Inferring the Sign of Kinase-Substrate Interactions by Combining Quantitative Phosphoproteomics with a Literature-Based Mammalian Kinome Network.

Marylens Hernandez, Alexander Lachmann, Shan Zhao, Kunhong Xiao, Avi Ma'ayan
{"title":"Inferring the Sign of Kinase-Substrate Interactions by Combining Quantitative Phosphoproteomics with a Literature-Based Mammalian Kinome Network.","authors":"Marylens Hernandez,&nbsp;Alexander Lachmann,&nbsp;Shan Zhao,&nbsp;Kunhong Xiao,&nbsp;Avi Ma'ayan","doi":"10.1109/BIBE.2010.75","DOIUrl":null,"url":null,"abstract":"<p><p>Protein phosphorylation is a reversible post-translational modification commonly used by cell signaling networks to transmit information about the extracellular environment into intracellular organelles for the regulation of the activity and sorting of proteins within the cell. For this study we reconstructed a literature-based mammalian kinase-substrate network from several online resources. The interactions within this directed graph network connect kinases to their substrates, through specific phosphosites including kinasekinase regulatory interactions. However, the \"signs\" of links, activation or inhibition of the substrate upon phosphorylation, within this network are mostly unknown. Here we show how we can infer the \"signs\" indirectly using data from quantitative phosphoproteomics experiments applied to mammalian cells combined with the literature-based kinase-substrate network. Our inference method was able to predict the sign for 321 links and 153 phosphosites on 120 kinases, resulting in signed and directed subnetwork of mammalian kinase-kinase interactions. Such an approach can rapidly advance the reconstruction of cell signaling pathways and networks regulating mammalian cells.</p>","PeriodicalId":87347,"journal":{"name":"Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/BIBE.2010.75","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBE.2010.75","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

Protein phosphorylation is a reversible post-translational modification commonly used by cell signaling networks to transmit information about the extracellular environment into intracellular organelles for the regulation of the activity and sorting of proteins within the cell. For this study we reconstructed a literature-based mammalian kinase-substrate network from several online resources. The interactions within this directed graph network connect kinases to their substrates, through specific phosphosites including kinasekinase regulatory interactions. However, the "signs" of links, activation or inhibition of the substrate upon phosphorylation, within this network are mostly unknown. Here we show how we can infer the "signs" indirectly using data from quantitative phosphoproteomics experiments applied to mammalian cells combined with the literature-based kinase-substrate network. Our inference method was able to predict the sign for 321 links and 153 phosphosites on 120 kinases, resulting in signed and directed subnetwork of mammalian kinase-kinase interactions. Such an approach can rapidly advance the reconstruction of cell signaling pathways and networks regulating mammalian cells.

Abstract Image

Abstract Image

Abstract Image

结合定量磷酸化蛋白质组学和基于文献的哺乳动物基因组网络推断激酶-底物相互作用的标志。
蛋白质磷酸化是一种可逆的翻译后修饰,通常用于细胞信号网络将细胞外环境的信息传递到细胞内细胞器,以调节细胞内蛋白质的活性和分选。在这项研究中,我们从几个在线资源中重建了一个基于文献的哺乳动物激酶-底物网络。这个有向图网络中的相互作用通过特定的磷酸位点,包括激酶调节相互作用,将激酶与其底物连接起来。然而,在这个网络中,连接的“迹象”,磷酸化后底物的激活或抑制,大多是未知的。在这里,我们展示了如何利用应用于哺乳动物细胞的定量磷酸化蛋白质组学实验数据,结合基于文献的激酶-底物网络,间接推断出“信号”。我们的推断方法能够预测120个激酶上的321个连接和153个磷酸位点的符号,从而得出哺乳动物激酶-激酶相互作用的符号和定向子网络。这种方法可以快速推进细胞信号通路和调节哺乳动物细胞网络的重建。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信