Computational approach towards repurposing of FDA approved drug molecules: strategy to combat antibiotic resistance conferred by Pseudomonas aeruginosa.
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引用次数: 0
Abstract
Antimicrobial resistance is recognized as a major worldwide public health dilemma in the current century. Pseudomonas aeruginosa, a Gram-negative opportunistic pathogen, causes nosocomial infections like respiratory tract infections, urinary tract infections, dermatitis, and cystic fibrosis. It manifests antibiotic resistance via intrinsic, acquired, and adaptive pathways, where efflux pumps function in the extrusion of antibiotics from the cell. MexB protein, part of the tripartite efflux pumps MexAB-OprM present in P.aeruginosa, expels the penems and β-lactam antibiotics, thereby enhancing Pseudomonas resistance. The current study was intended to screen around 1602 clinically approved drugs to understand their ability to inhibit the MexB protein. Amongst them, the top 5 drug molecules were selected based on the binding energies for analyzing their physio-chemical and toxicity properties. Lomitapide was found to have the maximum negative binding energy followed by Nilotinib, whereas Nilotinib's number of hydrogen bonds was higher than that of Lomitapide. ADMET study revealed that all 5 drug molecules had limited solubility. Also, Lomitapide and Venetoclax showed low bioavailability scores, while Nilotinib, Eltrombopag, and Conivaptan demonstrated higher potential for therapeutic levels. A molecular dynamic simulation study of the 5 drugs against MexB was carried out for 200 nanoseconds. The RMSD, RMSF, Hydrogen bond formation, Radius of gyration, SASA, PCA, DCCM, DSSP and MM-PBSA binding energy calculation along with demonstrated high stability of the MexB-Nilotinib complex with lesser distortions. Our study concludes, that Nilotinib is a potential inhibitor and can be developed as a therapeutic agent against MexB protein for controlling P. aeruginosa infections.
期刊介绍:
The Journal of Biomolecular Structure and Dynamics welcomes manuscripts on biological structure, dynamics, interactions and expression. The Journal is one of the leading publications in high end computational science, atomic structural biology, bioinformatics, virtual drug design, genomics and biological networks.