Development of pharmacophore alignment models as input for comparative molecular field analysis of a diverse set of azole antifungal agents

Citation
Tt. Talele et al., Development of pharmacophore alignment models as input for comparative molecular field analysis of a diverse set of azole antifungal agents, J CHEM INF, 39(6), 1999, pp. 958-966
Citations number
34
Categorie Soggetti
Chemistry
Journal title
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
ISSN journal
00952338 → ACNP
Volume
39
Issue
6
Year of publication
1999
Pages
958 - 966
Database
ISI
SICI code
0095-2338(199911/12)39:6<958:DOPAMA>2.0.ZU;2-O
Abstract
Molecular modeling studies were performed on a diverse set of 24 cytochrome P-450(14 alpha DM) inhibiting: azole antifungals that demonstrate differen t degrees of biological activity. The studied compounds, which have been re ported to be active in vitro against Candida albicans, were divided into a training set of 20 compounds and a test set of 4 compounds. In an effort to develop a ligand-binding model for the cytochrome P-450(14 alpha DM) recep tor, a pharmacophore mapping program (Apex-3D) was used to search structura l features that an common to ligands that exhibit moderate to high antifung al activity. Apex-3D then was utilized to propose a common biophoric region that included one low-energy conformation of each compound in the training set. These aligned structures suggested a three-point pharmacophore map (t wo atom-centered descriptors and one aromatic ring centroid) for the azole antifungals. The resulting alignment was used in a comparative molecular fi eld analysis (CoMFA) study in an attempt to correlate the steric and electr ostatic fields of the compounds with the respective biological activity. Th e predictive ability of each resultant CoMFA model was evaluated using a te st set consisting of four compounds. The best 3D quantitative structure-act ivity relationship model yielded cross-validated, conventional, and predict ive r(2) values equal to 0.536, 0.998, and 0.778, respectively. A predictiv e model was obtained from the CoMFA analysis, which shall be useful for the development of new azole analogues as potential antifungals.