Development of a statistical tool to predict anticandidal activity of essential oils

There is a general agreement that natural volatile compounds of essentials oils from plants provide a great potential for discovery of new antimicrobial drugs such as anticandidal ones. In this work, 60 commercial essential oils were analysed by GC/MS and their inhibitory activity against the growth of three Candida strains was evaluated. We then conducted a chemometric analysis and proposed a tool to predict their capacity to inhibit the Candida sp. developpment. Raw data were pretreated and normalised using MZmine2.2 software. It was possible to identify some of the natural compounds with anticandidal properties using two statistical tools in XLstat7.5: hierarchical clustering analysis (HAC) and principal component analysis (PCA). We highlighted that essential oils containing limonene, 1,8-cineole, linalool and linalyl acetate were mostly inactive, whereas eugenol, thymol, carvacrol, geraniol, geranial and neral as major components of the oils seems to be linked to an interesting anticandidal activity. Linear regressions showed a high correlation between the concentration of these molecules and their antifungal activity. Exceptions to these general tendencies could be characteristic of synergistic or antagonistic interactions.