Molecular Docking Based Virtual Design of Polysubstituted Triazoles as Cytochrome P-450 14-Alpha-Sterol Demethylase (Cyp51) Inhibitor

Computational ligand docking methodology, AutoDock 4.0, based on Lamarckian genetic algorithm was employed for virtual screening of a compound library with 13 entries including reference compound as fluconazole with the enzyme Cytochrome P-450-14-Alpha-Sterol Demethylase (Cyp51), a potential antifungal drug target. Considering free energy of binding as a criteria of evaluation, a total of 12 compounds were predicted to be potential inhibitors of Cytochrome P-450-14-Alpha-Sterol Demethylase (Cyp51) and 10 compounds displayed greater binding affinities than fluconazole as Cytochrome P-450-14-Alpha-Sterol Demethylase (Cyp51) Inhibitor. Compound 1a & 1b were the most potent in inhibiting the Cytochrome P-450-14-Alpha-Sterol Demethylase (Cyp51), in silico. Putative interactions between Cytochrome P-450-14-Alpha-Sterol Demethylase (Cyp51) and inhibitors were identified by inspection of docking-predicted poses. This understanding of protein–ligand interaction and value of binding energy imparts impetus to the rapid development of novel Cytochrome P-450-14-Alpha-Sterol Demethylase (Cyp51).