Karadzić, Milica

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  • Karadzić, Milica (1)
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Electrostatic and Topological Features as Predictors of Antifungal Potential of Oxazolo Derivatives as Promising Compounds in Treatment of Infections Caused by Candida albicans

Kovacević, Strahinja; Karadzić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija; Ivanović, Evica; Vojnović, Matilda

(Slovensko Kemijsko Drustvo, Ljubljana, 2018) 

TY  - JOUR
AU  - Kovacević, Strahinja
AU  - Karadzić, Milica
AU  - Podunavac-Kuzmanović, Sanja
AU  - Jevrić, Lidija
AU  - Ivanović, Evica
AU  - Vojnović, Matilda
PY  - 2018
UR  - http://aspace.agrif.bg.ac.rs/handle/123456789/4628
AB  - The results presented in this study include the prediction of the antifungal activity of 24 oxazolo derivatives based on their topological and electrostatic molecular descriptors, derived from the 2D molecular structures. The artificial neural network (ANN) method was applied as a regression tool. The input data for ANN modeling were selected by stepwise selection (SS) procedure. The ANN modeling resulted in three networks with the outstanding statistical characteristics. High predictivity of the established networks was confirmed by comparisons of the predicted and experimental data and by the residuals analysis. The obtained results indicate the usefulness of the formed ANNs in precise prediction of minimum inhibitory concentrations of the analyzed compounds towards Candida albicans. The Sum of Ranking Differences (SRD) method was used in this study to reveal possible grouping of the compounds in the space of the variables used in ANN modeling. The obtained results can be considered to be a contribution to development of new antifungal drugs structurally based on oxazole core, particularly nowadays when there is a lack of highly efficient antimycotics.
PB  - Slovensko Kemijsko Drustvo, Ljubljana
T2  - Acta Chimica Slovenica
T1  - Electrostatic and Topological Features as Predictors of Antifungal Potential of Oxazolo Derivatives as Promising Compounds in Treatment of Infections Caused by Candida albicans
EP  - 491
IS  - 3
SP  - 483
VL  - 65
DO  - 10.17344/acsi.2017.3532
ER  - 
@article{
author = "Kovacević, Strahinja and Karadzić, Milica and Podunavac-Kuzmanović, Sanja and Jevrić, Lidija and Ivanović, Evica and Vojnović, Matilda",
year = "2018",
abstract = "The results presented in this study include the prediction of the antifungal activity of 24 oxazolo derivatives based on their topological and electrostatic molecular descriptors, derived from the 2D molecular structures. The artificial neural network (ANN) method was applied as a regression tool. The input data for ANN modeling were selected by stepwise selection (SS) procedure. The ANN modeling resulted in three networks with the outstanding statistical characteristics. High predictivity of the established networks was confirmed by comparisons of the predicted and experimental data and by the residuals analysis. The obtained results indicate the usefulness of the formed ANNs in precise prediction of minimum inhibitory concentrations of the analyzed compounds towards Candida albicans. The Sum of Ranking Differences (SRD) method was used in this study to reveal possible grouping of the compounds in the space of the variables used in ANN modeling. The obtained results can be considered to be a contribution to development of new antifungal drugs structurally based on oxazole core, particularly nowadays when there is a lack of highly efficient antimycotics.",
publisher = "Slovensko Kemijsko Drustvo, Ljubljana",
journal = "Acta Chimica Slovenica",
title = "Electrostatic and Topological Features as Predictors of Antifungal Potential of Oxazolo Derivatives as Promising Compounds in Treatment of Infections Caused by Candida albicans",
pages = "491-483",
number = "3",
volume = "65",
doi = "10.17344/acsi.2017.3532"
}
Kovacević, S., Karadzić, M., Podunavac-Kuzmanović, S., Jevrić, L., Ivanović, E.,& Vojnović, M.. (2018). Electrostatic and Topological Features as Predictors of Antifungal Potential of Oxazolo Derivatives as Promising Compounds in Treatment of Infections Caused by Candida albicans. in Acta Chimica Slovenica
Slovensko Kemijsko Drustvo, Ljubljana., 65(3), 483-491.
https://doi.org/10.17344/acsi.2017.3532
Kovacević S, Karadzić M, Podunavac-Kuzmanović S, Jevrić L, Ivanović E, Vojnović M. Electrostatic and Topological Features as Predictors of Antifungal Potential of Oxazolo Derivatives as Promising Compounds in Treatment of Infections Caused by Candida albicans. in Acta Chimica Slovenica. 2018;65(3):483-491.
doi:10.17344/acsi.2017.3532 .
Kovacević, Strahinja, Karadzić, Milica, Podunavac-Kuzmanović, Sanja, Jevrić, Lidija, Ivanović, Evica, Vojnović, Matilda, "Electrostatic and Topological Features as Predictors of Antifungal Potential of Oxazolo Derivatives as Promising Compounds in Treatment of Infections Caused by Candida albicans" in Acta Chimica Slovenica, 65, no. 3 (2018):483-491,
https://doi.org/10.17344/acsi.2017.3532 . .
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