Bacterial resistance to various drugs and antibiotics has become a significant issue in the fight against infectious diseases. Due to the presence of diverse toxin-antitoxin (TA) systems, bacteria undergo adaptive metabolic alterations and can tolerate the effects of drugs and antibiotics. Bacterial TA systems are unique and can be therapeutic targets for developing new antimicrobial agents, owing to their ability to influence bacterial fate. With this background, our study aims to identify novel drug targets against Escherichia coli K12 MG1655 antitoxin using homology modelling approach. In this study, the protein-protein interaction network of 87 E. coli K12 MG1655 TA systems identified through literature mining was screened for the identification of hub proteins. The model evaluation, assessment, and homology modelling of the hub proteins were evaluated. Furthermore, computer-aided mathematical models of selected phytochemicals have been tested against the identified hub proteins. The TA system was functionally enriched in regulation of cell growth, negative regulation of cell growth, regulation of mRNA stability, mRNA catabolic process and RNA phosphodiester bond hydrolysis. RelE, RelB, MazE, MazF, MqsR, MqsA, and YoeB were identified as hub proteins. The robustness and superior quality of the RelB and MazE modelled structure were discovered by model evaluation, quality assessment criteria, and homology modelling of hub proteins. Clorobiocin was found to be a strong inhibitor by docking these modelled structures. Clorobiocin could be utilized as an antibacterial agent against multidrug resistant E. coli which may inactivate antitoxins and cause programmed cell death.
Keywords: Docking; Escherichia coli K12; Homology modelling; Protein-protein interaction; Toxin-antitoxin.
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