Natural products represent an inexhaustible source of new therapeutic agents. Their complex and constrained three-dimensional structures endow these molecules with exceptional biological properties, thereby giving them a major role in drug discovery programs. However, the pharmaceutical industry’s lack of interest in studying natural resources has been apparent since the early 2000s. Two main reasons for this disaffection can be put forward. The methods providing information on the bioactivity potential of natural products before their isolation are still lacking, but they are of key interest to target the isolation of valuable natural products only. On the other hand, the procedures for isolating and characterizing bioactive secondary metabolites from complex mixtures are often long, costly and tedious.
The steps necessary to prioritize extracts and to isolate compounds of interest in a targeted, rapid and effective manner are therefore essential. To address these issues, we have recently developed a molecular networking-based strategy [Fig. 1 ] consisting in deciphering the relationship between spectral networks and biological activities and further exploiting it to prioritize the isolation of bioactive secondary metabolites [1 ]–[3 ]. The core concept of this approach is based on the cross-linking of various information layers within a massive molecular network to spot bioactive scaffolds. Assuming that spectral dissimilarity within a taxonomically homogeneous set of samples could imply chemical uniqueness, the generation of these multi-informative maps unifying structural data, taxonomical information, and bioassay results allows bioactivities to be associated with taxon-specific scaffolds.
Fig. 1 Molecular Networking-based approach for sample prioritisation and targeted isolation of new bioactive metabolites from Euphorbiaceae extracts.
