Identification of small molecules using accurate mass MS/MS search. Issue 4 (24th April 2017)

• Record Type: Journal Article
• Authors: Kind, Tobias; Tsugawa, Hiroshi; Cajka, Tomas; Ma, Yan; Lai, Zijuan; Mehta, Sajjan S.; Wohlgemuth, Gert; Barupal, Dinesh Kumar; Showalter, Megan R.; Arita, Masanori; Fiehn, Oliver
• Is Part Of: Mass spectrometry reviews. Volume 37:Issue 4(2018)
• Page Start: 513
• Page End: 532
• Publication Date: 2017-04-24
• Subjects: compound identification -- high‐resolution mass spectrometry -- library search -- tandem mass spectrometry; Mass spectrometry -- Periodicals; 543
• DOI: 10.1002/mas.21535
• Languages: English
• ISSNs: 0277-7037

Abstract

Abstract : Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS‐based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data‐dependent and data‐independent methods, library scoring algorithms, as well as post‐curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS‐DIAL, Mass Frontier, SmileMS, Mass++, and XCMS 2 to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed.