1. CANPA: Computer-Assisted Natural Products Anticipation
- Author
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Erwan Poupon, Pierre Champy, Coralie Pavesi, Vincent Dumontet, Grégory Genta-Jouve, Alexander E. Fox Ramos, Mehdi A. Beniddir, Marc Litaudon, Biomolécules : Conception, Isolement, Synthèse (BioCIS), Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-Université de Cergy Pontoise (UCP), Université Paris-Seine-Université Paris-Seine, Université Paris-Saclay, Centre National de la Recherche Scientifique (CNRS), Institut de Chimie des Substances Naturelles (ICSN), Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC), Cibles Thérapeutiques et conception de médicaments (CiTCoM - UMR 8038), and Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)
- Subjects
Computer science ,Molecular Conformation ,Computational biology ,010402 general chemistry ,01 natural sciences ,Natural (archaeology) ,Analytical Chemistry ,chemistry.chemical_compound ,Alkaloids ,Tandem Mass Spectrometry ,[CHIM]Chemical Sciences ,Compound structure ,ComputingMilieux_MISCELLANEOUS ,Structure (mathematical logic) ,Biological Products ,Natural product ,Chemistry ,010401 analytical chemistry ,Pipeline (software) ,Data science ,0104 chemical sciences ,Plant Leaves ,Workflow ,Anticipation (artificial intelligence) ,Molecular networking ,Computer-Aided Design ,Alstonia - Abstract
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 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.
- Published
- 2019
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