MOLECULAR MODELING OF AZOLE ANTIFUNGAL AGENTS ACTIVE AGAINST CANDIDA-ALBICANS .1. A COMPARATIVE MOLECULAR-FIELD ANALYSIS STUDY

Citation
A. Tafi et al., MOLECULAR MODELING OF AZOLE ANTIFUNGAL AGENTS ACTIVE AGAINST CANDIDA-ALBICANS .1. A COMPARATIVE MOLECULAR-FIELD ANALYSIS STUDY, Journal of medicinal chemistry, 39(6), 1996, pp. 1227-1235
Citations number
40
Categorie Soggetti
Chemistry Medicinal
ISSN journal
00222623
Volume
39
Issue
6
Year of publication
1996
Pages
1227 - 1235
Database
ISI
SICI code
0022-2623(1996)39:6<1227:MMOAAA>2.0.ZU;2-R
Abstract
A series of 56 azole antifungal agents belonging to chemically diverse families related to bifonazole, one of the antimycotic drugs of clini cal use, were investigated using the comparative molecular field analy sis (CoMFA) paradigm. The studied compounds, which have been already s ynthesized and reported to be active in vitro against Candida albicans , were divided into a training set and a test set. The training set co nsisted of 40 molecules from all the different structural classes. Due to the lack of experimental structural data on these derivatives, mol ecular mechanics techniques were used to obtain putative active confor mations for all the compounds. The correctness of this molecular model ing 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 alignm ent rules of the training set molecules were used in this study and ar e based on the assumption that according to published results on azole antifungal agents, all the studied compounds exert their inhibitory a ctivity through the coordination of their azole moiety to the protopor phyrin iron atom of the fungal lanosterol 14 alpha-demethylase enzyme. The predictive ability of each resultant CoMFA model was evaluated us ing a test set consisting of 16 representative compounds that belong t o all the different structural classes. The best 3D-quantitative struc ture-activity relationship model found yields significant cross-valida ted, 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 a ntifungal agents which are thought to contribute to the biological act ivity were identified. The predictive capability of this model could b e exploited in further synthetic studies on antifungal azoles. Further more, the results obtained by using two different alignments of the in hibitors suggest that the binding mode of these molecules involves bot h a coordination to the iron protoporphyrin atom and an additional, li kewise relevant, hydrophobic interaction with the active site.