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

PM Allard; F Olivon; D Righi; P Leyssen; F Roussi; M Litaudon; JL Wolfender

doi:10.1055/s-0036-1596223

Planta Medica, Inhaltsverzeichnis

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

Authors

PM Allard

¹School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, Quai Ernest-Ansermet 30, CH-1211 Geneva 4, Switzerland
F Olivon

²Institut de Chimie des Substances Naturelles CNRS UPR 2301, University Paris-Saclay, 1 Avenue de la Terrasse, 91198 Gif-sur-Yvette, France
D Righi

¹School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, Quai Ernest-Ansermet 30, CH-1211 Geneva 4, Switzerland
P Leyssen

³Laboratory for Virology and Experimental Chemotherapy, Rega Institute for Medical Research, KU Leuven Minderbroedersstraat 10, B-3000 Leuven, Belgium
F Roussi

²Institut de Chimie des Substances Naturelles CNRS UPR 2301, University Paris-Saclay, 1 Avenue de la Terrasse, 91198 Gif-sur-Yvette, France
M Litaudon

²Institut de Chimie des Substances Naturelles CNRS UPR 2301, University Paris-Saclay, 1 Avenue de la Terrasse, 91198 Gif-sur-Yvette, France
JL Wolfender

¹School of Pharmaceutical Sciences, EPGL, University of Geneva, University of Lausanne, Quai Ernest-Ansermet 30, CH-1211 Geneva 4, Switzerland

Abstract

Volltext

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.

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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