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利用网络生物学方法对大肠杆菌 K12 毒素-抗毒素系统进行功能分析,作为新型药物靶点。

Functional analysis of Escherichia coli K12 toxin-antitoxin systems as novel drug targets using a network biology approach.

机构信息

Department of Microbiology, KS Hegde Medical Academy (KSHEMA), Nitte (Deemed to be University), Deralakatte, Mangalore, 575018, India; Central Research Laboratory, K.S. Hegde Medical Academy, Nitte (Deemed to be University), Deralakatte, Mangalore, 575018, India.

Division of Microbiology and Biotechnology, Yenepoya Research Centre, Yenepoya (Deemed to be University), University Road, Deralakatte, Mangalore, 575018, India.

出版信息

Microb Pathog. 2022 Aug;169:105683. doi: 10.1016/j.micpath.2022.105683. Epub 2022 Jul 16.

Abstract

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.

摘要

细菌对各种药物和抗生素的耐药性已成为对抗传染病的重大问题。由于存在多种毒素-抗毒素(TA)系统,细菌会发生适应性代谢改变,并能够耐受药物和抗生素的作用。细菌 TA 系统具有独特性,并且由于其能够影响细菌的命运,因此可以成为开发新型抗菌药物的治疗靶标。基于此背景,我们旨在通过同源建模方法来确定针对大肠杆菌 K12 MG1655 抗毒素的新型药物靶标。在本研究中,通过文献挖掘,筛选出 87 个大肠杆菌 K12 MG1655 TA 系统的蛋白-蛋白相互作用网络,以鉴定枢纽蛋白。评估、评估和同源建模枢纽蛋白的模型评价。此外,还针对鉴定出的枢纽蛋白测试了选定植物化学物质的计算机辅助数学模型。TA 系统在细胞生长的调节、细胞生长的负调节、mRNA 稳定性的调节、mRNA 分解代谢过程和 RNA 磷酸二酯键水解等方面具有功能富集性。RelE、RelB、MazE、MazF、MqsR、MqsA 和 YoeB 被鉴定为枢纽蛋白。通过对枢纽蛋白的模型评估、质量评估标准和同源建模,发现 RelB 和 MazE 模型结构具有稳健性和高质量。通过对接这些模型结构,发现氯雷比辛是一种强有力的抑制剂。氯雷比辛可作为一种抗多药耐药大肠杆菌的抗菌剂,其可能使抗毒素失活并导致程序性细胞死亡。

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