Mapping the Human Binary Interactome Network

绘制人类二元相互作用组网络

• 批准号: 7530040
• 负责人: David E. Hill
• 金额: $ 180万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-07-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7530040
• 关键词: Address; Bioinformatics; Biological Assay; Caenorhabditis elegans; Cells; Classification; Code; Complex; DNA; Data; Data Quality; Data Set; Disease; Drosophila genus; Ensure; Foundations; Funding; Generations; Genes; Goals; Human; Literature; Manuscripts; Maps; Modeling; Open Reading Frames; Organism; Personal Satisfaction; Preparation; Production; Proteins; Proteome; Publications; Publishing; RNA Splicing; RNA-Protein Interaction; Range; Saccharomyces cerevisiae; Specificity; Testing; Time; Update; Validation; Variant; Yeasts; improved; in vivo; interest; member; research study; yeast two hybrid system

DESCRIPTION (provided by applicant): The interactome of an organism is the network formed by the complete set of physical interactions that can occur in a range of physiologically relevant concentrations, including protein-protein, DNA-protein, and RNA-protein interactions. The generation of proteome-wide interactome network maps with high specificity and high sensitivity is a necessary, although not sufficient, aspect in the quest of generating predictive macromolecular models at the scale of the whole cell. Moreover, these maps serve as a foundation for mechanistic and quantitative studies of poorly characterized predicted gene products and disease-associated proteins. There are two major approaches to experimentally map the protein-protein interactome network of any organism of interest: i) all pairwise combinations of pairs of predicted proteins can be experimentally tested to derive all possible binary physical interactions (binary interactome); and ii) all proteins can be tested to interrogate in which protein complex(es) they belong (co-complex interactome). It is well established that binary and co-complex approaches are complementary in providing increasingly accurate and complete interactome models. We propose to continue our efforts at systematically mapping the human binary interactome with the goal of generating and analyzing a new version of HT-Y2H interactions with high quality and high sensitivity for all pairwise combinations of predicted gene products for which we have at least one Gateway-cloned ORF available. This corresponds to a matrix of ~16,000 X 16,000 proteins, which represents ~50% of the complete matrix since we assume a total of ~22,000 protein-coding genes and limit the analysis to a single splice variant per gene. Our modified specific aims are to: i) Provide an expanded high-confidence/high-coverage version of the human binary interactome map ii) Validate human binary interaction data iii) Analyze the expanded human interactome model

描述（由申请人提供）：生物体的相互作用组是由一整套物理相互作用形成的网络，这些相互作用可以在生理相关浓度范围内发生，包括蛋白质-蛋白质、DNA-蛋白质和RNA-蛋白质相互作用。具有高特异性和高灵敏度的蛋白质组范围的相互作用组网络图的生成是在全细胞规模上生成预测性大分子模型的探索中的必要的，尽管不是充分的方面。此外，这些地图作为机制和定量研究的基础，预测的基因产物和疾病相关的蛋白质的特点不佳。有两种主要方法来实验性地映射任何感兴趣的生物体的蛋白质-蛋白质相互作用组网络：i）可以实验性地测试预测蛋白质对的所有成对组合以导出所有可能的二元物理相互作用（二元相互作用组）;以及ii）可以测试所有蛋白质以询问它们属于哪种蛋白质复合物（共复合物相互作用组）。众所周知，二元和共复合物方法在提供越来越准确和完整的相互作用组模型方面是互补的。我们建议继续努力系统地绘制人类二元相互作用组，目标是生成和分析HT-Y2 H相互作用的新版本，其具有高质量和高灵敏度，适用于预测基因产物的所有成对组合，我们至少有一个网关克隆的ORF可用。这对应于~ 16，000 X 16，000个蛋白质的矩阵，其代表完整矩阵的~50%，因为我们假设总共~ 22，000个蛋白质编码基因，并且将分析限制为每个基因的单个剪接变体。 我们修改后的具体目标是： i）提供人类二元相互作用组图谱的扩展的高置信度/高覆盖率版本 ii）人类二元交互数据 iii）分析扩展的人类相互作用组模型