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1,3-Oxazole derivatives of cytisine as potential inhibitors of glutathione reductase of Candida spp.: QSAR modeling, docking analysis and experimental study of new anti-Candida agents.

Authors :
Metelytsia LO
Trush MM
Kovalishyn VV
Hodyna DM
Kachaeva MV
Brovarets VS
Pilyo SG
Sukhoveev VV
Tsyhankov SA
Blagodatnyi VM
Semenyuta IV
Source :
Computational biology and chemistry [Comput Biol Chem] 2021 Feb; Vol. 90, pp. 107407. Date of Electronic Publication: 2020 Nov 05.
Publication Year :
2021

Abstract

Natural products as well as their derivatives play a significant role in the discovery of new biologically active compounds in the different areas of our life especially in the field of medicine. The synthesis of compounds produced from natural products including cytisine is one approach for the wider use of natural substances in the development of new drugs. QSAR modeling was used to predict and select of biologically active cytisine-containing 1,3-oxazoles. The eleven most promising compounds were identified, synthesized and tested. The activity of the synthesized compounds was evaluated using the disc diffusion method against C. albicans M 885 (ATCC 10,231) strain and clinical fluconazole-resistant Candida krusei strain. Molecular docking of the most active compounds as potential inhibitors of the Candida spp. glutathione reductase was performed using the AutoDock Vina. The built classification models demonstrated good stability, robustness and predictive power. The eleven cytisine-containing 1,3-oxazoles were synthesized and their activity against Candida spp. was evaluated. Compounds 10, 11 as potential inhibitors of the Candida spp. glutathione reductase demonstrated the high activity against C. albicans M 885 (ATCC 10,231) strain and clinical fluconazole-resistant Candida krusei strain. The studied compounds 10, 11 present the interesting scaffold for further investigation as potential inhibitors of the Candida spp. glutathione reductase with the promising antifungal properties. The developed models are publicly available online at http://ochem.eu/article/120720 and could be used by scientists for design of new more effective drugs.<br /> (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1476-928X
Volume :
90
Database :
MEDLINE
Journal :
Computational biology and chemistry
Publication Type :
Academic Journal
Accession number :
33191110
Full Text :
https://doi.org/10.1016/j.compbiolchem.2020.107407