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Ligand Based Pharmacophore Modeling, Virtual Screening and Molecular Docking for Identification of Novel CYP51 Inhibitors

Background: Azoles were designed to impede fungal infection by inhibiting the prominent target Lanosterol 14α-demethylase (CYP51), an essential component of fungal cell membrane, in turn interrupting the pathway of lanosterol to ergosterol. Emerging resistance ability and toxicity of presently available drugs urge for novel antifungal agents. Methods and findings: This research focus on cost effective ligand based pharmacophore modeling to present potential novel CYP51 inhibitors. Out of 10 hypotheses, the best 4 featured pharmacophore model- 3HBA and 1HY with RMS 0.85, correlation coefficient of 0.94 and cost difference of 33.33 has been chosen. The prediction of generated pharmacophore was validated using rm2 matrices, Fischer’s randomization method, internal and external test prediction. The chosen model was used as a 3D query to screen the chemical databases (NCI and Maybridge). Two hits (NSC 1028 and HTS 00684) with high fit value and zero Lipinski’s violation were docked into CYP51 receptor site to identify key amino acid residues. Conclusions: Two hits (NSC 1028 and HTS 00684) with high fit value (7.56 and 8.25) and low estimated value (0.16 and 0.03) were docked into the catalytic site of CYP51 receptor. Hydrogen bond, Van Der Waals and hydrophobic interactions governed the binding mode of the hits within the active site. The results showed high affinity of hits when compared with the standard drug (fluconazole and voriconazole) which directs future evaluation of these hits using in vivo studies.


Sarvesh Kumar P, Aarti Singh, Swapnil Sharma, Mukta Sharma and Anupama Mittal

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