Quantitative Interaction Networks for Tyrosine-Phosphorylated Proteins

酪氨酸磷酸化蛋白质的定量相互作用网络

• 批准号: 7659578
• 负责人: GAVIN MACBEATH
• 金额: $ 35.57万
• 依托单位: HARVARD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-13 至 2010-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7659578
• 关键词: Address; Adhesions; Antibodies; Apoptosis; Binding; Cell Nucleus; Cell membrane; Cell physiology; Cells; Classification; Complex; Data; Diabetes Mellitus; Dissociation; Epidermal Growth Factor Receptor; Equilibrium; ErbB Receptor Family Protein; Eukaryota; Event; FGFR1 gene; FGFR3 gene; FRS2 gene; Family; Fibroblast Growth Factor Receptors; Growth; Half-Life; Human; Human Genome; IRS1 gene; Immune; Individual; Insulin Receptor; Investigation; Label; Ligands; Light; Location; Malignant Neoplasms; Mediating; Microarray Analysis; Modeling; Molecular; Neurites; Outcome; PC12 Cells; PTB Domain; Peptides; Phosphopeptides; Phosphotyrosine; Principal Investigator; Process; Property; Protein Microchips; Protein Tyrosine Kinase; Proteins; Receptor Protein-Tyrosine Kinases; Recombinants; Recruitment Activity; Research Personnel; Role; Signal Transduction; Signaling Molecule; Signaling Protein; Specificity; Substrate Interaction; System; Time; Tyrosine; Tyrosine Phosphorylation; Tyrosine Phosphorylation Site; Vascular Endothelial Growth Factor Receptor; Western Blotting; base; cancer cell; computer studies; computerized data processing; enzyme substrate; genome-wide; human disease; metaplastic cell transformation; migration; molecular recognition; neglect; novel; numb protein; overexpression; programs; protein complex; protein protein interaction; ras GTPase-Activating Proteins; receptor; receptor-mediated signaling; src-Family Kinases; web site

DESCRIPTION (provided by applicant): Intracellular signaling networks that involve protein tyrosine kinases are critical in the control of most cellular processes, including growth, adhesion, migration, differentiation, and apoptosis. Misregulation of these networks results in a variety of human diseases, including cancer, diabetes, and immune deficiency. Many of the proteins in these networks contain Src homology 2 (SH2) or phosphotyrosine binding (PTB) domains, which recognize tyrosine-phosphorylated proteins in a sequence-specific fashion. In this proposal, the molecular recognition properties of virtually every SH2 and PTB domain encoded in the human genome will be investigated with respect to physiologically-relevant ligands using protein microarray technology. Recombinant SH2/PTB domains will be arrayed in the wells of microtiter plates and subsequently probed with 258 fluorescently-labeled phosphopeptides representing experimentally-verified sites of tyrosine phosphorylation on human receptor tyrosine kinases, as well as with 604 peptides representing sites of tyrosine phosphorylation on downstream proteins (nonreceptor tyrosine kinases and SH2/PTB-containing proteins). By probing the arrays with eight different concentrations of each peptide, equilibrium dissociation constants will be determined for the binding of each peptide to each protein (~140 active SH2/PTB constructs). This effort will produce high quality, quantitative protein interaction networks which will reveal individual connections between signaling proteins, as well as how network connectivity changes with protein concentration. We have previously proposed that the extent to which a protein becomes more promiscuous when overexpressed contributes to its oncogenicity, and the study described here will generate the quantitative data needed to investigate this hypothesis further. In addition, the information revealed by our systematic efforts should prove invaluable to cell and cancer biologists who study tyrosine kinase-mediated signaling, to computational biologists who study molecular recognition, and to systems biologists who seek to model signal transduction networks. As such, we intend to make our data easily accessible though an interactive web site in formats suitable both for broad computational studies and for more focused hypothesis-driven inquiries. It is our hope that the studies described here will shed light on how signaling proteins are integrated into complex networks and how we can intervene most effectively when these networks go awry.

描述（由申请人提供）：涉及蛋白质酪氨酸激酶的细胞内信号传导网络对于控制大多数细胞过程至关重要，包括生长，粘附，迁移，分化和凋亡。这些网络的不正体导致各种人类疾病，包括癌症，糖尿病和免疫缺陷。这些网络中的许多蛋白质都包含SRC同源性2（SH2）或磷酸酪氨酸结合（PTB）结构域，它们以序列特异性方式识别酪氨酸磷酸化的蛋白质。在此提案中，使用蛋白质微阵列技术，将研究人类基因组中每个SH2和PTB结构域的分子识别特性。重组SH2/PTB结构域将在微量滴定板的井中持续，然后用258种代表实验验证的酪氨酸磷酸化位点的荧光标记的磷酸肽进行探测激酶和含SH2/PTB的蛋白质）。通过探测每种肽八个不同浓度的阵列，将确定平衡解离常数，以使每种肽与每种蛋白质的结合（〜140个活性SH2/PTB构建体）。这项工作将产生高质量的定量蛋白质相互作用网络，这些网络将揭示信号蛋白之间的各个连接，以及网络连通性如何随蛋白质浓度而变化。我们先前已经提出，过表达蛋白质有助于其致癌性时，蛋白质变得更加混杂，此处描述的研究将产生进一步研究该假设所需的定量数据。此外，我们的系统努力所揭示的信息应该证明是研究酪氨酸激酶介导的信号传导的细胞和癌症生物学家，对研究分子识别的计算生物学家以及试图建模信号传输网络的系统生物学家的计算生物学家。因此，我们打算通过适合广泛的计算研究和更集中的假设驱动的查询的格式的交互式网站，使我们的数据易于访问。我们希望这里描述的研究能够阐明信号蛋白如何集成到复杂的网络中以及当这些网络出现问题时如何最有效地干预。

项目成果

Tarp regulates early Chlamydia-induced host cell survival through interactions with the human adaptor protein SHC1.

• DOI: 10.1083/jcb.200909095
• 发表时间: 2010-07-12
• 期刊: The Journal of cell biology
• 作者: Mehlitz A;Banhart S;Mäurer AP;Kaushansky A;Gordus AG;Zielecki J;Macbeath G;Meyer TF
• 通讯作者: Meyer TF

Profiling phospho-signaling networks in breast cancer using reverse-phase protein arrays.

• DOI: 10.1038/onc.2012.378
• 发表时间: 2013-07-18
• 期刊: ONCOGENE
• 影响因子: 8
• 作者: Gujral, T. S.;Karp, R. L.;Finski, A.;Chan, M.;Schwartz, P. E.;MacBeath, G.;Sorger, P.
• 通讯作者: Sorger, P.