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Dernière mise à jour : Mai 2018

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UR 1264 - MYCSA : Mycologie et securite des aliments

MycSA

Mycologie & Sécurité des Aliments
INRA Bordeaux-Aquitaine
BP 81
33883 Villenave d'Ornon Cedex

Computational strategy for minimizing mycotoxins in cereal crops: Assessment of the biological activity of compounds resulting from virtual screening

A first evidence of the promising potential of computational approaches to discover new anti-mycotoxin solutions.

20 April 2022

Atanasova et al.-2022
Our new article in collaboration with LORIA (Inria, Fr) and EMBAPRA Agroindustria Tropical (Br)

 Atanasova V., Bresso E., Maigret B., Martins N.F., Richard-Forget, F. (2022). Computational strategy for minimizing mycotoxins in cereal crops: Assessment of the biological activity of compounds resulting from virtual screening. Molecules, 27, 2582. https://doi.org/10.3390/molecules27082582

Abstract: Cereal crops are frequently affected by toxigenic Fusarium species, among which the most common and worrying in Europe are Fusarium graminearum and Fusarium culmorum. These species are the causal agents of grain contamination with type B trichothecene (TCTB) mycotoxins. To help reduce the use of synthetic fungicides while guaranteeing low mycotoxin levels, there is an urgent need to develop new, efficient and environmentally-friendly plant protection solutions. Previously, F. graminearum proteins that could serve as putative targets to block the fungal spread and toxin production were identified and a virtual screening undertaken. Here, two selected compounds, M1 and M2, predicted, respectively, as the top compounds acting on the trichodiene synthase, a key enzyme of TCTB biosynthesis, and the 24-sterol-C-methyltransferase, a protein involved in ergosterol biosynthesis, were submitted for biological tests. Corroborating in silico predictions, M1 was shown to significantly inhibit TCTB yield by a panel of strains. Results were less obvious with M2 that induced only a slight reduction in fungal biomass. To go further, seven M1 analogs were assessed, which allowed evidencing of the physicochemical properties crucial for the anti-mycotoxin activity. Altogether, our results provide the first evidence of the promising potential of computational approaches to discover new anti-mycotoxin solutions.