title: Imidazolium Ionic Liquids as Potential Anti-Candida Inhibitors: QSAR Modeling and Experimental Studies.
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.
authors.affiliation: Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Sciences of Ukraine, 1 Murmanska Street, Kyiv-94, 02660, Ukraine. dianahodyna@gmail.com.
authors.forename: Diana
authors.initials: D
authors.lastname: Hodyna
authors.forename: Vasyl
authors.initials: V
authors.lastname: Kovalishyn
authors.forename: Sergiy
authors.initials: S
authors.lastname: Rogalsky
authors.forename: Volodymyr
authors.initials: V
authors.lastname: Blagodatnyi
authors.forename: Larisa
authors.initials: L
authors.lastname: Metelytsia
mesh_terms: D000935:Antifungal Agents / Q000737:chemistry / Q000494:pharmacology*; D002176:Candida albicans / Q000187:drug effects* / Q000254:growth & development; D007093:Imidazoles / Q000737:chemistry / Q000494:pharmacology*; D052578:Ionic Liquids / Q000737:chemistry / Q000494:pharmacology*; D000069550:Machine Learning; D008958:Models, Molecular; D016571:Neural Networks, Computer; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis; D015203:Reproducibility of Results
chemical_list: D000935:Antifungal Agents; D007093:Imidazoles; D052578:Ionic Liquids