3D-QSAR Studies of Imidazole Derivatives as Candida albicans P450 - Demethylase Inhibitors

Abstract

In present search for better antifungal agents with high degree of specificity towards fungal enzymes, 3D-QSAR studies of some antifungal imidazoles was performed by comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. The compounds were divided into a training set of 34 molecules and a test set of 15 molecules. The global minimum energy conformer of the template molecule miconazole, 1 was obtained by simulated annealing method and used to build the structures of the molecules in the dataset. Tripos's Sybyl 7.1 program was used to develop the 3D CoMFA and CoMSIA models. The CoMFA model produced statistically significant results with crossvalidated and conventional correlation coefficients of 0.697 and 0.925, respectively. The combination of steric, electrostatic, hydrophobic and hydrogen acceptor fields in CoMSIA gave results with cross-validated and conventional correlation coefficients of 0.656 and 0.912, respectively. The predictive ability of CoMFA and CoMSIA were determined using a test set of 15 imidazole derivatives giving predictive correlation coefficients of 0.66 and 0.57, respectively indicating good predictive power of CoMFA over CoMSIA. Based upon the information derived from CoMFA and CoMSIA, newer imidazole derivatives can be designed as potent Candida P450_DM inhibitors.