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肺炎克雷伯菌谷氨酸消旋酶新型治疗候选物的鉴定与优先级排序。

Identification and prioritization of novel therapeutic candidates against glutamate racemase from Klebsiella pneumoniae.

作者信息

Kumar Ankit, Anjum Farah, Hassan Md Imtaiyaz, Shamsi Anas, Singh Rashmi Prabha

机构信息

Department of Biotechnology, Sharda School of Engineering and Technology, Sharda University, Greater Noida, Uttar Pradesh, India.

Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia.

出版信息

PLoS One. 2025 Feb 6;20(2):e0317622. doi: 10.1371/journal.pone.0317622. eCollection 2025.

DOI:10.1371/journal.pone.0317622
PMID:39913383
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11801594/
Abstract

BACKGROUND

Klebsiella pneumoniae, a gram-negative bacterium in the Enterobacteriaceae family, is non-motile, encapsulated, and a major cause of nosocomial infections, particularly in intensive care units. The bacterium possesses a thick polysaccharide capsule and fimbriae, which contribute to its virulence, resistance to phagocytosis, and attachment to host cells. The bacterium has developed serious resistance to most antibiotics currently in use.

OBJECTIVE

This study aims to investigate the structural properties of MurI (glutamate racemase) from Klebsiella pneumoniae and to identify potential candidate inhibitors against the protein, which will help in the development of new strategies to combat the infections related to MDR strains of Klebsiella pneumoniae.

METHODS

The 3D structure of the protein was modelled using SWISS-MODEL, which utilizes the homology modelling technique. After refinement, the structure was subjected to virtual high throughput screening on the TACC server using Enamine AC collection. The obtained molecules were then put through various screening parameters to obtain promising lead candidates, and the selected molecules were then subjected to MD simulations. The data obtained from MD simulations was then assessed with the help of different global dynamics analyses. The protein-ligand complexes were also subjected to MM/PBSA-based binding free energy calculation using the g_mmpbsa program.

RESULTS

The screening parameters employed on the molecules obtained via virtual screening from the TACC server revealed that Z1542321346 and Z2356864560 out of four molecules have better potential to act as potential inhibitors for MurI protein. The binding free energy values, which came out to be -27.26±3.06 kcal/mol and -29.53±4.29 kcal/mol for Z1542321346 and Z2356864560 molecules, respectively, favoured these molecules in terms of inhibition potential towards targeted protein.

CONCLUSION

The investigation of MurI via computational approach and the subsequent analysis of potential inhibitors can pave the way for developing new therapeutic strategies to combat the infections and antibiotic resistance of Klebsiella pneumoniae. This study could significantly help the medical fraternity in the treatment of infections caused by this multidrug-resistant pathogen.

摘要

背景

肺炎克雷伯菌是肠杆菌科中的一种革兰氏阴性菌,无运动性,有荚膜,是医院感染的主要原因,尤其是在重症监护病房。该细菌具有厚厚的多糖荚膜和菌毛,这有助于其毒力、抗吞噬作用以及与宿主细胞的附着。该细菌已对目前使用的大多数抗生素产生了严重耐药性。

目的

本研究旨在研究肺炎克雷伯菌中MurI(谷氨酸消旋酶)的结构特性,并确定针对该蛋白的潜在候选抑制剂,这将有助于制定新策略来对抗与肺炎克雷伯菌多重耐药菌株相关的感染。

方法

使用采用同源建模技术的SWISS-MODEL对该蛋白的三维结构进行建模。优化后,利用Enamine AC化合物库在TACC服务器上对该结构进行虚拟高通量筛选。然后将获得的分子进行各种筛选参数评估以获得有前景的先导候选物,随后对所选分子进行分子动力学模拟。然后借助不同的全局动力学分析评估从分子动力学模拟获得的数据。还使用g_mmpbsa程序对蛋白质-配体复合物进行基于MM/PBSA的结合自由能计算。

结果

对通过TACC服务器虚拟筛选获得的分子所采用的筛选参数显示,四个分子中的Z1542321346和Z2356864560作为MurI蛋白潜在抑制剂的潜力更大。Z1542321346和Z2356864560分子的结合自由能值分别为-27.26±3.06千卡/摩尔和-29.53±4.29千卡/摩尔,就对靶向蛋白的抑制潜力而言,这些值有利于这些分子。

结论

通过计算方法对MurI进行研究以及随后对潜在抑制剂进行分析,可为开发对抗肺炎克雷伯菌感染和抗生素耐药性的新治疗策略铺平道路。本研究可显著帮助医学界治疗由这种多重耐药病原体引起的感染。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/9f1a4990d756/pone.0317622.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/2eca865cf251/pone.0317622.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/f7135e4db9bf/pone.0317622.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/c0512a20370b/pone.0317622.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/098c51225136/pone.0317622.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/9b7b3cbc20ae/pone.0317622.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/54a498a93e9a/pone.0317622.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/f6fe0dbfb6ca/pone.0317622.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/9066f0c8b496/pone.0317622.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/1731dd966fc6/pone.0317622.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/9f1a4990d756/pone.0317622.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/2eca865cf251/pone.0317622.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/098c51225136/pone.0317622.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/9b7b3cbc20ae/pone.0317622.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/54a498a93e9a/pone.0317622.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/f6fe0dbfb6ca/pone.0317622.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/9066f0c8b496/pone.0317622.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/1731dd966fc6/pone.0317622.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c49/11801594/9f1a4990d756/pone.0317622.g010.jpg

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