Novel Insight from Computational Virtual Screening Depict the Binding Potential of Selected Phytotherapeutics Against Probable Drug Targets of Clostridium difficile

This study explores computational screening and molecular docking approaches to screen novel herbal therapeutics against probable drug targets ofClostridium difficile. The essential genes were predicted by comparative genome analysis of C. difficile and best homologous organisms using BLAST search at database of essential genes (DEG). The functions of these genes in various metabolic pathways were predicted and some of these genes were considered as potential targets. Three major proteins were selected as putative targets, namely permease IIC component, ABC transporter and histidine kinase. The three-dimensional structures of these targets were predicted by molecular modelling. The herbal bioactive compounds were screened by computer-aided virtual screening and binding potentials against the drug targets were predicted by molecular docking. Quercetin present inPsidium guajava (binding energy of −9.1 kcal/mol), Ellagic acid found inPunica granatum andPsidium guajava (binding energy −9.0 kcal/mol) and Curcumin, present inCurcuma longa (binding energy −7.8 kcal/mol) demonstrated minimum binding energy and more number of interacting residues with the drug targets. Further, comparative study revealed that phytoligands demonstrated better binding affinities to the drug targets in comparison with usual ligands. Thus, this investigation explores th e therapeutic probabilities of selected phytoligands against the putative drug targets ofC. difficile.
Source: Interdisciplinary Sciences, Computational Life Sciences - Category: Bioinformatics Source Type: research