SCOP: A Revitalized Foundation for Studies of Protein Structure and Evolution

SCOP：蛋白质结构和进化研究的复兴基础

• 批准号: 8260234
• 负责人: John-Marc Chandonia
• 金额: $ 34.4万
• 依托单位: UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-23 至 2014-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8260234
• 关键词: Accounting; Algorithms; Benchmarking; Biological; Biology; Classification; Collection; Communities; Complex; Computer software; Data; Data Analyses; Data Storage and Retrieval; Databases; Evolution; Family; Floods; Foundations; Goals; Gold; Homologous Protein; Internet; Link; Manuals; Medical; Mutation; Procedures; Process; Protein Databases; Protein Family; Proteins; Publications; Published Comment; Recording of previous events; Research; Resources; Scientist; Side; Speed; Structural Biologist; Structure; System; Technology; Tertiary Protein Structure; Testing; Time; abstracting; base; database structure; design; flexibility; human disease; insight; interest; meetings; open source; pathogen; protein structure; public health relevance; tool; web interface; web site

DESCRIPTION (provided by applicant): Project Summary/Abstract The primary goal of this project will be to revitalize the Structural Classification of Proteins (SCOP) and ASTRAL databases, both in order to better serve the needs of both current users and the larger scientific community. Both databases provide carefully curated resources that are widely used by biologists to explore remote homologs of proteins of interest, and by computational biologists as a "gold standard" for benchmarking prediction algorithms. However, neither database has changed its basic design since early releases-15 years ago in the case of SCOP. We will redesign the internals of both databases in order to account for aspects of protein evolution that were not appreciated at the time the databases were first created, such as metamorphic proteins and homologous proteins that have evolved different folds. We will also develop a unified interface to both databases that will allow scientists to easily find and focus on proteins or families of interest, as the current hierarchical view is increasingly unwieldy as more structures are added. Since the process of SCOP curation has become a bottleneck due to the large number of structures being solved today, we plan to build automated tools to assist in the classification. We will also create interfaces to allow biologists to submit sequences or structures for automated classification using the latter tools. In many cases, this would enable structural biologists to gain insight into a protein's evolution or function prior to publication of a newly solved structure. PUBLIC HEALTH RELEVANCE: PROJECT NARRATIVE The SCOP and ASTRAL databases are carefully curated resources that are widely used by biologists to explore the structure, function, and evolution of protein families of interest, and by computational biologists as a "gold standard" for benchmarking prediction algorithms. Protein structures are essential to many modern studies of pathogens and human diseases, and medical conditions are being rapidly linked to specific mutations. Although the flood of structural information threatens to overwhelm our current capacity for analysis, our proposed changes to the curation procedures for SCOP and ASTRAL, and improvements to the underlying structure of the databases, will allow these resources to continue to yield biological and medical insight for many years to come.

该项目的主要目标是振兴蛋白质结构分类（SCOP）和ASTRAL数据库，以便更好地满足当前用户和更大的科学界的需求。这两个数据库都提供了精心策划的资源，被生物学家广泛用于探索感兴趣的蛋白质的远程同源物，并被计算生物学家用作基准预测算法的“黄金标准”。然而，这两个数据库都没有改变它的基本设计，因为早期版本-15年前的SCOP的情况。我们将重新设计这两个数据库的内部结构，以解释蛋白质进化的一些方面，这些方面在数据库最初创建时没有得到重视，例如变形蛋白和进化出不同折叠的同源蛋白。我们还将开发两个数据库的统一界面，使科学家能够轻松找到并专注于感兴趣的蛋白质或家族，因为随着更多结构的添加，当前的分层视图越来越难以操作。由于SCOP策展的过程已经成为一个瓶颈，由于大量的结构正在解决今天，我们计划建立自动化工具，以协助分类。我们还将创建接口，允许生物学家使用后者的工具提交序列或结构进行自动分类。在许多情况下，这将使结构生物学家能够在发表新解决的结构之前深入了解蛋白质的进化或功能。 公共卫生相关性： SCOP和ASTRAL数据库是精心策划的资源，被生物学家广泛用于探索感兴趣的蛋白质家族的结构，功能和进化，并被计算生物学家用作基准预测算法的“黄金标准”。蛋白质结构对于病原体和人类疾病的许多现代研究至关重要，并且医学状况正在迅速与特定突变联系起来。尽管大量的结构信息可能会压倒我们目前的分析能力，但我们对SCOP和ASTRAL的策展程序提出的修改，以及对数据库底层结构的改进，将使这些资源在未来许多年内继续产生生物学和医学见解。