The potential of plant-derived secondary metabolites as novel drug candidates against Klebsiella pneumoniae: Molecular docking and simulation investigation

Klebsiella pneumoniae is an important multidrug-resistant pathogen affecting humans and a major source for hospital infections associated with high morbidity and mortality due to limited treatment options. The pathogenesis of this microbe is caused by several key proteins; one of them is type 3 fimbrial proteins, which has been known for its crucial role in the host cell invasion. Therefore, targeting fimbriae protein can be a solution for treating this pathogenic disease. Plant Secondary metabolites with diverse chemical scaffolds have been recognized as an invaluable source of compounds in drug discovery and development. However, systematic identification of drug targets for plant secondary metabolites at the human proteome level via various experimental assays is highly expensive and time-consuming. In this study, we have employed plant derived secondary metabolites to predict new drug targets of type 3 fimbrial protein of K. pneumoniae. Subsequently, structure-based virtual screening was performed to identify compounds showing the best binding confirmation with the target enzyme and forming a stable complex. Molecular dynamics simulations of the protein-ligand complex indicated that the intermolecular hydrogen bonds formed between the protein and ligand complex remain stable during the simulation time. The interaction shown by the compounds provides an important insight into the mechanism involved in the ligand-receptor interaction. The model will aid in the development of a drug with improved efficacy and reduced side effects. Thus, vernolide could serve as a drug for treating pneumonia infections in humans. The drug likeliness prediction on this derivative also supports its suitability as a drug candidate. However, an in vitro and in vivo analysis of the selected compound is necessary for further validation before administration of the drug to human beings.