A spectroscopic test suggests that fragment ion structure annotations in MS/MS libraries are frequently incorrect.
Lara van TeteringSylvia SpiesQuirine D K WildemanKas J HouthuijsRianne E van OutersterpJonathan K MartensRon A WeversDavid Scott WishartGiel BerdenJos OomensPublished in: Communications chemistry (2024)
Modern untargeted mass spectrometry (MS) analyses quickly detect and resolve thousands of molecular compounds. Although features are readily annotated with a molecular formula in high-resolution small-molecule MS applications, the large majority of them remains unidentified in terms of their full molecular structure. Collision-induced dissociation tandem mass spectrometry (CID-MS 2 ) provides a diagnostic molecular fingerprint to resolve the molecular structure through a library search. However, for de novo identifications, one must often rely on in silico generated MS 2 spectra as reference. The ability of different in silico algorithms to correctly predict MS 2 spectra and thus to retrieve correct molecular structures is a topic of lively debate, for instance in the CASMI contest. Underlying the predicted MS 2 spectra are the in silico generated product ion structures, which are normally not used in de novo identification, but which can serve to critically assess the fragmentation algorithms. Here we evaluate in silico generated MS n product ion structures by comparison with structures established experimentally by infrared ion spectroscopy (IRIS). For a set of three dozen product ion structures from five precursor molecules, we find that virtually all fragment ion structure annotations in three major in silico MS 2 libraries (HMDB, METLIN, mzCloud) are incorrect and caution the reader against their use for structure annotation of MS/MS ions.
Keyphrases
- mass spectrometry
- high resolution
- ms ms
- liquid chromatography
- high performance liquid chromatography
- tandem mass spectrometry
- gas chromatography
- multiple sclerosis
- molecular docking
- ultra high performance liquid chromatography
- small molecule
- capillary electrophoresis
- single molecule
- high resolution mass spectrometry
- machine learning
- simultaneous determination
- liquid chromatography tandem mass spectrometry
- solid phase extraction
- deep learning
- density functional theory
- gas chromatography mass spectrometry
- endothelial cells
- low birth weight
- single cell
- preterm birth