Discovering approximate-associated sequence patterns for protein-DNA interactions
Discovering approximate-associated sequence patterns for protein-DNA interactions
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DOI：
10.1093/bioinformatics/btq682
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发表时间：
2011-02-15
期刊：
影响因子：
5.8
通讯作者：
Leung, Kwong-Sak
中科院分区：
文献类型：
--
作者：
Chan, Tak-Ming;Wong, Ka-Chun;Leung, Kwong-Sak
动机：转录因子（tf）与转录因子结合位点（TFBSs）之间的结合是转录调控中基本的蛋白质- dna相互作用。为了更好地理解蛋白质- dna的相互作用，人们做了大量的努力。近年来，对tf - tfbs相关的精确序列模式（规则）的挖掘显示出了巨大的潜力，并取得了非常有希望的结果。然而，精确的规则无法处理实际数据中的变化，从而导致信息规则的有限性。在本文中，我们对TFs和TFBSs的精确规则进行了概括，以近似于生物变异所必需的TFs和TFBSs的规则。结果：提出了一种渐进的方法来解决近似问题，以减轻计算需求。首先，从现有的TF-TFBS数据（TRANSFAC数据库）中对相似的tfbs进行分组。其次，从每个TFBS群对应的TF序列中发现近似且高度保守的结合核；针对具体目标开发了定制算法。我们通过将分组的TFBS共识和TF核心联系起来，发现了近似的TF-TFBS规则。通过匹配（验证）来自蛋白质数据库（PDB）三维结构的实际蛋白质- dna结合对来评估发现的规则。近似结果比精确结果显示出更多的验证规则和高达300%的验证率。与传统方法相比，定制算法的验证率提高了73%以上。近似规则（64-79%）具有统计学意义。NCBI记录的详细变异分析和保守性验证表明，该近似规则准确地揭示了蛋白质- dna相互作用的灵活性和特异性。所发现的近似TF-TFBS规则显示出探索更多信息绑定规则的良好泛化能力。
Motivation: The bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) are fundamental protein-DNA interactions in transcriptional regulation. Extensive efforts have been made to better understand the protein-DNA interactions. Recent mining on exact TF-TFBS-associated sequence patterns (rules) has shown great potentials and achieved very promising results. However, exact rules cannot handle variations in real data, resulting in limited informative rules. In this article, we generalize the exact rules to approximate ones for both TFs and TFBSs, which are essential for biological variations.Results: A progressive approach is proposed to address the approximation to alleviate the computational requirements. Firstly, similar TFBSs are grouped from the available TF-TFBS data (TRANSFAC database). Secondly, approximate and highly conserved binding cores are discovered from TF sequences corresponding to each TFBS group. A customized algorithm is developed for the specific objective. We discover the approximate TF-TFBS rules by associating the grouped TFBS consensuses and TF cores. The rules discovered are evaluated by matching (verifying with) the actual protein-DNA binding pairs from Protein Data Bank (PDB) 3D structures. The approximate results exhibit many more verified rules and up to 300% better verification ratios than the exact ones. The customized algorithm achieves over 73% better verification ratios than traditional methods. Approximate rules (64-79%) are shown statistically significant. Detailed variation analysis and conservation verification on NCBI records demonstrate that the approximate rules reveal both the flexible and specific protein-DNA interactions accurately. The approximate TF-TFBS rules discovered show great generalized capability of exploring more informative binding rules.