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Prediction of the anti-inflammatory mechanisms of curcumin by module-based protein interaction network analysis

机译:基于模块的蛋白质相互作用网络分析预测姜黄素的抗炎机制

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摘要

Curcumin, the medically active component from Curcuma longa (Turmeric), is widely used to treat inflammatory diseases. Protein interaction network (PIN) analysis was used to predict its mechanisms of molecular action. Targets of curcumin were obtained based on ChEMBL and STITCH databases. Protein–protein interactions (PPIs) were extracted from the String database. The PIN of curcumin was constructed by Cytoscape and the function modules identified by gene ontology (GO) enrichment analysis based on molecular complex detection (MCODE). A PIN of curcumin with 482 nodes and 1688 interactions was constructed, which has scale-free, small world and modular properties. Based on analysis of these function modules, the mechanism of curcumin is proposed. Two modules were found to be intimately associated with inflammation. With function modules analysis, the anti-inflammatory effects of curcumin were related to SMAD, ERG and mediation by the TLR family. TLR9 may be a potential target of curcumin to treat inflammation.
机译:姜黄素是姜黄(姜黄)的医学活性成分,被广泛用于治疗炎症。蛋白质相互作用网络(PIN)分析被用来预测其分子作用机理。基于ChEMBL和STITCH数据库获得姜黄素的靶标。蛋白质-蛋白质相互作用(PPI)从String数据库中提取。姜黄素的密码由Cytoscape构建,其功能模块通过基于分子复合物检测(MCODE)的基因本体(GO)富集分析来识别。构造了具有482个节点和1688个交互作用的姜黄素PIN,它具有无标度,小世界和模块化特性。在分析这些功能模块的基础上,提出姜黄素的作用机理。发现有两个模块与炎症密切相关。通过功能模块分析,姜黄素的抗炎作用与SMAD,ERG和TLR家族的介导有关。 TLR9可能是姜黄素治疗炎症的潜在靶标。

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