In Silico Identification of Antifungal Compounds as Mutant DHFRase Inhibitors: Structure-Based Approach, Molecular Dynamics Simulation and Structural Integrity Analysis

Abstract

Fungal infection of invasive nature is an alarming threat globally and a leading cause of human morbidity and mortality as they are opportunistic in nature. Rising resistance to current clinically approved marketed products for fungal infections is a major concern for humans. Dihydrofolate Reductase (DHFRase) is an essential enzyme in folate metabolic pathway responsible for DNA synthesis and is ubiquitous to all organisms, and also acts as a key target for developing antifungal drugs. In this study, potential mutant DHFRase inhibitors were screened with the help of hierarchical mode of docking of virtual library of antifungal compounds and molecular dynamic (MD) simulation. The identification of best hits was done by using the docking, binding energy prediction and further, which was supported by their predicted pharmacokinetics. MD simulation of the human DHFRase enzyme with the reference lead compound i.e. PY957 and most promising hit found i.e. ChemDiv-C390-0455 and to validate the stability of enzyme-ligand complex in best 07 retrieved hit as a potential mutant DHFRase inhibitor. The key residues Glh30, Phe34, Phe64, Phe31 of the binding pocket acknowledged as essential were found to be matching with the key interactions of the selected hit. Computed root mean square deviation (RMSD) and root mean square fluctuation (RMSF) in MD simulation of complex of DHFRase enzyme with PY957 and ChemDiv-C390-0455 were read less than 2.25[Formula: see text]Å during 100 nanoseconds simulation for both complex.