文章摘要
崔丹1 闫玉清1△ 李琬2 陈丽娜2△ 李为国2 太京燮2 张良才2 宿滨2 李心玲1.致心律失常性右心室心肌病致病蛋白的挖掘[J].,2012,12(18):3425-3429
致心律失常性右心室心肌病致病蛋白的挖掘
Mining Arrhythmogenic Right Ventricular Cardiomyopathy PotentialDisease Protein
  
DOI:
中文关键词: 致心律失常性右心室心肌病  蛋白质互作网络  致病蛋白
英文关键词: Arrhythmogenic Right Ventricular Cardiomyopathy  Protein-protein interaction network  Disease protein
基金项目:黑龙江省教育厅基金(12511271);黑龙江省自然科学基金(D200834)
作者单位
崔丹1 闫玉清1△ 李琬2 陈丽娜2△ 李为国2 太京燮2 张良才2 宿滨2 李心玲1 哈尔滨师范大学生命科学与技术学院 
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中文摘要:
      目的:鉴定疾病蛋白对深入理解致心律失常性右心室心肌病(ARVC)致病机制至关重要。可以采用计算生物学的方法,在 ARVC 疾病相关网络中挖掘新的潜在的致病蛋白。方法:本文整合HPRD 和BioGRID 的蛋白质互作数据,获得了较为全面且真 实可靠的蛋白质互作数据;通过结合文本挖掘和统计学检验筛选出ARVC 种子蛋白,应用最近邻居扩增的方法,构建ARVC 蛋 白质互作网络(PPIN),并采用PRINCESS 法则对网络中每对互作蛋白加权;最后,基于ARVC 关联得分策略对网络中的每个蛋白 质打分并排秩。结果:分析发现排秩前50 的候选蛋白大都与ARVC 关系密切,如PRKCA,CDH1,SMAD4,SMAD2,CDH5, CTNNA1,DSC1 等在调节心肌收缩、细胞程序性死亡、心脏的发育过程及维持桥粒的完整性方面起重要作用。结论:我们提出的 方法为鉴定与ARVC 致病机制相关的新致病蛋白提供了有效的途径。
英文摘要:
      Objective: Identification of disease proteins is important to understand the mechanism of Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC). Computational biological methods can be used to mine potential disease proteins in disease-related network. Methods: We integrated protein-protein interaction data from HPRD and BioGRID databases to obtain a more comprehensive and trustworthy protein-protein interaction data. The method of text mining combined with statistical tests was used to screen ARVC candidate proteins. ARVC-Protein-Protein Interaction Network (PPIN) was built through the nearest-neighbor expansion method and weighted each protein pair in the network using PRINCESS. Then an ARVC-related score strategy was presented to rank each protein of the network. Results: Top 50 candidate proteins were analyzed, and most candidate proteins were closely associated with ARVC, such as PRKCA, CDH1, SMAD4, SMAD2, CDH5, CTNNA1, DSC1. They played an important role in regulating myocardial contractility, cell degeneration, heart development and maintaining the integrity of desmosomes. Conclusions: Our approach reported here provides new insights for the identification of disease genes, and will be helpful for the studies on the pathogenesis of ARVC in depth.
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