Computational screening of potential inhibitors targeting MurF of Brugia malayi Wolbachia through multi-scale molecular docking, molecular dynamics and MM-GBSA analysis

Abstract

Lymphatic filariasis is a parasitic disease caused by the worms Wuchereria bancrofti, Brugia malayi and Brugia timori. Three anti-filarial drugs namely Diethylcarbamazine, Ivermectin and Albendazole and their combinations are used as the control strategies for filariasis. The disease has received much attention in drug discovery due to the unavailability of vaccines and the toxic pharmaceutical properties of the existing drugs. In Wolbachia endosymbiont Brugia malayi, the UDP-N-acetylmuramoyl-tripeptide-d-alanyl-d-alanine ligase (MurF) plays a key role in peptidoglycan biosynthesis pathway and therefore can be considered as effective drug target against filariasis disease. Therefore, in the present study, MurF was selected as the therapeutic target to identify specific inhibitors against filariasis. Homology modeling was performed to predict the three-dimensional structure of MurF due to the absence of the experimental structure. Further molecular dynamics simulation and structure-based high throughput virtual screening with three different chemical databases (Zinc, Maybridge and Specs) were carried out to identify potent inhibitors and also to check their conformations inside the binding site of MurF, respectively. Top three compounds with high docking score and high relative binding affinity against MurF were selected. Further, validation studies, including predicted ADME (Absorption, Distribution, Metabolism, Excretion) assessment, binding free energy using MM-GBSA (Molecular Mechanics Generalized Born Surface Area) and DFT (Density Functional Theory) calculations were performed for the top three compounds. From the results, it was observed that all the three compounds were predicted to show high reactivity, acceptable range of pharmacokinetic properties and high binding affinity with the drug target MurF. Overall, the results could provide more understanding on the inhibition of MurF enzyme and the screened compounds could lead to the development of new specific anti-filarial drugs.

Keywords: ADME prediction; Brugia malayi; Lymphatic filariasis; Molecular dynamics; MurF; Structure based virtual screening.