Molecular networking (MN) is becoming a standard bioinformatics tool in the metabolomic community. Its paradigm is based on the observation that compounds with a high degree of chemical similarity share comparable MS2 fragmentation pathways. To afford a clear separation between MS2 spectral clusters, only the most relevant similarity scores are selected using dedicated filtering steps requiring time-consuming parameter optimization. Depending on the filtering values selected, some scores are arbitrarily deleted and a part of the information is ignored. The problem of creating a reliable representation of MS2 spectra data sets can be solved using algorithms developed for dimensionality reduction and pattern recognition purposes, such as t-distributed stochastic neighbor embedding (t-SNE). This multivariate embedding method pays particular attention to local details by using nonlinear outputs to represent the entire data space. To overcome the limitations inherent to the GNPS workflow and the networking architecture, we developed MetGem. Our software allows the parallel investigation of two complementary representations of the raw data set, one based on a classic GNPS-style MN and another based on the t-SNE algorithm. The t-SNE graph preserves the interactions between related groups of spectra, while the MN output allows an unambiguous separation of clusters. Additionally, almost all parameters can be tuned in real time, and new networks can be generated within a few seconds for small data sets. With the development of this unified interface (), we fulfilled the need for a dedicated, user-friendly, local software for MS2 comparison and spectral network generation.

Molecular networking is becoming more and more popular into the metabolomic community to organize tandem mass spectrometry (MS) data. Even though this approach allows the treatment and comparison of large data sets, several drawbacks related to the MS-Cluster tool routinely used on the Global Natural Product Social Molecular Networking platform (GNPS) limit its potential. MS-Cluster cannot distinguish between chromatography well-resolved isomers as retention times are not taken into account. Annotation with predicted chemical formulas is also not implemented and semiquantification is only based on the number of MS scans. We propose to introduce a data-preprocessing workflow including the preliminary data treatment by MZmine 2 followed by a homemade Python script freely available to the community that clears the major previously mentioned GNPS drawbacks. The efficiency of this workflow is exemplified with the analysis of six fractions of increasing polarities obtained from a sequential supercritical CO extraction of Stillingia lineata leaves.

From a set of 292 Euphorbiaceae extracts, the use of a molecular networking (MN)-based prioritization approach highlighted three clusters (MN1−3) depicting ions from the bark extract of Codiaeum peltatum. Based on their putative antiviral potential and structural novelty, the MS-guided purification of compounds present in MN1 and MN2 afforded two new daphnane-type diterpenoid orthoesters (DDO), codiapeltines A (1) and B (2), the new actephilols B (3) and C (4), and four known 1,4-dioxane-fused phenanthrene dimers (5−8). The structures of the new compounds were elucidated by NMR spectroscopic data analysis, and the absolute configurations of compounds 1 and 2 were deduced by comparison of experimental and calculated ECD spectra. Codiapeltine B (2) is the first daphnane bearing a 9,11,13-orthoester moiety, establishing a new major structural class of DDO. Compounds 1−8 and four recently reported monoterpenyl quinolones (9− 12) detected in MN3 were investigated for their selective activities against chikungunya virus replication and their antipolymerase activities against the NS5 proteins of dengue and zika viruses. Compounds 3−8 exhibited strong inhibitory activities on both dengue and zika NS5 in primary assays, but extensive biological analyses indicated that only actephilol B (3) displayed a specific interaction with the NS5 targets.

Most of the polyvalent organoiodine compounds derive from iodoarenes, which are released in stoichiometric amounts in any reaction mediated by λ3- or λ5-iodanes. In parallel to the development of solid-supported reagents or reactions catalytic in iodine, a third strategy has emerged to address this issue in terms of sustainability. The atom-economy of transformations involving stoichiometric amounts of λ3- or λ5-iodanes, thus, has been improved by designing tandem reactions that allows for incorporating the aryl motif into the products through a subsequent one-pot nucleophilic addition or catalytic coupling reaction. This review summarizes the main achievements reported in this area.

We report herein the diastereoselective C­(sp3)–H arylation of glycosides. A wide range of β- and α-glycosides proved able to selectively undergo Pd­(II)-catalyzed coupling with diverse aryl iodides to assemble a large library of functionalized 3-arylglycosylamides. DFT calculations were performed to elucidate the unexpected trans stereoselectivity of this reaction.

An expedient method for the synthesis of fused glycosylquinolin-2-ones and glycosylspirooxindoles through an unprecedented intramolecular Pd-catalyzed anomeric C-H activation of the sugar moiety of 2-bromophenyl glycosylcarboxamides is reported. The scope of the reaction is broad and tolerates a wide range of functional groups.

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Iodine(III) reagents are used in catalytic one-pot reactions, first as both oxidants and substrates, then as cross-coupling partners, to afford chiral polyfunctionalized amines. The strategy relies on an initial catalytic auto C(sp(3) )-H amination of the iodine(III) oxidant, which delivers an amine-derived iodine(I) product that is subsequently used in palladium-catalyzed cross-couplings to afford a variety of useful building blocks with high yields and excellent stereoselectivities. This study demonstrates the concept of self-amination of the hypervalent iodine reagents, which increases the value of the aryl moiety.