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CANPA: Computer-Assisted Natural Products Anticipation
- Source :
- Analytical Chemistry, Analytical Chemistry, American Chemical Society, 2019, 91 (17), pp.11247-11252. ⟨10.1021/acs.analchem.9b02216⟩
- Publication Year :
- 2019
- Publisher :
- American Chemical Society (ACS), 2019.
-
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.
- 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
Subjects
Details
- ISSN :
- 15206882 and 00032700
- Volume :
- 91
- Database :
- OpenAIRE
- Journal :
- Analytical Chemistry
- Accession number :
- edsair.doi.dedup.....0435c119db4cc6f82ed91c29a447980d
- Full Text :
- https://doi.org/10.1021/acs.analchem.9b02216