Towards eco-metabolomics: NADES-guided extraction enables semi-quantitative metabolomics for Melissa officinalis

• 20 NADES and 3 traditional solvents were used to extract MO leaves. • Extraction selectivity was predicted using COSMO-RS and validated with standards. • Molar concentration of annotated metabolites was predicted using MS2Quant. • NADES demonstrated extraction selectivity across biochemical classes. • The entire workflow allowed the implementation of the known melissa metabolome. In recent years, there has been a growing emphasis on the development of green extraction techniques that minimize environmental impact while maximizing yield of the extracted compounds. To this aim, in this study we investigated the potential of green solvents for extracting bioactive compounds from Melissa officinalis (MO) leaves. Specifically, we focus on the application of 20 Natural Deep Eutectic Solvents (NADES) with a relative polarity ranging from 0.34 to 1.29. Their extraction affinity against a set of 11 plant metabolites was predicted using COSMO-RS software and experimentally validated using quantitative LC HRMS analysis. Subsequently, the same extracts were subjected to non-target metabolomics to uncover the NADES selectivity towards the wide spectrum of MO leaf metabolites. Data preprocessing and feature alignment were performed using MZmine, and aligned features were annotated using SIRIUS+CSI:FingerID. Overall, 249 and 195, metabolites were annotated in positive and negative ionization ion mode, respectively. Additionally, to have a more accurate view of the different NADES extraction capacity, we adopted a semi-quantitative approach that enables the prediction of concentration for all the annotated metabolites (N = 444). The results highlighted the selectivity of some NADES in extracting very diverse biochemical classes, providing valuable insights into the composition and concentration of bioactive compounds. Interestingly, thymol-menthol NADES demonstrated the ability to efficiently extract a broad range of bioactive compounds, yielding a metabolome comparable to that obtained with conventional ethanolic. Overall, the entire workflow facilitated the green extraction and annotation of known bioactive molecules that had never been described in MO.