Finally, the KG structure allows for queries over heterogeneous datasets. As an illustration, we searched for analogs of a feature annotated as scopolamine from the The transformation of large metabolomics datasets in a queryable knowledge graph structure enhanced by the connection with public electronic resources offers exciting possibilities in the frame of drug discovery research programs. Indeed the whole process can be viewed as a "virtual fractionation" of the profiled extracts, which, when applied to large extract collections, has been proven to help in the removal of common metabolic background across extracts and to efficiently highlight chemical scaffolds responsible for the observed bioactivities at the extract level, without passing by the cumbersome physical fractionation of the individual extracts . Here, the approach is pushed further and leverages the precise results of the high-throughput reductionist mass-spectrometry fragmentation process -information is obtained down to the sub-molecular level in the forms of singular peaks and losses -and enhances them through a contextualization process inherent to the KG structure. The reconciliation of chemical structure identifiers allows to connect metabolite annotation results to public resources documenting the bioactivity of molecular structures (e.g.,