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CANPA: Computer-Assisted Natural Products Anticipation

preprint
submitted on 18.04.2019 and posted on 23.04.2019 by Alexander Enrique Fox Ramos, Coralie Pavesi, Marc Litaudon, Vincent Dumontet, Erwan Poupon, Pierre Champy, Grégory Genta-Jouve, Mehdi Beniddir

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 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 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.

Funding

CONCYTEC 239-2015-FONDECYT

Mountains to Climb in the Chemistry of Highly Complex Indole Alkaloids: Methodology for Total Synthesis – Mount-Indole

Agence Nationale de la Recherche

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History

Email Address of Submitting Author

mehdi.beniddir@u-psud.fr

Institution

Université Paris-Sud-Faculty of pharmacy

Country

France

ORCID For Submitting Author

0000-0003-2153-4290

Declaration of Conflict of Interest

no conflict of interest

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