Quantitative-structure-activity relationship study to predict the antifungal activity of essential oils against Fusarium verticillioides

Abstract

Fusarium verticillioides is the principal fungal pathogen affecting corn maize both in the field and/or during grain storage. The efficiency of essential oils (EOs) as antifungals has been well established against many phytopathogenic fungi, so the aim of this QSAR study was to design a mathematical model using arbitrary descriptors based on EO components to predict antifungal activity. The EOs that reported the highest activity were Origanum spp. The results obtained in the QSAR analysis revealed a statistically significant model (P <0.0001) which predicted the antifungal activity in a linear equation based on three EO component descriptors: the content of oxygenated sesquiterpenes, content of phenolic compounds and/or the content of peroxide compounds by their composition. These descriptors permitted antifungal activity to be predicted of new EOs without any additional information required, and thus this could be an aid in the search for EOs with the capacity to affect F. verticillioides growth. To our knowledge, the present study constitutes the first QSAR study on the antifungal activity of the EOs. In addition, the strategy used to design the descriptors can be used in the study of other types of complex mixtures.