QSAR Study of Some 1,3-Oxazolylphosphonium Derivatives as New Potent Anti-Candida Agents and Their Toxicity Evaluation

Author(s): Maria M. Trush*, Vasyl Kovalishyn, Alla D. Ocheretniuk, Oleksandr L. Kobzar, Maryna V. Kachaeva, Volodymyr S. Brovarets, Larisa O. Metelytsia.

Journal Name: Current Drug Discovery Technologies

Volume 16 , Issue 2 , 2019

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Abstract:

Background: The incidence of invasive fungal infections caused by Candida spp. has increased continuously in recent decades, especially in populations of immunocompromised patients or individuals hospitalized with serious underlying diseases. Therefore, the goal of our study was the search for new potent Candida albicans inhibitors via the development of QSAR models that could speed up this search process. A number of the most promising 1,3-oxazol-4-yltriphenylphosphonium derivatives with predicted activities were synthesized and experimentally tested. Furthermore, the toxicity of the studied compounds was determined in vitro using acetylcholinesterase enzyme as a biological marker.

Methods: The classification QSAR models were created using Random Forests (WEKA-RF), k-Nearest Neighbors and Associative Neural Networks methods and different combinations of descriptors on the Online Chemical Modeling Environment (OCHEM) platform. Аntifungal properties of the investigated compounds were performed using standard disk diffusion method. The enzyme inhibitory action of the compounds was determined by modified Ellman's method using acetylcholinesterase from the electric organ of Electrophorus electricus.

Results: Three classification QSAR models were developed by the WEKA-RF, k-NN and ASNN methods using the ALogPS, E-State indices and Dragon v.7 descriptors. The predictive ability of the models was tested through cross-validation, giving a balanced accuracy BA = 80-91%. All compounds demonstrated good antifungal properties against Candida spp. and slight inhibition of the acetylcholinesterase activity.

Conclusion: The high percentage of coincidence between the QSAR predictions and the experimental results confirmed the high predictive power of the developed QSAR models that can be applied as tools for finding new potential inhibitors against Candida spp. Furthermore, 1,3-oxazol-4- yl(triphenyl)phosphonium salts could be considered as promising candidates for the treatment of candidiasis and the disinfection of medical equipment.

Keywords: Antifungal activity, QSAR, oxazolylphosphonium salts, Candida albicans, acetylcholinesterase inhibition assay, fungal infections.

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Article Details

VOLUME: 16
ISSUE: 2
Year: 2019
Page: [204 - 209]
Pages: 6
DOI: 10.2174/1570163815666180418145422
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