Modeling human phosphorylation networks through kinome-wide profiling
Modeling human phosphorylation networks through kinome-wide profiling
批准号:
8579092
负责人:
BENJAMIN E TURK
金额:
$49.93万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-10 至 2018-05-31
关键词:
Affinity ChromatographyAntineoplastic AgentsBioinformaticsBiological AssayCell ProliferationCollectionCommunitiesComplementComputersConsensusConsensus SequenceCultured CellsDataData SetDatabasesDiseaseDrug TargetingEukaryotaEventFeedbackFundingGoalsHealthHumanHuman GenomeInformaticsLATS1 geneLATS2 geneMammalian CellMapsMass Spectrum AnalysisMethodsMitosisModelingModificationPathologyPathway interactionsPeptide LibraryPeptidesPharmaceutical PreparationsPhosphorylationPhosphorylation SitePhosphotransferasesPlayPost-Translational Protein ProcessingProtein KinaseProteinsProteomeRegulationResearchResearch PersonnelResourcesScanningSignal PathwaySignal TransductionSignal Transduction PathwaySignaling ProteinSiteSpecificityTechniquesTumor Suppressor ProteinsUnited States National Institutes of HealthValidationWorkcell behaviordrug discoveryexpression vectorfallshigh throughput analysishuman diseaseinhibitor/antagonistinsightminiaturizenovelpublic health relevanceresearch studyscreeningtherapeutic targettooltumorweb-accessible
中文摘要
描述(申请人提供):蛋白质磷酸化是真核生物中最常见的可逆的翻译后修饰,但由蛋白激酶、它们的调节器和它们的底物组成的信号网络只被部分阐明。拟议项目的总体目标是使用排列的位置扫描多肽文库,为人类基因组中编码的整个蛋白激酶集合建立一个全面的共识磷酸化基序集合,并将这些数据整合到目前整个生物医学界可用的网络可访问工具中。由此产生的蛋白激酶专一性基序和信息学工具的数据集将:(1)允许对其磷酸化位置已经或目前正在高通量磷酸蛋白质组质谱学实验中被绘制的大量蛋白质进行功能注释;以及通过现在识别负责这些修饰的相关的激酶和信号通路,允许识别新的蛋白质
与人类健康和疾病相关的激酶底物,并将它们置于特定信号转导途径的背景下;以及(3)提供一套可用于结构和药物抑制剂研究以及针对与人类疾病有关的特定信号通路的治疗性靶向的一套通用的激酶工具。为了说明我们方法的实用性,我们将研究河马信号通路中蛋白激酶的预测底物,河马信号通路是一种保守的肿瘤抑制通路,在调节细胞增殖、分化和生存方面发挥重要作用。这个项目将有助于增加我们对蛋白激酶如何实现特异性的基本理解,将识别信号网络中的关键连接,并将为研究信号转导和蛋白质磷酸化的研究人员提供一般资源。
英文摘要
DESCRIPTION (provided by applicant): Protein phosphorylation is the most common reversible post-translational modification in eukaryotes, yet signaling networks comprising protein kinases, their regulators, and their substrates are only partially elucidated. The overall goals of the proposed project are to build a comprehensive collection of consensus phosphorylation motifs for the entire collection of protein kinases encoded in the human genome using arrayed positional scanning peptide libraries, and integrate this data into web-accessible tools that are currently available to the entire biomedical community. The resulting dataset of protein kinase specificity motifs and informatics tools will: (1) allow functional annotation of a large number of proteins whose phosphorylation sites already have been, or currently are, being mapped in high-throughput phosphoproteomic mass- spectrometry experiments and datasets that have been previously funded by the NIH by now identifying the relevant kinase and signaling pathways responsible for these modifications; (2) allow the identification of new protein
kinase substrates relevant to human health and disease and place them within the context of specific signal transduction pathways; and (3) provide a general set of kinase tools useful for structural and drug inhibitor studies and for the therapeutic targeting of specific signaling pathways implicated in human disease. To illustrate the utility of our approach, we will investigate predicted substrates of protein kinases in the Hippo signaling pathway, a conserved tumor suppressor pathway important in regulating cell proliferation, differentiation and survival. This project will serve to increase our fundamental understanding of how specificity is achieved by protein kinases, will identify critical connections in signaling networks, and will provide a general resource for researchers studying signal transduction and protein phosphorylation.
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