Mining molecular structure databases: Identification of small molecules based on fragmentation mass spectrometry data

Abstract

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.

Transformation of the gas‐phase favored O‐protomer of p‐aminobenzoic acid to its unfavored N‐protomer by ion activation in the presence of water vapor: An ion‐mobility mass spectrometry study

“…In fact, several computational programs such as Mass Frontier (HighChem, Ltd. Bratislava, Slovakia), CFM‐ID (http://cfmid.wishartlab.com), and ACD/MS Fragmenter (Advanced Chemistry Labs, Toronto, Canada) are available for interpretation of mass spectra. However, in a recent review, Hufsky and Böcker concluded that searching spectral libraries will not lead to identification of most compounds. For most fragmentation modeling attempts, a specific lead structure is assumed for each compound and then the program “chops” it without any regard to fragmentation principles.…”

Structure elucidation of metabolite x17299 by interpretation of mass spectrometric data

“…Consequently, structure characterization typically ends, regardless of the result, after searching available mass spectral libraries of known compounds and rarely continues with purification and NMR analysis (Wishart 2011; Bingol et al 2016; Watson 2013). Some software products have recently been developed to predict fragmentation spectra from molecular structures and to streamline the search process, but to our knowledge, little success has been achieved to elucidate true unknown structures solely from mass spectra using software programs (Hufsky and Böcker 2016; Tsugawa et al 2016; Knolhoff et al 2016; Treutler et al 2016; Ma et al 2014; Kind et al 2014). LC/MS has also been widely applied to the structure characterization of large molecules, such as proteins, glycans, and antibody-drug conjugates (Aebersold and Mann 2016; Leymarie and Zaia 2012; Beck et al 2016).…”

A tutorial in small molecule identification via electrospray ionization‐mass spectrometry: The practical art of structural elucidation

“…The types of additional information were already depicted in Table (ie, presence of the spectrum or analyte structure in a knowledgebase, a priori expectations on the unknown analyte). Several comprehensive reviews have been published on the computational aspects of MS‐based structural elucidation . Although it is not our intention to provide the reader with extensive lists of all published informatics tools, we mention a few of particular interest.…”

“…This advanced web‐based tool allows one to search the Pubchem database of chemical structures with a high resolving power MS and MS/MS spectrum. The technical details of the techniques described here are beyond the scope of this tutorial, but were the subject of a recent review . It is noteworthy that these machine‐learning approaches can only be developed with high‐quality training data, that can be retrieved from the spectral libraries discussed earlier.…”

“…Several comprehensive reviews have been published on the computational aspects of MS-based structural elucidation. [90][91][92][93] Although it is not our intention to provide the reader with extensive lists of all published informatics tools, we mention a few of particular interest. Because this review is a tutorial, we focus on explanations of the general informatics strategies and concepts, instead of enumerating the characteristics of all available software tools.…”