A quantitative structure?antifungal activity relationship study of oxygenated aromatic essential oil compounds using data structuring and PLS regression analysis

Abstract

Twenty two oxygenated aromatic essential oil compounds were chosen for the study of the antifungal activity against two wood-decaying fungi, the white-rot Trametes versicolor, which mainly metabolizes lignin, and the brown-rot Coniophoha puteana, which digests cellulose in plant cell walls. Minimal inhibitory concentrations (MICs) were determined by the agar dilution method, using dimethyl sulfoxide (DMSO) as the solvent for the selected compounds and potato-dextrose agar (PDA) as the growth medium for both fungi. The MICs were then used to generate a tree structure, which represents the structuring of the essential oil compounds by the nature and position of the substituents in their aromatic rings, and as dependent variables (log(1/MIC)) in the QSAR analysis. Data structuring proved that a relationship between the molecular structures of the essential oil compounds and their antifungal activity exists, and the hypotheses derived therefrom were complemented by performing a QSAR analysis using the partial least squares (PLS) method. Statistically significant PLS models were obtained with the 1-octanol-water partition coefficient (C log P), the energy of the highest occupied molecular orbital (E(HOMO)), and the number of hydrogen-bond donor atoms in the molecules of the compounds studied (Donor) for T. versicolor and with C log P and the fractional negative surface area (FNSA1) for C. puteana.

Dysregulation of Ion Homeostasis by Antifungal Agents

“…Similar results were reported in other studies (Voda et al, 2004). Carvacrol exhibited a MIC of 0.008% (or 79.8 μg/ml) against Saccharomyces cerevisiae , which was 1,500 times more effective than Oregano oil.…”

Inhibitory effect of 10 natural phenolic compounds on Fusarium verticillioides. A structure–property–activity relationship study

“…Voda et al (2004) demonstrated that 80% of the variation in the antifungal activity of phenolic compounds may be explained by the lipophilicity (represented by log P) descriptor. Verma and Hansch (2006) also reported a relationship between hydrophobicity and cytotoxic activities in a study on the cytotoxicity of organic compounds in cancer cells.…”

“…QSAR studies are widely used to predict the activity of new chemical compounds and to establish a mechanism for a better understanding of chemicalebiological interactions in drug-design process. Although QSAR studies on the biological action of phenols have been reported for different biological systems (Dambolena, Zygadlo, & Rubinstein, 2011;Greenberg, Dodds, & Tian, 2008;Verma & Hansch, 2006;Voda, Boh, & Vrtacnik, 2004), no QSAR studies on F. verticillioides growth have yet been performed.…”

Terpenes: Natural Products for Controlling Insects of Importance to Human Health—A Structure-Activity Relationship Study

“…The biological activity of a chemical compound depends on the ability to reach the specific target molecule and its subsequent capacity to interact with it ( [125] and references therein). Hence, the three major types of interactions that the modeller must deal with are the hydrophobic, electronic, and steric ones [126].…”