利用分子动力学、物理化学和结构分析来探索OMP33-36蛋白作为鲍曼不动杆菌的药物靶点:一种对抗医院感染的方法。

IF 2.7 4区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Sukriti Singh , Jyotsna Agarwal , Anupam Das , Mala Trivedi , Kshatresh D. Dubey , K.V. Athish Pranav , Manish Dwivedi
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引用次数: 0

摘要

鲍曼不动杆菌是导致许多严重耐多药(MDR)疾病的ESKAPE细菌中的一员。这种细菌迅速适应导致出现耐多药变种的环境因素,特别是在医院/医疗环境中。在这项工作中,我们利用计算机药物筛选方法证明了外膜蛋白33-36 (Omp33-36)孔蛋白是鲍曼不动杆菌的潜在治疗靶点,以及植物化合物的调节潜力。从蛋白质数据库中检索到Omp33-36蛋白受体,表征为受体蛋白。从三种植物穿心莲(Andrographis paniculata, Cascabela thevetia, Prosopis cineraria)中分离出可能的化合物(配体),在已有研究的基础上对其抗细菌感染的潜力进行了评价,并进行了进一步的分析。首先,从IMPPAT数据库中鉴定和检索了70种潜在的植物化合物,然后分别使用swissADME和ProTox服务器进行了理化表征和毒性评估。15种化合物显示出显著的药物可能性,并使用Autodock Vina对它们与Omp33-36的相互作用进行分析。对接研究得到7个结合亲和力最佳的化合物,范围在-7.2 kcal/mol ~ -7.9 kcal/mol之间,并根据这些化合物的潜力,引入4个植物化合物进行200ns的分子动力学模拟。在MD模拟中,化合物Prosogerin、Quercitin和Tamarixetin对Omp33-36蛋白具有很强的亲和力,结合能在-18到-33 kcal/mol之间。总的来说,该分析描述了槲皮素和他玛西汀这两种化合物具有最一致的相互作用,并显示出作为调节鲍曼不动杆菌感染的药物的前景。然而,需要体外和体内实验验证,以提出所选择的植物分子作为治疗鲍曼不动杆菌的先导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Leveraging molecular dynamics, physicochemical, and structural analysis to explore OMP33-36 protein as a drug target in Acinetobacter baumannii: An approach against nosocomial infection

Leveraging molecular dynamics, physicochemical, and structural analysis to explore OMP33-36 protein as a drug target in Acinetobacter baumannii: An approach against nosocomial infection
The Acinetobacter baumannii is a member of the "ESKAPE" bacteria responsible for many serious multidrug-resistant (MDR) illnesses. This bacteria swiftly adapts to environmental cues leading to the emergence of multidrug-resistant variants, particularly in hospital/medical settings. In this work, we have demonstrated the outer membrane protein 33-36 (Omp33-36) porin as a potential therapeutic target in A. baumannii and the regulatory potential of phytocompounds using an in-silico drug screening approach. Omp33-36 protein receptor was retrieved from the protein data bank and characterized as a receptor protein. The possible compounds (ligands) from three plants namely Andrographis paniculata, Cascabela thevetia, and Prosopis cineraria, were evaluated for their potential against bacterial infections based on prior investigations and selected for further analysis. Initially, seventy potential phytocompounds were identified and retrieved from IMPPAT database, followed by Physio-chemical characterizations and toxicity assessment using swissADME and ProTox server respectively. 15 compounds have shown significant drug-likeliness and were implemented for their interaction analysis with Omp33-36 using Autodock Vina. The docking study presented seven compounds with the best binding affinities, ranging from −7.2 kcal/mol to −7.9 kcal/mol and further, based on the potential of these compounds, 4 phytocompounds were introduced for molecular dynamic simulation for 200ns. During MD simulation, compounds Prosogerin, Quercitin and Tamarixetin have shown a substantial affinity for the Omp33-36 protein and binding energy ranging from −18 to −33 kcal/mol. Overall, the analysis depicted the two compounds, Quercitin and Tamarixetin, with the most consistent interactions and indicated promise as drug leads in regulating A. baumannii infection. However, in-vitro and in-vivo experimental validation are required to propose the selected phytomolecules as a therapeutic lead against A. baumannii.
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来源期刊
Journal of molecular graphics & modelling
Journal of molecular graphics & modelling 生物-计算机:跨学科应用
CiteScore
5.50
自引率
6.90%
发文量
216
审稿时长
35 days
期刊介绍: The Journal of Molecular Graphics and Modelling is devoted to the publication of papers on the uses of computers in theoretical investigations of molecular structure, function, interaction, and design. The scope of the journal includes all aspects of molecular modeling and computational chemistry, including, for instance, the study of molecular shape and properties, molecular simulations, protein and polymer engineering, drug design, materials design, structure-activity and structure-property relationships, database mining, and compound library design. As a primary research journal, JMGM seeks to bring new knowledge to the attention of our readers. As such, submissions to the journal need to not only report results, but must draw conclusions and explore implications of the work presented. Authors are strongly encouraged to bear this in mind when preparing manuscripts. Routine applications of standard modelling approaches, providing only very limited new scientific insight, will not meet our criteria for publication. Reproducibility of reported calculations is an important issue. Wherever possible, we urge authors to enhance their papers with Supplementary Data, for example, in QSAR studies machine-readable versions of molecular datasets or in the development of new force-field parameters versions of the topology and force field parameter files. Routine applications of existing methods that do not lead to genuinely new insight will not be considered.
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