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.
