Deconstructing and Reconstructing the T Cell Signaling Network
Deconstructing and Reconstructing the T Cell Signaling Network
批准号:
8878998
负责人:
ARTHUR WEISS
金额:
$170.32万
依托单位国家:
美国
项目类别:
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-07-15 至 2016-06-30
关键词:
Antigen ReceptorsAntigen-Presenting CellsAntigensArthritisBehaviorBindingBiochemicalCell CommunicationCell membraneCell physiologyCellsCollaborationsComplexComputer SimulationDevelopmentDiffusionDimensionsDiseaseEquilibriumEventFeedbackGoalsGuanine Nucleotide Exchange FactorsITAMImmune System DiseasesImmune responseKineticsLeadLipid BilayersLupusMeasuresMediatingMembraneModelingMolecularOutputPathway interactionsPhosphorylationPlayProtein Tyrosine KinaseProtein Tyrosine PhosphataseProteinsReactionReceptor SignalingRecombinant ProteinsRegulationRegulatory PathwayRoleSignal TransductionSolutionsSon of Sevenless ProteinsSpecificitySurfaceSystemT cell regulationT cell therapyT-Cell ReceptorT-LymphocyteTyrosine PhosphorylationUrsidae FamilyZAP-70 Geneanalogbasecomplex biological systemscomputerized toolsinhibitor/antagonistinsightinterestkinase inhibitormembrane modelnovelnovel strategiesprogramsras Proteinstwo-dimensional
中文摘要
描述(由申请人提供):T细胞-抗原递呈细胞相互作用的复杂性以及目前用于研究它的简单生化方法需要不同的方法来理解TCR信号传导及其调控。共同的兴趣,现有的合作和独特的专业知识,为我们提供了(博士)。Chakraborty, Groves, Kuriyan, Roose和Weiss)提供了一个独特的机会,可以用更复杂和新颖的方法研究这个复杂的生物系统。我们在这里提出了一个全面的程序来了解相互作用分子的特异性和调控,并开发了一个系统来研究TCR调节的脂质双分子层系统上的信号事件,以模拟本质上发生在质膜二维空间上的事件。这种方法可能会对分子相互作用和动力学产生新的见解,这在复杂的细胞系统中是无法实现的,也无法被溶液中发生的反应所模仿,因为溶液中的扩散不限于二维。的确,出乎意料的结果是,与溶液动力学相比,催化活性显著增加,由Groves博士和Kuriyan博士获得,他们应用双层系统研究Ras和SOS蛋白在双层表面一起定位的影响。我们的总体目标是开发一个简单但强大的生化系统和TCR信号的计算模型,帮助我们理解调节的关键机制:(项目1)TCR相关免疫受体酪氨酸激活基元(ITAMs)和LAT的酪氨酸磷酸化;以及(项目#2)鸟嘌呤核苷酸交换因子(gef) RasGRP和SOS对LAT下游Ras的激活。通过研究二维系统中所涉及的分子的特异性、调控和活性,我们试图模拟质膜内小叶的表面。我们将从一个最小的简单系统开始,并迭代地增加复杂性。我们希望能够增加空间复杂性和分子复杂性。我们将研究定义明确的重要产出,并将不仅采用生化和生物物理措施,还将采用计算工具来表征该系统。我们将使用建模来比较简单和更复杂的系统,但也研究这些简单系统如何偏离溶液或更复杂的细胞系统中可获得的系统。
英文摘要
DESCRIPTION (provided by applicant): The complexity of the T cell - antigen presenting cell interaction and the current simple biochemical approaches being used to study it requires different approach to understand TCR signaling and its regulation. Common interests, existing collaborations and unique expertise, provide us (Drs. Chakraborty, Groves, Kuriyan, Roose and Weiss) with a unique opportunity to study this complex biological system with more sophisticated and novel approaches. We present here a comprehensive program to understand the specificity and regulation of the interacting molecules and the development of a system to study TCR regulated signaling events on a lipid bilayer system to simulate the events occurring essentially on the two dimensional space of the plasma membrane. Such an approach is likely to yield novel insights into molecular interactions and kinetics not obtainable in complex cellular systems and not mimicked by reactions that occur in solution, where diffusion is not limited to 2 dimensions. Indeed, unanticipated results, with marked increase in catalytic activity compared to solution kinetics, were obtained by Dr. Groves and Kuriyan who applied a bilayer system to study the influence of localizing Ras and SOS proteins together at the surface of a bilayer. Our overall objective is to develop a simple but robust biochemical system and computational model of TCR signaling that helps us understand the critical mechanisms that regulate: (Project #1) tyrosine phosphorylation of the TCR-associated immunoreceptor tyrosine-based activation motifs (ITAMs) and of LAT; and, (Project #2) the activation of Ras downstream of LAT by the guanine nucleotide exchange factors (GEFs) RasGRP and SOS. By studying the specificity, regulation and the activities of the molecules involved in a two-dimensional system we attempt to mimic the surface of the inner leaflet of the plasma membrane. We will start with a minimal simple system and iteratively add complexity. We hope to be able to add spatial complexity and molecular complexity. We will study well-defined and important outputs, and will bring to bear not only biochemical and biophysical measures but also computational tools to characterize this system. We will use modeling to compare simple to more complex systems but also study how these simple systems deviate from those obtainable in solution or in more complex cellular systems.
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