The Transporter Classification Database (TCDB)

描述（由申请人提供）：转运蛋白催化分子进出细胞和细胞器。它们实现细胞内稳态，负责病原体和肿瘤中的多药耐药性，并且当有缺陷时，导致数十种重要的人类遗传疾病。我们的实验室维护，更新和改进转运蛋白分类数据库，TCDB，其中包含转运蛋白分类（TC）系统，由国际生物化学和分子生物学联合会（IUBMB）正式采用。TCDB是国际公认的，仔细注释的，通用的标准，用于分类和提供有关生命所有主要领域中转运蛋白和转运相关蛋白的信息。它提供了关于这些蛋白质及其组成的转运系统的序列、生物化学、生理学、病理学、结构和进化数据。它使用了一个成功的分类系统，基于转运蛋白类，亚类，家族，亚家族，单个转运系统和组成蛋白。 在GM0077402的竞争性更新中，我们建议扩展、更新、自动化和互连TCDB。特别是，我们将合作整合和统一TCDB和Pfam使用的分类系统，形成一个TC本体系统。我们将产生有关转运蛋白的新数据，并扩展功能预测的程序。这最后的努力将获得可靠的新的生物学知识，从各种来源，包括遗传学，基序，结构域，操纵子和调节子分析。我们的具体目标如下：1.比较和评价同源性建立的方法，例如，我们和Pfam的统计方法，以及介绍一个系统的蛋白质重复单元和结构域的识别。我们将确认和扩展同源性结果的基础上，结构重叠和配置文件：配置文件比较。我们将开发和实施PFAM和TCDB之间的信息交流管道，并使两个分类系统标准化。2.将我们的家庭描述纳入维基百科，以促进社区注释和互动。因此，我们将添加到维基百科，并与Pfam集成，为社区注释创建一个公共平台。3.使用ChEBI和GO建立TCDB的底层本体框架。4.使用和自动化多种方法，包括同源性和同线性，以获得可靠的功能预测，并为其他研究人员提供指导。5.利用我们的TCDB咨询委员会，持续实现知识库现代化和可持续性。

DESCRIPTION (provided by applicant): Transporters catalyze entry and exit of molecules into and out of cells and organelles. They achieve cellular homeostasis, are responsible for multidrug resistance in pathogens and tumors, and when defective, cause dozens of important human genetic diseases. Our laboratory maintains, updates and improves the Transporter Classification Database, TCDB, which houses the Transporter Classification (TC) system, adopted officially by the International Union of Biochemistry and Molecular Biology (IUBMB). TCDB is the internationally acclaimed, carefully annotated, universal standard for classifying and providing information about transporters and transport-related proteins in all major domains of life. It presents sequence, biochemical, physiological, pathological, structural and evolutionar data about these proteins and the transport systems they comprise. It uses a successful system of classification based on transporter class, subclass, family, subfamily, individual transport systems and constituent proteins. In this competitive renewal of GM0077402, we propose to expand, update, automate and interlink TCDB. In particular, we will collaborate to integrate and unify the classification systems used by TCDB and Pfam with the formation of a TC ontological system. We will generate new data concerning transport proteins, and expand procedures for making functional predictions. This last effort will derive reliable new biological knowledge from a variety of sources, including phylogeny, motif, domain, operon and regulon analyses. Our Specific Aims are as follows: 1. To compare and evaluate methods of homology establishment, e.g., our and Pfam's statistical approaches, as well as introduce a system of protein repeat unit and domain identification. We will confirm and extend homology results based on structural superimpositions and profile: profile comparisons. We will develop and implement pipelines for the exchange of information between Pfam and TCDB and standardize both classification systems. 2. To incorporate our family descriptions into Wikipedia, to facilitate community annotation and interaction. Thus, we will add to Wikipedia, and integrate with Pfam to create a common platform for community annotation. 3. To create a substrate ontological framework for TCDB, using ChEBI and GO. 4. To use and automate multiple approaches, including phylogeny and synteny, to derive reliable functional predictions and provide guides for other researchers to do the same. 5. To utilize our TCDB advisory board for continued knowledgebase modernization and sustainability.