An approach of computer-aided drug design (CADD) tools for in silico assessment of various inhibitors of lanosterol-14α demethylase

Abstract

Structure-based virtual screening is a modern CADD tool in drug discovery that identifies active inhibitors based upon the prediction of binding affinity as well as molecular interactions of ligand molecules (or inhibitors) with their corresponding target proteins or enzymes. This advanced technique is used to identify potential candidates from natural origin possessing antifungal potentials through inhibition of cell wall synthesis in deleterious species Candida albicans, Saccharomyces cerevisiae, etc. 3D confirmations for the chemical structures of identified phytoconstituents were prepared through ChemDraw 16.0 program for prediction of activity (way2drug), mechanism (PyRx), physicochemical & pharmacokinetics (SWISS-ADME) and toxicological (PROTOX-2) probabilities through in-silico approaches. BIOVIA Discovery studio visualizer was used to generate a 3D and 2D image of the most active 18 molecules among 110 identified ligands. The research concludes with some most probable ligands of pteridophytic origin that interact with cell wall synthesis in normal and resistant fungal species. The results suggested that out of 18 active molecules, Mol-9, Mol-13, Mol-4 and Mol-16 showed highest docking score on lanosterol-14-alpha demethylase obtained from different sources. Hence, these molecules may possess good bioactivity against fungal growth and can be further developed as potent antifungal drug. However further research is required to explore individual molecule for their potency and efficacy and for exploring further molecular pathways against fungal infections.