Linking proteins to signaling pathways for experiment design and evaluation.
Linking proteins to signaling pathways for experiment design and evaluation.
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DOI：
10.1371/journal.pone.0036202
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Korcsmáros T
中科院分区：
文献类型：
--
作者：
Farkas IJ;Szántó-Várnagy A;Korcsmáros T
生物医学实验工作的重点往往是改变选定蛋白质的功能。这些变化可能会影响信号通路，因此可能会出人意料地、非特异性地影响细胞过程。我们提出了一种在线工具Pathway Linker，它可以提供对这种变化可能产生的信号影响的初步估计，例如药物或microRNA治疗。通过将来自多个来源的蛋白质-蛋白质相互作用和信号通路数据与统计显着性检验和清晰的可视化相结合，Pathway Linker最大限度地减少了用户的努力。我们通过三个案例研究证明，所开发的工具可以在正常的实验室实验中指出意想不到的信号偏差，并在已知药物靶点的相互作用中识别可能的新信号蛋白。在我们的第一个案例研究中，我们表明，秀丽线虫CDC-25.1基因的敲除(旨在避免后代)可能会在全球范围内影响信号系统，并意外地影响实验。在第二个案例研究中，我们评估了一个鲜为人知的线虫基因的功能丧失表型，以预测其功能。在第三个案例研究中，我们分析了人类抗癌药物靶蛋白GJA1，并为该蛋白预测了新的信号通路成员，这可能是副作用的来源。与类似的服务相比，Path Linker的一个主要优势是它极大地减少了必要的人工文献搜索量，并且可以在没有计算背景的情况下使用。路径链接器可在http://PathwayLinker.org.上获得详细的文档和源代码可在网站上找到。
Biomedical experimental work often focuses on altering the functions of selected proteins. These changes can hit signaling pathways, and can therefore unexpectedly and non-specifically affect cellular processes. We propose PathwayLinker, an online tool that can provide a first estimate of the possible signaling effects of such changes, e.g., drug or microRNA treatments. PathwayLinker minimizes the users' efforts by integrating protein-protein interaction and signaling pathway data from several sources with statistical significance tests and clear visualization. We demonstrate through three case studies that the developed tool can point out unexpected signaling bias in normal laboratory experiments and identify likely novel signaling proteins among the interactors of known drug targets. In our first case study we show that knockdown of the Caenorhabditis elegans gene cdc-25.1 (meant to avoid progeny) may globally affect the signaling system and unexpectedly bias experiments. In the second case study we evaluate the loss-of-function phenotypes of a less known C. elegans gene to predict its function. In the third case study we analyze GJA1, an anti-cancer drug target protein in human, and predict for this protein novel signaling pathway memberships, which may be sources of side effects. Compared to similar services, a major advantage of PathwayLinker is that it drastically reduces the necessary amount of manual literature searches and can be used without a computational background. PathwayLinker is available at http://PathwayLinker.org. Detailed documentation and source code are available at the website.