Computational Genomics of Signal Transduction
Computational Genomics of Signal Transduction
批准号:
8055379
负责人:
Igor B. Jouline
金额:
$28.0万
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-09-06 至 2014-03-31
关键词:
AddressAmino AcidsAnalysis of VarianceAnimal ModelAreaBacteriaBehaviorBehavioralBindingBinding SitesBiochemicalBiochemical GeneticsBiologicalBiological ProcessBiologyCaringCell membraneCellsChemoreceptorsChemotaxisClassificationCommunicable DiseasesComplexComputing MethodologiesCritical PathwaysDataDiseaseDockingDrug DesignEnzymesExplosionGene ProteinsGenerationsGeneticGenomicsGoalsHealthHumanIndividualInvadedKnowledgeLaboratoriesLeadLearningLifeMalignant NeoplasmsMapsMediatingMethodologyMethodsMethylationModelingModificationMolecularNatureOmpR proteinOrganismOutputPathway interactionsPharmaceutical PreparationsPhosphoric Monoester HydrolasesPhosphorylationPhosphotransferasesPhylogenetic AnalysisPost-Translational Protein ProcessingProcessProtein DephosphorylationProteinsResearchResolutionRoleScaffolding ProteinSequence AnalysisSignal PathwaySignal TransductionSignal Transduction PathwaySiteStimulusStudy modelsSubgroupSwimmingSystemSystems AnalysisSystems BiologyTechniquesTestingTherapeutic AgentsVirulenceWorkbasecell behaviorcomparative genomicsdesignelectron tomographyhigh riskhuman diseaseinnovationinsightmolecular dynamicsnew therapeutic targetnovelpathogenpathogenic bacteriaprotein complexprotein protein interactionprotein-histidine kinasepublic health relevancereceptorresponsescaffoldsimulationthree dimensional structuretrend
中文摘要
描述(申请人提供):信号转导通路被所有细胞用来检测环境刺激并产生适当的行为反应。这些途径是人类疾病的关键组成部分,使病原体能够检测并入侵人类宿主,当功能不正常时,会导致癌症和其他疾病。在原核生物和真核生物中,信号转导通路涉及多种蛋白质-蛋白质相互作用,这些相互作用通过蛋白质的共价修饰(如磷酸化)或相互作用介导的蛋白质构象变化来促进信息传递。了解信号转导通路中蛋白质之间的相互作用将有益于影响人类健康的广泛领域。细菌的趋化系统代表了当今生物学中研究得最好的信号转导系统。这一途径使细菌能够通过细胞膜上的化学感受器检测外部刺激,并通过组氨酸蛋白激酶对反应调节蛋白的磷酸化来控制细胞的游泳行为。趋化途径已被研究多年,提供了丰富的结构、生化和遗传信息。然而,关于该系统的许多重要问题仍然没有答案:信号复合体是如何组装的,例如:信号是如何终止的,以及受体的共价修饰如何有助于适应。我们的长期目标是了解活细胞如何在分子水平上检测、传输和适应各种信号。在这项提案中,我们将应用计算基因组和生物物理方法来了解细菌趋化信号转导途径的三个关键步骤:激发、信号终止和适应。新的方法将被用来研究这些领域中的蛋白质-蛋白质相互作用。这将包括基于系统发育分析创建趋化蛋白的自然分类,识别进化相关亚群中的保守残基,共同进化残基的协方差分析,以及测试蛋白质-蛋白质相互作用模型的分子对接模拟。在目标1中,这些方法将用于研究参与兴奋通路的化学受体(MCPs)、支架蛋白(CHEW)和组氨酸激酶(CHEA)之间的相互作用。目标2将集中在反应调节因子(CHEY)和参与终止兴奋性信号的磷酸酶之间的相互作用。目的3研究具有甲基转移酶、甲基酯酶或脱氨酶活性的酶对化学感受器进行共价修饰的适应途径的关键相互作用。这项工作将产生细菌趋化作用途径中蛋白质-蛋白质相互作用的可测试模型,这将推动我们的合作者和其他实验室进一步的实验和系统生物学研究。通过这些研究获得的原理将提供关于信号转导的重要信息,并有助于针对控制人类病原体毒力的信号通路的新疗法的设计。
与公共卫生相关:信号转导是对所有生物体至关重要的普遍生物过程,也是针对包括癌症和传染病在内的各种情况设计新药的目标。我们将详细研究细菌中的信号转导途径,以了解在许多生物体中管理类似过程的普遍原理。所得结果可用于确定针对病原菌的新治疗药物的靶点。
英文摘要
DESCRIPTION (provided by applicant): Signal transduction pathways are used by all cells to detect environmental stimuli and generate appropriate behavioral responses. These pathways are critical components of human disease, allowing pathogens to detect and invade the human host and when not functioning properly, leading to cancer and other diseases. In both prokaryotic and eukaryotic organisms, signal transduction pathways involve multiple protein-protein interactions that facilitate information transfer by covalent modification of proteins (e.g. phosphorylation) or interaction-mediated conformational changes in the proteins. Understanding protein-protein interactions within signal transduction pathways will benefit a wide range of fields impinging on human health. The chemotaxis system of bacteria represents the best studied signal transduction in biology today. This pathway allows bacteria to detect external stimuli via chemoreceptors in the cell membrane and control the cell's swimming behavior through phosphorylation of a response regulator protein by a histidine protein kinase. The chemotaxis pathway has been studied for many years, providing a wealth of structural, biochemical, and genetic information. However, many important questions about the system remain unanswered: how the signaling complex is assembled, for example: how signals are terminated, and how covalent modification of receptors contributes to adaptation. Our long term goal is to understand how living cells detect, transmit, and adapt to various signals on a molecular level. In this proposal we will apply computational genomic and biophysical approaches to understanding three key steps of the bacterial chemotaxis signal transduction pathway: excitation, signal termination, and adaptation. Novel methodology will be utilized to study protein- protein interactions in each of these areas. This will involve creating a natural classification of chemotaxis proteins based on phylogenetic analysis, identification of conserved residues within evolutionarily related subgroups, co-variance analysis of co-evolving residues, and molecular docking simulations to test models of protein-protein interactions. In Aim 1, these methods will be applied to the interactions between the chemoreceptors (MCPs), the scaffolding protein (CheW), and the histidine kinase (CheA) involved in the excitation pathway. Aim 2 will concentrate on interactions between the response regulator (CheY) and phosphatases involved in termination of the excitatory signal. Aim 3 will investigate interactions critical to the adaptation pathway involving covalent modification of the chemoreceptor by enzymes with methytransferase, methylesterase, or deamidase activities. This work will produce testable models of protein-protein interactions within the bacterial chemotaxis pathway that will drive further experimental and systems biology research by our collaborators and other laboratories. The principles learned through these studies will provide important information about signal transduction and aid the design of new therapeutics targeting the signaling pathways that control virulence in human pathogens.
PUBLIC HEALTH RELEVANCE: Signal transduction is a universal biological process vital to all organisms and is a target for the design of new drugs against a variety of conditions including cancer and infectious diseases. We will study in detail a signal transduction pathway in bacteria in order to gain understanding of universal principles that govern similar processes in many organisms. The results obtained may be used to identify targets for new therapeutic agents against pathogenic bacteria.
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Computational Genomics of Signal Transduction
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批准号:10393584
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项目类别:
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资助金额:$38.17万
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财政年份:2019
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负责人:Igor B. Jouline
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资助金额:$38.17万
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财政年份:2019
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批准号:10624777
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财政年份:2014
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资助金额:$28.34万
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批准号:7494516
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项目类别:
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资助金额:$18.45万
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财政年份:2004
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负责人:Igor B. Jouline
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依托单位:
Computational Genomics of Signal Transduction
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批准号:6946930
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项目类别:
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资助金额:$18.74万
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负责人:Igor B. Jouline
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项目类别:
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资助金额:$28.15万
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Computational Genomics of Signal Transduction
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批准号:7888651
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项目类别:
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资助金额:$28.09万
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财政年份:2004
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负责人:Igor B. Jouline
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依托单位:
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批准号:7283092
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项目类别:
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资助金额:$18.48万
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财政年份:2004
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负责人:Igor B. Jouline
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依托单位:
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批准号:7116901
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项目类别:
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资助金额:$18.66万
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财政年份:2004
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负责人:Igor B. Jouline
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依托单位:
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批准号:8450842
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项目类别:
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资助金额:$27.34万
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财政年份:2004
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批准号:6819029
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项目类别:
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资助金额:$22.5万
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财政年份:2004
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负责人:Igor B. Jouline
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依托单位:
海外基金