Illuminating the Druggable Genome Knowledge Management Center (IDG KMC)

描述：照亮可药物基因组知识管理中心（IDG KMC）的总体目标是评估和组织（通过数据组织核心，DOC），呈现和可视化（通过用户界面门户，UIP）和排名（与IDG联盟合作）所有潜在的疾病相关蛋白，作为四个蛋白质超家族的潜在可药物靶点：g蛋白偶联受体（gpcr），核受体（nr），离子通道（IC）和激酶。通过结合从多个来源提取的数据，再加上算法处理、预测和人工管理，新兴知识将与适当的蛋白质相关联。KMC将把疾病、通路、蛋白质、基因、化学、生物活性、药物发现和临床信息元素从DOC“目标中心”资源数据库的数据库、文献、专利和其他文件中链接起来。TCRD将作为IDG查询平台的主要来源，该平台是ulp开发的系统，将使科学家能够访问、可视化和分析IDG特定数据。协调DOC和UIP活动的行政核心（AC）将通过组织特定类别的外部目标小组（External Target panel）来协助人类管理，将蛋白质分为4类(tclini - clini

DESCRIPTION: The overall goal of the Illuminating the Druggable Genome Knowledge Management Center (IDG KMC) is to evaluate and organize (via the Data Organizing Core, DOC), present and visualize (via the User Interface Portal, UIP) and rank (in cooperation with the IDG Consortium) all prospective disease-linked proteins, as potential druggable targets for four protein superfamilies: G-protein-coupled receptors (GPCRs), nuclear receptors (NRs), ion channels (IC) and kinases. By combining data extracted from multiple sources, coupled with algorithmic processing, prediction and human curation, the emerging knowledge will be associated with the appropriate proteins. The KMC will link disease, pathway, protein, gene, chemical, bioactivity, drug discovery and clinical information elements from databases, literature, patents and other documents in the DOC "Target Central" Resource Database. TCRD will serve as primary source for the IDG Query Platform, the UlP-developed system that will enable scientists to access, visualize and analyze IDG-specific data. Coordinating DOC and UIP activities, the Administrative Core, AC, will assist with human curation by organizing class-specific External Target Panels to categorize proteins into 4 classes (Tclin - clinical; Tchem - manipulated by chemicals; Tmacro - manipulated by macromolecules; and Tdark - the genomic "dark matter"). Tissue and cellular localization for both disease and protein will serve as central filtes for ranking. The specific aims of the KMC are based on the demonstrated experience of the Oprea-Sklar team at the University of New Mexico (data capture, processing, mining and modeling), and the Simeonov-led team at NCATS (software development, visualization and modeling), supported by teams based in Denmark, Florida and UK. Using automated tools, we performed disease-protein associations for each protein superfamily, obtained preliminary stratification (e.g., Tclin 22%, Tdark 30%), and designed Specific Aims that enable us to further annotate this genome subset. It is expected that within 12 months, the TCRD-based IDG Querly Platform will be operational, which may dramatically improve the target prioritization process for the research community at large and the IDG Consortium, in exploring "dark matter" for GPCRs, NRs, ICs and kinases.