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Structural characterization and modeling of ncRNA-protein interactions

机译:ncRNA-蛋白质相互作用的结构表征和建模

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摘要

Recent studies have suggested that noncoding RNA (ncRNA) molecules could play an important role in the regulatory architecture of eukaryotic cells. This new RNA-based regulation might indicate the existence of a hidden layer in the central dogma. In spite of its importance, the large-scale structure as well as the local interaction pattern of the ncRNA regulatory network has not been investigated. In this work, we collected regulatory interactions between ncRNA molecules and their regulated protein targets. We then constructed the ncRNA-protein interaction network corresponding to six model organisms, including Homo sapiens. The large-scale network analysis of ncRNA-protein interactions revealed a high degree of similarity for the degree distribution to that of the transcription regulatory network. Moreover, characterization of the local interaction structure of these networks based on motifs abundance also reveals significant similarities between ncRNA-protein and TFs-gene regulatory networks. Based on the identified motif abundance, we propose an evolutionary model that rebuilds the degree distribution and predicts the observed degree exponent. Taken together, our findings offer insights into the noncoding RNA-mediated regulation and provide knowledge about its structure and evolutionary mechanisms.
机译:最近的研究表明,非编码RNA(ncRNA)分子可能在真核细胞的调控结构中起重要作用。这种基于RNA的新规定可能表明中央教条中存在隐藏层。尽管它的重要性,但尚未研究ncRNA调控网络的大规模结构以及局部相互作用模式。在这项工作中,我们收集了ncRNA分子与其调控的蛋白质靶标之间的调控相互作用。然后,我们构建了与六个模式生物相对应的ncRNA-蛋白质相互作用网络,其中包括智人。 ncRNA-蛋白质相互作用的大规模网络分析表明,其程度分布与转录调控网络高度相似。而且,基于基元丰度的这些网络的局部相互作用结构的表征也揭示了ncRNA蛋白与TFs基因调控网络之间的显着相似性。基于确定的主题丰度,我们提出了一种演化模型,该模型可以重建度分布并预测观察到的度指数。综上所述,我们的发现为非编码RNA介导的调控提供了见识,并提供了有关其结构和进化机制的知识。

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