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In recent years, LC‐MS has become the golden standard for metabolomic studies. Indeed, LC is relatively easy to couple with the soft electrospray ionization. As a consequence, many tools have been developed for the structural annotation of tandem mass spectra. However, it is sometimes difficult to do data‐dependent acquisition (DDA), especially when developing new methods that stray from the classical LC‐MS workflow.    Objective  An old tool from petroleomics that has recently gained popularity in metabolomics, the Van Krevelen diagram, is adapted for an overview of the molecular diversity profile in lichens through high‐resolution mass spectrometry (HRMS).    Methods  A new method is benchmarked against the state‐of‐the‐art classification tool ClassyFire using a database containing most known lichen metabolites (n ≈ 2,000). Four lichens known for their contrasted chemical composition were selected, and extractions with apolar, aprotic polar, and protic polar solvents were performed to cover a wide range of polarities. Extracts were analyzed with direct infusion electrospray ionization mass spectrometry (DI‐ESI‐MS) and atmospheric solids analysis probe mass spectrometry (ASAP‐MS) techniques to be compared with the chemical composition described in the literature.    Results  The most common lichen metabolites were efficiently classified, with more than 90% of the molecules in some classes being matched with ClassyFire. Results from this method are consistent with the various extraction protocols in the present case study.    Conclusion  This approach is a rapid and efficient tool to gain structural insight regarding lichen metabolites analyzed by HRMS without relying on DDA by LC‐MS/MS analysis. It may notably be of use during the development phase of novel MS‐based metabolomic approaches.

New insights into the Van Krevelen diagram: Automated molecular formula determination from HRMS for a large chemical profiling of lichen extracts