结核分枝杆菌
生物信息学
肺结核
对接(动物)
虚拟筛选
分子动力学
人口
化学
计算生物学
立体化学
生物
医学
计算化学
生物化学
兽医学
病理
环境卫生
基因
作者
Mandeep Chouhan,Prashant Kumar Tiwari,Mahmoud Moustafa,Kundan Kumar Chaubey,Arti Gupta,Rajeev Kumar,Amaresh Kumar Sahoo,Esam I. Azhar,Vivek Dhar Dwivedi,Sanjay Kumar
标识
DOI:10.1080/07391102.2023.2208214
摘要
The majority of the world population (around 25%) has latent Mycobacterium tuberculosis (Mtb) infection, among which only 5–10% of individuals develop active tuberculosis (TB), and 90–95% continue to have latent tuberculosis infection. This makes it the biggest global health concern. It has been reported that the resuscitation-promoting factor B (RpfB) is an exciting potential target for tuberculosis drug discovery due to its significant role in the reactivation of latent TB infection to an active infection. Several attempts have been made to investigate potential inhibitors against RpfB utilizing in-silico approaches. The present study also utilized a computational approach to investigate microbially derived natural compounds against the Mtb RpfB protein which is a very cost-effective This evaluation used structure-based virtual screening (SBVS), drug-likeness profiling, molecular docking, molecular dynamics simulation, and free-binding energy calculations. Six potential natural compounds, viz. Cyclizidine I, Boremexin C, Xenocoumacin 2, PM-94128, Cutinostatin B, and (+)1-O-demethylvariecolorquinone A were selected, which displayed a potential binding affinity between −52.39 and −60.87 Kcal/mol MMGBSA score and docking energy between −7.307 Kcal/mol to −6.972 Kcal/mol. All the complexes showed acceptable stability (<2.7 Å RMSD) during 100 ns MD simulation time except the RpfB protein-xenocoumacin 2 complex. This result exhibited that the selected compounds have high efficiency in inhibiting the Mtb RpfB and can be taken into account for additional in vitro and in vivo experimental validation.Communicated by Ramaswamy H. Sarma
科研通智能强力驱动
Strongly Powered by AbleSci AI