Imidazolium Ionic Liquids as Potential Anti-Candida Inhibitors: QSAR Modeling and Experimental Studies

Title:Imidazolium Ionic Liquids as Potential Anti-Candida Inhibitors: QSAR Modeling and Experimental Studies

Volume: 13 Issue: 2

Author(s): Diana Hodyna, Vasyl Kovalishyn, Sergiy Rogalsky, Volodymyr Blagodatnyi and Larisa Metelytsia

Affiliation:

Keywords: Imidazolium ionic liquids, Candida albicans, antifungal activity, QSAR, Associative Neural Networks, k-Nearest Neighbors, Random Forests.

Abstract: Quantitative structure-activity relationships (QSAR) of imidazolium ionic liquids (ILs) as inhibitors of C. albicans collection strains (IOA-109, KCTC 1940, ATCC 10231) have been studied. Predictive QSAR models were built using different descriptor sets for a set of 88 ionic liquids with known minimum inhibitory concentrations (MIC) against C. albicans. We applied the state-of-the-art QSAR methodologies such as WEKA Random Forest (RF) as a binary classifier, Associative Neural Networks (ASNN) and k-Nearest Neighbors (k-NN) to build continuum non-linear regression models. The obtained models were validated using a 5-fold cross-validation approach and resulted in the prediction accuracies of 80% ± 5.0 for the classification models and q² = 0.73-0.87 for the non-linear regression models. Biological testing of newly synthesized 1,3-dialkylimidazolium ionic liquids with predicted activity was performed by disco-diffusion method against C. albicans ATCC 10231 M885 strain and clinical isolates C. albicans, C. krusei and C. glabrata strains. The high percentage of coincidence between the QSAR predictions and the experimental results confirmed the high predictive power of the developed QSAR models within the applicability domain of new imidazolium ionic liquids.

Cite this article as:

Hodyna Diana, Kovalishyn Vasyl, Rogalsky Sergiy, Blagodatnyi Volodymyr and Metelytsia Larisa, Imidazolium Ionic Liquids as Potential Anti-Candida Inhibitors: QSAR Modeling and Experimental Studies, Current Drug Discovery Technologies 2016; 13 (2) . https://dx.doi.org/10.2174/1570163813666160510122201