3. FOOD ChEMISTRy & bIOTEChNOLOGy 3.1. Lectures
3. FOOD ChEMISTRy & bIOTEChNOLOGy 3.1. Lectures
3. FOOD ChEMISTRy & bIOTEChNOLOGy 3.1. Lectures
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Chem. Listy, 102, s265–s1311 (2008) Food Chemistry & Biotechnology<br />
pharmacological activity. This evidence was clearly described<br />
in lipid theory advanced by Meyer and Overton. According<br />
to this theory, log P is a measure of hydrophobicity which is<br />
important for the penetration and distribution of the drug, but<br />
also for the interaction of drug with receptors. Therefore, it<br />
can be suggested that lipophilic properties have to be checked<br />
for designing of potent antifungal agents as they are deciding<br />
factors for its activity.<br />
Fig. 2. Plot of residual values against the experimentally observed<br />
log 1/c MIC values<br />
Conclusions<br />
QSAR analysis was performed to estimate the quantitative<br />
effects of the lipophilicity parameter, logP, of the different<br />
substituted 2-amino and 2-methylbenzimidazole derivatives<br />
on their antifungal activity against Saccharomyces<br />
cerevisiae. log P values were calculated for each molecule,<br />
and high-quality mathematical model relating the inhibitory<br />
activity, log 1/c MIC , and log P was defined . . For the estimation<br />
of the predictive ability of this model, the cross-validation<br />
statistical technique was applied. Comparison of the linear,<br />
quadratic and cubic relationships showed that the cubic equation<br />
was the most appropriate for prediction of antifungal<br />
activity of the investigated class of molecules. It is concluded<br />
that strong influence of the partition coefficient, log P, is<br />
important for the inhibitory activity and this parameter is usually<br />
related to pharmacological activity. The obtained mathematical<br />
model was used to predict antifungal activity of the<br />
benzimidazoles investigated and close agreement between<br />
experimental and predicted values was obtained. It indicates<br />
that this model can be successfully applied to predict the antifungal<br />
activity of these class of molecules.<br />
This work has been supported by Ministry of Science<br />
and Environment Protection of the Republic of Serbia as are<br />
the part of the project No. 142028<br />
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