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Mining molecular structure databases: Identification of small molecules based on fragmentation mass spectrometry data
Author(s) -
Hufsky Franziska,
Böcker Sebastian
Publication year - 2016
Publication title -
mass spectrometry reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.035
H-Index - 126
eISSN - 1098-2787
pISSN - 0277-7037
DOI - 10.1002/mas.21489
Subject(s) - chemistry , fragmentation (computing) , mass spectrometry , molecule , data mining , database , computational chemistry , chromatography , computer science , organic chemistry , operating system
Mass spectrometry (MS) is a key technology for the analysis of small molecules. For the identification and structural elucidation of novel molecules, new approaches beyond straightforward spectral comparison are required. In this review, we will cover computational methods that help with the identification of small molecules by analyzing fragmentation MS data. We focus on the four main approaches to mine a database of metabolite structures, that is rule‐based fragmentation spectrum prediction, combinatorial fragmentation, competitive fragmentation modeling, and molecular fingerprint prediction. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:624–633, 2017