This review focuses on the ever-expanding repertoire of molecular networking applications for targeting natural products.

This Data Descriptor announces the submission to public repositories of the monoterpene indole alkaloid database (MIADB), a cumulative collection of 172 tandem mass spectrometry (MS/MS) spectra from multiple research projects conducted in eight natural product chemistry laboratories since the 1960s. All data have been annotated and organized to promote reuse by the community. Being a unique collection of these complex natural products, these data can be used to guide the dereplication and targeting of new related monoterpene indole alkaloids within complex mixtures when applying computer-based approaches, such as molecular networking. Each spectrum has its own accession number from CCMSLIB00004679916 to CCMSLIB00004680087 on the GNPS. The MIADB is available for download from MetaboLights under the identifier: MTBLS142 ( https://www.ebi.ac.uk/metabolights/MTBLS142 ).

Three new monoterpene indole alkaloids (1-3) have been isolated from the bark of Geissospermum laeve, together with the known alkaloids (-)-leuconolam (4), geissolosimine (5), and geissospermine (6). The structures of 1-3 were elucidated by analysis of their HRMS and NMR spectroscopic data. The absolute configuration of geissolaevine (1) was deduced from the comparison of experimental and theoretically calculated ECD spectra. The isolation workflow was guided by a molecular networking-based dereplication strategy using an in-house database of monoterpene indole alkaloids. In addition, five known compounds previously undescribed in the Geissospermum genus were dereplicated from the G. laeve alkaloid extract network and were assigned with various levels of identification confidence. The antiparasitic activities against Plasmodium falciparum and Leishmania donovani as well as the cytotoxic activity against the MRC-5 cell line were determined for compounds 1-5.

Traditional natural products discovery workflows implying a combination of different targeting strategies, including structure-and/or bioactivity-based approaches, afford no information about new compound structures until late in the discovery pipeline. By integrating a MS/MS prediction module and a collaborative library of (bio)chemical transformations, we have developed a new platform, coined MetWork, that is capable of anticipating the structural identity of metabolites starting from any identified compound. In our quest to discover new monoterpene indole alkaloids, we demonstrate the utility of the MetWork platform by anticipating the structures of five previously undescribed sarpagine-like N-oxide alkaloids that have been targeted and isolated from the leaves of Alstonia balansae using a molecular networking-based dereplication strategy fueled by computer-generated annotations. This study constitutes the first example of nonpeptidic molecular networking-based natural product discovery workflow, in which the targeted structures were initially generated, and therefore anticipated by a computer prior to their isolation.

Five new monoterpene indole alkaloids (1–5), including four serpentinine-related bisindoles and one alstonine derivative monomer, have been isolated from the aerial parts of Picralima nitida. Their structures were elucidated by analysis of their HRMS and NMR spectroscopic data, and their absolute configurations were deduced from the comparison of experimental and simulated ECD spectra. In addition, two known compounds (6 and 7), previously undescribed from P. nitida, have also been purified. The compound isolation workflow was guided by a molecular networking-based dereplication strategy. Twenty-three compounds were dereplicated from the EtOH extract of P. nitida and fractions network and were assigned various levels of identification confidence. The antiparasitic activities against Plasmodium falciparum as well as the cytotoxic activity against the MRC-5 cell line were determined for compounds 1–7.

Total synthesis of the anticancer peptide natural product yakuamide A is reported. Its b-tert-hydroxy amino acids were prepared by regioselective aminohydroxylation involving a chiral mesyloxycarbamate reagent. Stereospecific construction of the E-and Z-DIle residues was accomplished through a one-pot reaction featuring anti dehydration, azide reduction, and O!N acyl transfer. Alkene isomerization was negligible during this process. These methods enabled a highly convergent and efficient synthetic route to the natural product.

<p>Traditional natural products discovery workflows implying a combination of different targeting strategies including structure- and/or bioactivity-based approaches, afford no information about new compound structure until late in the discovery pipeline. By integrating a MS/MS prediction module and a collaborative library of (bio)chemical transformations, we have developed a new platform, coined MetWork, that is able of anticipating the structural identity of metabolites starting from any identified compound. In our quest to discover new monoterpene indole alkaloids, we demonstrate the utility of the MetWork platform by anticipating the structures of five previously undescribed sarpagine-like <i>N</i>-oxide alkaloids that have been targeted and isolated from the leaves of <i>Alstonia</i> <i>balansae</i> using a molecular networking-based dereplication strategy fueled by computer-generated annotations. This study constitutes the first example of a natural product discovery workflow, termed CANPA, in which the targeted structures were initially generated and therefore anticipated by a computer prior to their isolation.</p>

<p>Traditional natural products discovery workflows implying a combination of different targeting strategies including structure- and/or bioactivity-based approaches, afford no information about new compound structure until late in the discovery pipeline. By integrating a MS/MS prediction module and a collaborative library of (bio)chemical transformations, we have developed a new platform, coined MetWork, that is able of anticipating the structural identity of metabolites starting from any identified compound. In our quest to discover new monoterpene indole alkaloids, we demonstrate the utility of the MetWork platform by anticipating the structures of five previously undescribed sarpagine-like <i>N</i>-oxide alkaloids that have been targeted and isolated from the leaves of <i>Alstonia</i> <i>balansae</i> using a molecular networking-based dereplication strategy fueled by computer-generated annotations. This study constitutes the first example of non peptidic molecular networking-based natural product discovery workflow, in which the targeted structures were initially generated, and therefore anticipated by a computer prior to their isolation.<br></p>