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金银花中木犀草素通过蛋白质网络相互作用的抑菌调控

The bacteriostatic regulation of luteolin from honeysuckle by protein network interaction.

作者信息

Zhang Jianfeng, Chen Mujun, Yang Dianzeng, Jia Yanjie

机构信息

College of Information Engineering, Henan Vocational College of Agriculture, Zhengzhou, China.

College of Artificial Intelligence, Henan Vocational College of Agriculture, Zhengzhou, Henan, China.

出版信息

Front Bioinform. 2025 Aug 1;5:1637479. doi: 10.3389/fbinf.2025.1637479. eCollection 2025.

Abstract

A comprehensive analysis of the bacteriostatic mechanism of luteolin at the molecular level was performed. Luteolin-related targets were first retrieved from the STITCH database, followed by the acquisition of protein-protein interaction (PPI) information from the STRING database. The retrieved PPI data was subsequently imported into Cytoscape software to construct a PPI network. Finally, the Molecular Complexity Detection (MCODE) algorithm and BinGo plugin were utilized to conduct module analysis and functional annotation of the constructed network, respectively. The results showed that a total of ten targets were successfully screened from the database. Based on these targets, a PPI network consisting of 91 nodes and 332 edges was constructed. Cluster analysis identified seven distinct functional modules, and subsequent module analysis further demonstrated that luteolin was primarily involved in multiple biological processes, including pathogenic bacteria resistance, antibacterial defensive responses, pathogenic fungi resistance, and resistance to both gram-negative and gram-positive bacteria. These findings indicated that luteolin exhibits robust antibacterial and antifungal activities. By investigating the inhibitory mechanism of luteolin at the molecular-network level, this study paves the way for the development of novel bacteriostatic strategies, offering a valuable perspective for related research.

摘要

对木犀草素在分子水平上的抑菌机制进行了全面分析。首先从STITCH数据库中检索与木犀草素相关的靶点,随后从STRING数据库中获取蛋白质-蛋白质相互作用(PPI)信息。将检索到的PPI数据导入Cytoscape软件以构建PPI网络。最后,分别利用分子复杂性检测(MCODE)算法和BinGo插件对构建的网络进行模块分析和功能注释。结果表明,共从数据库中成功筛选出10个靶点。基于这些靶点,构建了一个由91个节点和332条边组成的PPI网络。聚类分析确定了7个不同的功能模块,随后的模块分析进一步表明,木犀草素主要参与多种生物学过程,包括对病原菌的抗性、抗菌防御反应、对致病真菌的抗性以及对革兰氏阴性菌和革兰氏阳性菌的抗性。这些发现表明木犀草素具有强大的抗菌和抗真菌活性。通过在分子网络水平上研究木犀草素的抑制机制,本研究为新型抑菌策略的开发铺平了道路,为相关研究提供了有价值的视角。

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