Identifying The Human Calcineurin Signaling Network

识别人类钙调神经磷酸酶信号网络

基本信息

批准号：
9276716
负责人：
Martha S. Cyert
金额：
$ 48.31万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-06-01 至 2020-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9276716
关键词：
Address Adverse effects Affinity Animals Binding Binding Proteins Binding Sites Biochemical Bioinformatics Calcineurin Calcineurin inhibitor Calmodulin Catalytic Domain Cells Characteristics Chronic Clinical Complement Complex Computer Simulation Computing Methodologies Coronary Arteriosclerosis Cyclosporine Diabetes Mellitus Diagnosis Disease Docking Etiology Event FK506 Heart Diseases Human Immune System Diseases Immunosuppressive Agents In Vitro Ion Channel Kidney Failure Knowledge Libraries Malignant Neoplasms Mammals Mediating Methods Mutate Organism Parents Patients Peptides Phage Display Phosphoric Monoester Hydrolases Phosphorylation Phosphotransferases Process Protein Dephosphorylation Protein Region Protein phosphatase Proteins Proteome Proteomics Regulation Renal function Research Personnel Resources Schizophrenia Signal Pathway Signal Transduction Signaling Protein Site Specificity Structure Surface System Techniques Testing Therapeutic Viral Proteins Virus Diseases Virus Inhibitors Work Yeasts base computerized tools drug discovery experience flexibility in vivo insight novel novel strategies novel therapeutic intervention prevent protein function protein protein interaction public health relevance receptor research study success transcription factor yeast protein

Address Adverse effects Affinity Animals Binding Binding Proteins Binding Sites Biochemical Bioinformatics Calcineurin Calcineurin inhibitor Calmodulin Catalytic Domain Cells Characteristics Chronic Clinical Complement Complex Computer Simulation Computing Methodologies Coronary Arteriosclerosis Cyclosporine Diabetes Mellitus Diagnosis Disease Docking Etiology Event FK506 Heart Diseases Human Immune System Diseases Immunosuppressive Agents In Vitro Ion Channel Kidney Failure Knowledge Libraries Malignant Neoplasms Mammals Mediating Methods Mutate Organism Parents Patients Peptides Phage Display Phosphoric Monoester Hydrolases Phosphorylation Phosphotransferases Process Protein Dephosphorylation Protein Region Protein phosphatase Proteins Proteome Proteomics Regulation Renal function Research Personnel Resources Schizophrenia Signal Pathway Signal Transduction Signaling Protein Site Specificity Structure Surface System Techniques Testing Therapeutic Viral Proteins Virus Diseases Virus Inhibitors Work Yeasts base computerized tools drug discovery experience flexibility in vivo insight novel novel strategies novel therapeutic intervention prevent protein function protein protein interaction public health relevance receptor research study success transcription factor yeast protein

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项目摘要

DESCRIPTION (provided by applicant): The absence of experimental and computational tools for global identification of phosphatase substrates leaves a major gap in our understanding of cellular regulatory networks and prevents systems-level analyses of phosphatase signaling. The proposal addresses this knowledge gap by systematically identifying targets of calcineurin (CN), the ubiquitous Ca2+/calmodulin-dependent protein phosphatase and target of immunosuppressants, FK506 and cyclosporin A. Only 25 substrates are currently attributed to CN in mammals--the same as in yeast, whose proteome is ~tenfold smaller, and chronic inhibition of CN in patient's cause's side-effects by disrupting unidentified regulatory events. This suggests that in humans, the majority of CN substrates, and thus its regulatory functions, remain to be identified. Recent insights into CN substrate recognition drive our approach: CN binds to short linear motifs (SLiMs), termed PxIxIT and LxVP, which can occur hundreds of residues away substrate dephosphorylation sites. Mutating these motifs or preventing their binding to conserved surfaces on CN, i.e. with FK506, CysA, or viral inhibitor A238L, blocks dephosphorylation. Building upon our previous success establishing the CN signaling network in yeast, we are determining human CN substrates by systematically identifying CN- binding peptides in the proteome, which is challenging due to their low affinities and degenerate sequences. This work aims to 1) systematically discover human PxIxIT and LxVP-type sequences by synergizing experimental and computational methods. CN-binding sequences are directly selected from phage display libraries that contain all disordered regions of the human proteome, where SLiMs reside. PxIxITs are also identified in silico by leveraging their characteristic structural features and using a novel method to predict binding to the conserved PxIxIT-docking surface on CN. Candidate sequences are validated for CN-binding in vitro, and in Aim 2 their parent proteins are tested for interaction with and/or dephosphorylation by CN in cultured animal cells. In Aim 3 we characterize the functions and binding mode of a newly discovered CN-binding motif, YLxxLF, which may identify a distinct class of CN- interacting proteins and provide avenues for selective disruption of CN signaling events. This systems- level analysis of CN signaling in humans will ultimately identify intersections with other regulatory networks that can be exploited therapeutically, such as providing strategies to ameliorate immunosuppressant side effects. Furthermore, this work will provide fundamental insights into how phosphatases achieve specificity and will create a critical new resource for researchers studying Ca2+ or phosphorylation-dependent regulation of protein function.

描述（通过应用程序提供）：缺少用于磷酸酶底物的全球鉴定的实验和计算工具在我们对细胞调节网络的理解中留下了一个重大差距，并阻止了磷酸酶信号传导的系统级分析。该提议通过系统地识别钙调神经酶（CN）的靶标，无处不在的Ca2+/钙调蛋白依赖性蛋白质磷酸酶以及免疫抑制剂，FK506和环孢菌素A的靶标解决了这一知识差距。目前，只有25个底物归因于Cn的较小的蛋白质，其在YEAST中是较小的，其蛋白质是在YEAST中属于CN的25个。患者的副作用通过破坏身份不明的监管事件来产生。这表明，在人类中，大多数CN底物及其调节功能仍有待鉴定。对CN底物识别的最新见解可以推动我们的方法：CN与短线性基序（Slim）结合，称为PXIXIT和LXVP，这可能会出现数百个残留物，从而将底物去磷酸化位点远离。突变这些基序或防止其与CN上配置的表面的结合，即用FK506，CYSA或病毒抑制剂A238L阻止去磷酸化。在我们以前的成功建立CN信号网络中的基础上，我们通过系统地识别蛋白质组中的CN结合肽来确定人类CN底物，这是由于其低亲和序列而受到挑战。这项工作的目的是1）通过协同实验和计算方法来系统地发现人类pxixit和LXVP型序列。 CN结合序列是直接从包含Slims居住的人类蛋白质组的所有无序区域的噬菌体显示库中选择的。在计算机中还可以通过利用其特征性结构特征并使用新颖的方法来预测CN上配置的PXIXIT-docking表面的结合来确定PXIXIT。候选序列在体外进行了CN结合验证，在AIM 2中，他们的母蛋白与CN在培养的动物细胞中的相互作用和/或去磷酸化进行了测试。在AIM 3中，我们表征了新发现的CN结合基序YLXXLF的功能和结合模式，该图案可以识别一类不同的CN-相互作用蛋白，并为选择性破坏CN信号事件提供途径。该系统级别对人类中CN信号的分析将最终确定可以热探索的其他调节网络的交叉点，例如提供减轻免疫抑制副作用的策略。此外，这项工作将提供有关磷酸酶如何达到特异性的基本见解，并为研究CA2+或磷酸化依赖性蛋白质功能调节的研究人员创造关键的新资源。