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

被引:9
作者
Khan, Shama [1 ]
Madhi, Shabir A. [1 ,2 ,3 ]
Olwagen, Courtney [1 ,4 ]
机构
[1] Univ Witwatersrand, South African Med Res Council, Vaccines & Infect Dis Analyt Res Unit, Fac Hlth Sci,Sch Pathol, Johannesburg, South Africa
[2] Univ Witwatersrand, Natl Res Fdn, South African Res Chair Initiat Vaccine Preventabl, Fac Hlth Sci,Dept Sci & Technol, Johannesburg, South Africa
[3] Univ Witwatersrand, Wits Infect Dis & Oncol Res Inst, Fac Hlth Sci, Johannesburg, South Africa
[4] Univ Witwatersrand, Fac Hlth Sci, South African Med Res Council, Vaccines & Infect Dis Analyt Res Unit, Johannesburg, South Africa
基金
新加坡国家研究基金会;
关键词
Antimicrobial resistance; FabI; Klebsiella pneumoniae; novel drug discovery; bioinformatics; MOLECULAR-DYNAMICS; PREDICTION; PERCEPTION; RESISTANCE; SOFTWARE; DOCKING; GLIDE; MODEL;
D O I
10.1080/07391102.2023.2200571
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:1506 / 1517
页数:12
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