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Centrifugal partition chromatography (CPC) and all countercurrent separation apparatus provide chemists with efficient ways to work with complex matrixes, especially in the domain of natural products. However, despite the great advances provided by these techniques, more efficient ways of analyzing the output flow would bring further enhancement. This study describe a hyphenated approach made by coupling NMR with CPC through a hybrid-indirect coupling made possible by using a solid phase extraction (SPE) apparatus intended for high-pressure liquid chromatography (HPLC)-NMR hyphenation. Some hardware changes were needed to adapt the incompatible flow-rates and a reverse-engineering approach that led to the specific software required to control the apparatus. 1D 1HNMR and 1H–1H correlation spectroscopy (COSY) spectra were acquired in reasonable time without the need for any solvent-suppression method thanks to the SPE nitrogen drying step. The reduced usage of expensive deuterated solvents from several hundreds of milliliters to the milliliter order is the major improvement of this approach compared to the previously published ones.

Dereplication represents a key step for rapidly identifying known secondary metabolites in complex biological matrices. In this context, liquid-chromatography coupled to high resolution mass spectrometry (LC-HRMS) is increasingly used and, via untargeted data-dependent MS/MS experiments, massive amounts of detailed information on the chemical composition of crude extracts can be generated. An efficient exploitation of such data sets requires automated data treatment and access to dedicated fragmentation databases. Various novel bioinformatics approaches such as molecular networking (MN) and in-silico fragmentation tools have emerged recently and provide new perspective for early metabolite identification in natural products (NPs) research. Here we propose an innovative dereplication strategy based on the combination of MN with an extensive in-silico MS/MS fragmentation database of NPs. Using two case studies, we demonstrate that this combined approach offers a powerful tool to navigate through the chemistry of complex NPs extracts, dereplicate metabolites, and annotate analogues of database entries.