4.7 Article

In-silico identification of potential inhibitors against FabI protein in Klebsiella pneumoniae

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TAYLOR & FRANCIS INC
DOI: 10.1080/07391102.2023.2200571

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Antimicrobial resistance; FabI; Klebsiella pneumoniae; novel drug discovery; bioinformatics

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The development of new antimicrobial drugs is necessary to combat the global increase of multi-drug resistant and novel hypervirulent strains of Klebsiella pneumoniae (KPN) associated with higher morbidity and mortality. This study used computer integrated-drug discovery methods and binding-free energy calculations to identify three novel inhibitors (21272541, 67724550, and 67724551) of the FabI protein, which plays a crucial role in fatty acid biosynthesis. All three inhibitors showed strong affinity, with 21272541 being the most effective inhibitor. These inhibitors hold promise for the development of new antimicrobial drugs against antimicrobial resistant KPN infections, pending further in-vitro and in-vivo clinical studies to confirm their efficacy.
The development of new antimicrobial drugs is needed to combat multi-drug resistant and novel hypervirulent strains of Klebsiella pneumoniae (KPN) that are associated with increased morbidity and mortality globally. The FabI protein plays a crucial role in fatty acid biosynthesis and has been identified as an important target for in-silico, in-vitro, and in-vivo drug discovery. In this study we have used computer integrated-drug discovery approaches and binding-free energy calculations to identify three novel inhibitors (21272541, 67724550, and 67724551) of the FabI protein. All inhibitors showed strong affinity including van der Waals energy, electrostatic energy, polar and non-polar energies; however, the 21272541 compound was the most effective inhibitor and bound with the strongest affinity (Delta G(bind) -59.02 kcal/mol) to the FabI protein. Nevertheless, all three inhibitors are promising targets for new novel antimicrobial drugs that could contribute to the management of antimicrobial resistant KPN infections based on various computational analysis. Additional in-vitro and in-vivo clinical studies will be needed to confirm drug effectiveness for the treatment of KPN infections.

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