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运输系统的序列、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的基础上运输类，子类，家庭，亚科，和个人的运输。 在GM0077402的竞争性更新中，我们建议扩大和深化我们的努力，以扩展、更新、自动化和互连TCDB。我们将生成有关转运蛋白的新数据，设计新的数据机器学习方法，并介绍对未表征转运蛋白进行功能预测的程序。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.开发自动文本挖掘和信息提取软件。 2.进行生物信息学分析和分子生物学实验，拓展TC知识。 3.将TCDB与其他相关数据库双向互连，从而从现有的“孤岛”数据库中创建一个知识“网络”。 4.使用多种方法获得可靠的功能预测，作为未来研究的指导。 5.利用新成立的TCDB咨询委员会，制定现代化和可持续性计划。这些目标是使TCDB对科学界越来越有用的最高优先事项。 公共卫生相关性：TCDB是一个数据库，为全球科学界提供有关催化盐、营养素、毒素、药物和大分子跨膜转运的蛋白质的系统化信息。它是IUBMB批准的唯一用于分类转运蛋白的系统。该提案的资金将允许TCDB的维护和进一步发展，与相关数据库的互连，扩大信息获取的机器学习方法，并引入预测未知蛋白质功能的方法。

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 evolutionary data about these proteins and the transport systems they comprise. It uses a successful system of classification based on transporter class, subclass, family, subfamily, and individual transporter. In this competitive renewal of GM0077402, we propose to broaden and deepen our efforts to expand, update, automate and interlink TCDB. We will generate new data concerning transport proteins, design new machine learning approaches for data, and introduce procedures for making functional predictions of uncharacterized transporters. 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 develop software for automatic text mining and information extraction. 2. To conduct bioinformatic analyses and molecular biological experiments for TC knowledge expansion. 3. To interconnect TCDB bidirectionally with other relevant databases, thereby creating a "network" of knowledge from current "island" databases. 4. To use multiple approaches to derive reliable functional predictions as guides for future research. 5. To utilize a newly formed TCDB advisory board and establish a plan for modernization and sustainability. These goals are top priorities for rendering TCDB increasingly useful to the scientific community. PUBLIC HEALTH RELEVANCE: TCDB is a database providing the worldwide scientific community with systematized information about proteins that catalyze transmembrane transport of salts, nutrients, toxins, drugs and macromolecules. It is the only IUBMB approved system for classifying transport proteins. Funding of this proposal will allow the maintenance and further development of TCDB, interlinking with related databases, expansion of machine learning approaches for information acquisition, and introduction of approaches for predicting the functions of uncharacterized proteins.