In silico prediction of ATTAF-1 and ATTAF-2 selectivity towards human/fungal lanosterol 14α-demethylase using molecular dynamic simulation and docking approaches

Abstract

The emergence of resistance to azole drugs, presented significant problems for medicine that could be overcome by advances in antifungal design. We convinced that the crystal structures of fungal and host lanosterol-14α-demethylases in complex with a range of ligands, provide opportunity for the discovery and development of broad-spectrum antifungals.To enable the non-clinical evaluation of compounds in a reliable manner, major efforts are ongoing to design in vitro and in silico tools that are predictive for the compounds behavior. In silico screening of antifungal drugs to find novel and selective agents with minimal effect on human CYP51 enzyme has been a major challenge in antifungal drug discovery. In this study, MD simulation and docking calculations for lanosterol-14α-demethylase activities with totally 12 tautomers and enantiomers of ATTAF-1 and ATTAF-2 and 8 standard triazole drugs were performed. To determine the fungal lanosterol-14α-demethylase inhibition selectivity of these antifungal compounds versus human one, PDB codes of pathogenic Candida glabrata (PDB Code: 5JLC) and Candida albicans (PDB Code: 5V5Z) and human (PDB Code: 3LD6) CYP51 enzymes were used for docking and MD calculations. Results of in silico investigations on the extent of fungal CYP51 inhibition versus human one obviously showed that ATTAF-1 and ATTAF-2 have less potential to inhibit human CYP51 than the fungal CYP51 enzyme and possibly will have fewer side effects for human utilizations. These results of computational optimization could greatly contribute toward designing potential and new 14α-sterol demethylase inhibitors with better activities and less human toxicity.

Keywords

• MD simulation
• Molecular docking
• Lanosterol-14α-demethylase
• Human toxicity
• Antifungal
• Selectivity