Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12779/4161
Title: Molecular modeling of azole antifungal agents active against Candida albicans .1. A comparative molecular field analysis study
Authors: Tafi, Andrea 
Anastassopoulou, J
Theophanides, T
Botta, Maurizio 
Corelli, Federico 
Massa, S
Artico, M
Costi, R
Disanto, R
Ragno, R.
Issue Date: 1996
Project: None 
Journal: JOURNAL OF MEDICINAL CHEMISTRY
Abstract: 
A series of 56 azole antifungal agents belonging to chemically diverse families related to bifonazole, one of the antimycotic drugs of clinical use, were investigated using the comparative molecular field analysis (CoMFA) paradigm. The studied compounds, which have been already synthesized and reported to be active in vitro against Candida albicans, were divided into a training set and a test set. The training set consisted of 40 molecules from all the different structural classes. Due to the lack of experimental structural data on these derivatives, molecular mechanics techniques were used to obtain putative active conformations for all the compounds. The correctness of this molecular modeling work was confirmed a posteriori by comparison with structural data of the analog 2w obtained by X-ray crystallographic analysis (Massa, S.; et al. fur. J. Med. Chem. 1992, 27, 495-502). Two different alignment rules of the training set molecules were used in this study and are based on the assumption that according to published results on azole antifungal agents, all the studied compounds exert their inhibitory activity through the coordination of their azole moiety to the protoporphyrin iron atom of the fungal lanosterol 14 alpha-demethylase enzyme. The predictive ability of each resultant CoMFA model was evaluated using a test set consisting of 16 representative compounds that belong to all the different structural classes. The best 3D-quantitative structure-activity relationship model found yields significant cross-validated, conventional, and predictive r(2) values equal to 0.57, 0.95, and 0.69, respectively. The average absolute error of predictions of this model is 0.30 log units, and the structural moieties of the studied antifungal agents which are thought to contribute to the biological activity were identified. The predictive capability of this model could be exploited in further synthetic studies on antifungal azoles. Furthermore, the results obtained by using two different alignments of the inhibitors suggest that the binding mode of these molecules involves both a coordination to the iron protoporphyrin atom and an additional, likewise relevant, hydrophobic interaction with the active site.
Description: 
49251
URI: http://hdl.handle.net/20.500.12779/4161
ISSN: 0022-2623
DOI: 10.1021/jm950385+
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