Planta Med 2016; 82(S 01): S1-S381
DOI: 10.1055/s-0036-1596223
Abstracts
Georg Thieme Verlag KG Stuttgart · New York

Massive multi-informative molecular networks to mine New-Caledonian chemodiversity for antiviral compounds

PM Allard
1   School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, Quai Ernest-Ansermet 30, CH-1211 Geneva 4, Switzerland
,
F Olivon
2   Institut de Chimie des Substances Naturelles CNRS UPR 2301, University Paris-Saclay, 1 Avenue de la Terrasse, 91198 Gif-sur-Yvette, France
,
D Righi
1   School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, Quai Ernest-Ansermet 30, CH-1211 Geneva 4, Switzerland
,
P Leyssen
3   Laboratory for Virology and Experimental Chemotherapy, Rega Institute for Medical Research, KU Leuven Minderbroedersstraat 10, B-3000 Leuven, Belgium
,
F Roussi
2   Institut de Chimie des Substances Naturelles CNRS UPR 2301, University Paris-Saclay, 1 Avenue de la Terrasse, 91198 Gif-sur-Yvette, France
,
M Litaudon
2   Institut de Chimie des Substances Naturelles CNRS UPR 2301, University Paris-Saclay, 1 Avenue de la Terrasse, 91198 Gif-sur-Yvette, France
,
JL Wolfender
1   School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, Quai Ernest-Ansermet 30, CH-1211 Geneva 4, Switzerland
› Author Affiliations
Further Information

Publication History

Publication Date:
14 December 2016 (online)

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    Molecular networking has recently appeared as a paradigm-shifting tool allowing to explore complex metabolomes in a radically new way [1]. Large amount of data accumulated when acquiring data-dependent MS fragmentation experiments on complex extracts of diverse natural sources can now be automatically organized according to their similarity. Since tandem MS/MS spectra reflect the structure of the fragmented molecules, these networks can group metabolites according to their structural similarities. One of the great advantages of the network-based representation is the possibility to visualize complex sets of data in order to interpret them globally. It then becomes possible to observe patterns and links that would not have emerged from the browsing of the same data represented as plain spread sheets [2]. Here we took advantage of this network representation to map different information layers (taxonomy, bioactivity) on top of the molecular network generated over a collection of 293 crude EtOAc extracts of New-Caledonian Euphorbiaceae. The objective was to use this multi-informative network as a “molecular treasure map” to mine the chemodiversity of this set of plants and directly target bioactive and/or original chemical scaffolds. Guided by this massive multi-informative molecular network, the MS-targeted isolation of specific compounds from Neoguillauminia sp. was achieved and their antiviral potential against the Chikungunya virus (CHIKV) was evaluated.

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    Keywords: Massive multi-informative molecular networks, data-visualization, MS-targeted isolation, chikungunya virus, Neoguillauminia sp., bioinformatics.

    References:

    [1] Watrous J, Roach P, Alexandrov T, Heath B. S, Yang J. Y, Kersten R. D, van der Voort M, Pogliano K, Gross H, Raaijmakers JM, Moore BS, Laskin J, Bandeira N, Dorrestein PC. Proc Natl Acad Sci USA 2012; 109: E1743-E1752

    [2] Reda K, Febretti A, Knoll A, Aurisano J, Leigh J, Johnson A, Papka M. E, Hereld M. IEEE Comput Graph Appl 2013; 33: 38 – 48


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    No conflict of interest has been declared by the author(s).

     
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