of known compounds or propose structures of unknown compounds. Similarity of HRMS2 spectra between structurally related compounds has been suggested to facilitate identification of unknown compounds. To test this hypothesis, the similarity of reference standard HRMS2 spectra was calculated for 243 pairs of micropollutants and their structurally related transformation products (TPs); for comparison, spectral similarity was also calculated for 219 pairs of unrelated compounds. Spectra were measured on Orbitrap and QTOF mass spectrometers and similarity was calculated with the dot product. The influence of different factors on spectral similarity [e.g., normalized collision energy (NCE), merging fragments from all NCEs, and shifting fragments by the mass difference of the pair] was considered. Spectral similarity increased at higher NCEs and highest similarity scores for related pairs were obtained with merged spectra including measured fragments and shifted fragments. Removal of the monoisotopic peak was critical to reduce false positives. Using a spectral similarity score threshold of 0.52, 40% of related pairs and 0% of unrelated pairs were above this value. Structural similarity was estimated with the Tanimoto coefficient and pairs with higher structural similarity generally had higher spectral similarity. Pairs where one or both compounds contained heteroatoms such as sulfur often resulted in dissimilar spectra. This work demonstrates that HRMS2 spectral similarity may indicate structural similarity and that spectral similarity can be used in the future to screen complex samples for related compounds such as micropollutants and TPs, assisting in the prioritization of non-target compounds. Graphical Abstract ᅟ.

Entities:  

Keywords:  High-resolution tandem mass spectrometry; Micropollutants; Non-target screening; Spectral similarity; Transformation products

Year:  2017        PMID: 28952028     DOI: 10.1007/s13361-017-1797-6

Source DB:  PubMed          Journal:  J Am Soc Mass Spectrom        ISSN: 1044-0305            Impact factor:   3.109


  27 in total

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Journal:  Anal Bioanal Chem       Date:  2015-06-13       Impact factor: 4.142

6.  Extended Suspect and Non-Target Strategies to Characterize Emerging Polar Organic Contaminants in Raw Wastewater with LC-HRMS/MS.

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Journal:  Environ Sci Technol       Date:  2015-10-07       Impact factor: 9.028

7.  HMDB: the Human Metabolome Database.

Authors:  David S Wishart; Dan Tzur; Craig Knox; Roman Eisner; An Chi Guo; Nelson Young; Dean Cheng; Kevin Jewell; David Arndt; Summit Sawhney; Chris Fung; Lisa Nikolai; Mike Lewis; Marie-Aude Coutouly; Ian Forsythe; Peter Tang; Savita Shrivastava; Kevin Jeroncic; Paul Stothard; Godwin Amegbey; David Block; David D Hau; James Wagner; Jessica Miniaci; Melisa Clements; Mulu Gebremedhin; Natalie Guo; Ying Zhang; Gavin E Duggan; Glen D Macinnis; Alim M Weljie; Reza Dowlatabadi; Fiona Bamforth; Derrick Clive; Russ Greiner; Liang Li; Tom Marrie; Brian D Sykes; Hans J Vogel; Lori Querengesser
Journal:  Nucleic Acids Res       Date:  2007-01       Impact factor: 16.971

8.  MS2Analyzer: A software for small molecule substructure annotations from accurate tandem mass spectra.

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Authors:  Sebastian Böcker; Kai Dührkop
Journal:  J Cheminform       Date:  2016-02-01       Impact factor: 5.514

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Journal:  Anal Chem       Date:  2019-10-22       Impact factor: 6.986

2.  Use of Passive and Grab Sampling and High-Resolution Mass Spectrometry for Non-Targeted Analysis of Emerging Contaminants and Their Semi-Quantification in Water.

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5.  Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships.

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7.  AI/ML-driven advances in untargeted metabolomics and exposomics for biomedical applications.

Authors:  Lauren M Petrick; Noam Shomron
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Review 8.  Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics.

Authors:  Ivana Blaženović; Tobias Kind; Jian Ji; Oliver Fiehn
Journal:  Metabolites       Date:  2018-05-10
  8 in total

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