Interrogating domain-domain interactions with parsimony based approaches.
Interrogating domain-domain interactions with parsimony based approaches.
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DOI：
10.1186/1471-2105-9-171
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发表时间：
2008-03-26
影响因子：
3
通讯作者：
Przytycka TM
中科院分区：
文献类型：
--
作者：
Guimarães KS;Przytycka TM
相互作用结构域对的识别和表征是了解蛋白质相互作用的重要一步。在过去的几年里，已经提出了几种方法来预测域的相互作用。了解这些方法的力量和局限性是开发改进方法和更好地理解这些相互作用的性质的关键。在之前发布的用于预测域与域交互的简约解释方法（PE）的基础上，我们引入了一种新的广义简约解释（GPE）方法，该方法（i）将域定义的粒度调整为输入数据集的粒度和（ii）允许域交互具有不同的成本。这允许优先选择所谓的“共现结构域”作为蛋白质之间相互作用的可能介质。这两个变体的简约方法的性能是竞争力的顶级算法的性能，即使简约方法使用的信息比其他一些方法。我们还研究了在介导网络中蛋白质相互作用的结构域相互作用中可能存在的共现结构域和同源结构域的富集。相应的研究进行了调查域的相互作用预测的GPE方法，以及通过使用组合计数方法独立于任何预测方法。我们的研究结果表明，虽然预测的域相互作用中对这些特殊域对有相当大的倾向，但这种过度表示显着低于iPfam数据集。广义简约解释方法为预测和研究域-域相互作用提供了一种新的手段。我们发现，在网络中的所有蛋白质相互作用是由域相互作用介导的假设下，从iPfam数据的域相互作用介导的网络中的相互作用的属性存在显着的偏差。
The identification and characterization of interacting domain pairs is an important step towards understanding protein interactions. In the last few years, several methods to predict domain interactions have been proposed. Understanding the power and the limitations of these methods is key to the development of improved approaches and better understanding of the nature of these interactions. Building on the previously published Parsimonious Explanation method (PE) to predict domain-domain interactions, we introduced a new Generalized Parsimonious Explanation (GPE) method, which (i) adjusts the granularity of the domain definition to the granularity of the input data set and (ii) permits domain interactions to have different costs. This allowed for preferential selection of the so-called "co-occurring domains" as possible mediators of interactions between proteins. The performance of both variants of the parsimony method are competitive to the performance of the top algorithms for this problem even though parsimony methods use less information than some of the other methods. We also examined possible enrichment of co-occurring domains and homo-domains among domain interactions mediating the interaction of proteins in the network. The corresponding study was performed by surveying domain interactions predicted by the GPE method as well as by using a combinatorial counting approach independent of any prediction method. Our findings indicate that, while there is a considerable propensity towards these special domain pairs among predicted domain interactions, this overrepresentation is significantly lower than in the iPfam dataset. The Generalized Parsimonious Explanation approach provides a new means to predict and study domain-domain interactions. We showed that, under the assumption that all protein interactions in the network are mediated by domain interactions, there exists a significant deviation of the properties of domain interactions mediating interactions in the network from that of iPfam data.
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