Revisiting In-Gas Transformations of Quinate Conjugates Through the LC-qTOF-MS and Molecular Networking Topology.

RATIONALE

The emergence of computational metabolomics tools such as molecular networking and machine learning-based platforms like SIRIUS has significantly advanced MS-based metabolomics studies. These tools enable rapid metabolite identification by deciphering complex fragmentation patterns and chemical transformations occurring during mass spectrometry analysis.

METHODS

In this study, methanolic extracts of Viscum combreticola, a plant recently shown to contain a rich composition of cinnamic acid-quinates conjugates, were analyzed using the LC-qTOF-MS in combination with a molecular networking approach to explore the chemical complexity of quinate conjugates.

RESULTS

Findings of this study through molecular networking topology revealed that quinic acid undergoes a series of in-gas chemical transformations, including dehydration (-HO) and decarboxylation (-CO). These transformations yield unique product ions, some of which are associated with other organic acids, such as isocitric acid. By employing the MS search option on the GNPS2 platform, molecules exhibiting these product ions were readily identified in this study. Therefore, highlighting the potential of this function in GNPS2 for tracing unique fragmentation patterns synonymous with certain molecules that can be used to confirm their identity visually.

CONCLUSION

The MS search function can aid in the discovery of new compounds containing the diagnostic ions of interest that could otherwise be easily missed with manual annotation. This study presents a potential validation approach of looking at multiple product ions to confirm the identity of a molecule, particularly in the presence of other compounds with similar fragmentation pathways or shared fragment ions.