Bioactive Natural Products Prioritization Using Massive Multi-informational Molecular Networks.

Détails

ID Serval
serval:BIB_88AF9364A8A0
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Bioactive Natural Products Prioritization Using Massive Multi-informational Molecular Networks.
Périodique
ACS Chemical Biology
Auteur(s)
Olivon F., Allard P.M., Koval A., Righi D., Genta-Jouve G., Neyts J., Apel C., Pannecouque C., Nothias L.F., Cachet X., Marcourt L., Roussi F., Katanaev V.L., Touboul D., Wolfender J.L., Litaudon M.
ISSN
1554-8937 (Electronic)
ISSN-L
1554-8929
Statut éditorial
Publié
Date de publication
2017
Peer-reviewed
Oui
Volume
12
Numéro
10
Pages
2644-2651
Langue
anglais
Résumé
Natural products represent an inexhaustible source of novel therapeutic agents. Their complex and constrained three-dimensional structures endow these molecules with exceptional biological properties, thereby giving them a major role in drug discovery programs. However, the search for new bioactive metabolites is hampered by the chemical complexity of the biological matrices in which they are found. The purification of single constituents from such matrices requires such a significant amount of work that it should be ideally performed only on molecules of high potential value (i.e., chemical novelty and biological activity). Recent bioinformatics approaches based on mass spectrometry metabolite profiling methods are beginning to address the complex task of compound identification within complex mixtures. However, in parallel to these developments, methods providing information on the bioactivity potential of natural products prior to their isolation are still lacking and are of key interest to target the isolation of valuable natural products only. In the present investigation, we propose an integrated analysis strategy for bioactive natural products prioritization. Our approach uses massive molecular networks embedding various informational layers (bioactivity and taxonomical data) to highlight potentially bioactive scaffolds within the chemical diversity of crude extracts collections. We exemplify this workflow by targeting the isolation of predicted active and nonactive metabolites from two botanical sources (Bocquillonia nervosa and Neoguillauminia cleopatra) against two biological targets (Wnt signaling pathway and chikungunya virus replication). Eventually, the detection and isolation processes of a daphnane diterpene orthoester and four 12-deoxyphorbols inhibiting the Wnt signaling pathway and exhibiting potent antiviral activities against the CHIKV virus are detailed. Combined with efficient metabolite annotation tools, this bioactive natural products prioritization pipeline proves to be efficient. Implementation of this approach in drug discovery programs based on natural extract screening should speed up and rationalize the isolation of bioactive natural products.

Mots-clé
Animals, Biological Products/chemistry, Biological Products/pharmacology, Cercopithecus aethiops, Classification, Combinatorial Chemistry Techniques, Drug Design, Drug Discovery, Image Processing, Computer-Assisted, Molecular Structure, Structure-Activity Relationship, Vero Cells, Wnt Proteins/genetics, Wnt Proteins/metabolism
Pubmed
Web of science
Open Access
Oui
Création de la notice
19/09/2017 13:27
Dernière modification de la notice
20/08/2019 14:47
Données d'usage