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

Jennifer E. Schollée, Emma L. Schymanski, Michael A. Stravs, Rebekka Gulde, Nikolaos S. Thomaidis, Juliane Hollender

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.