Integrated Resource for Protein Recognition Studies

蛋白质识别研究综合资源

• 批准号: 8735154
• 负责人: ILYA VAKSER
• 金额: $ 28.62万
• 依托单位: UNIVERSITY OF KANSAS LAWRENCE
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8735154
• 关键词: Accounting; Benchmarking; Biology; Cereals; Communities; Complex; Computational Technique; Computer Assisted; Computer Simulation; Computer software; Data; Data Set; Databases; Development; Disease; Docking; Drug Design; Drug Targeting; Environment; Feedback; Genome; Goals; Imagery; Individual; Internet; Kinetics; Knowledge; Left; Libraries; Life; Medicine; Methodology; Methods; Modeling; Molecular; Molecular Structure; Online Systems; Outcome; Play; Probability; Procedures; Process; Property; Protein Databases; Proteins; Research; Resource Development; Resources; Role; Sampling; Simulate; Source; Structural Models; Structure; System; Techniques; Testing; Update; base; conformational conversion; flexibility; genome wide association study; genome-wide; improved; insight; model development; protein complex; protein protein interaction; protein structure; public health relevance; rapid growth; reconstruction; structural biology; structural genomics; three dimensional structure; tool; user-friendly

DESCRIPTION (provided by applicant): The protein-protein docking problem is one of the focal points of activity in computational structural biology. The 3D structure of a protein-protein complex, generally, is more difficult to determine experimentally than the structure of an individual protein. Adequate computational techniques to model protein interactions are important because of the growing number of known protein 3D structures, particularly in the context of structural genomics. The project will improve our understanding of fundamental properties of protein interaction and will facilitate development of better tools for prediction of protein complexes. The Specific Aims of the project are: (1) Protein recognition data resources, (2) Advanced docking methodology, and (3) Integrated web-based environment. The long-term goals are: (a) development of an automated tool for a reliable modeling of protein interactions, which will account for dynamic changes in the molecular structures and kinetics of protein association and (b) utilization of this tool to understand principles of protein interaction. The ultimate goal is to recreate the network of protein interactions in genomes and understand the structure-base mechanisms of these interactions. The systematic, detailed description of these interactions will provide insights into the basic principles of life processes at the molecular levl. The focus of the proposal is an integrated system of resources for studying protein-protein 3D interactions. The core dataset consists of regularly updated and annotated co-crystallized protein-protein structures. The database of experimentally determined and simulated unbound complexes will be further expanded upon the core dataset. It will serve as a comprehensive benchmark set for the development of docking techniques. The database of complexes of protein models will provide a unique expansion of the core dataset for the development of docking capabilities in protein modeling, including genome-wide studies. The docking decoys will provide the community-wide testing ground for new scoring functions. The docking procedure will be developed further to make it more adequate to the challenges of structural modeling of protein-protein complexes. The development will make use of the rapidly growing body of experimentally determined structures of protein-protein complexes. The docking methods will utilize available knowledge on the protein targets, combined with the improved use of structural and physicochemical recognition factors. Coarse-graining of the docking in terms of structural representation, energy function, and sampling will be systematically explored, making use of the interface rotamer libraries and probabilities of conformational transitions. The docking procedure and the related databases will continue to be provided as a web-based public resource.

描述（由申请人提供）：蛋白质 - 蛋白质对接问题是计算结构生物学活动的焦点之一。蛋白质蛋白的3D结构 通常，比单个蛋白质的结构更难在实验上确定复合物。建模蛋白质相互作用的足够计算技术很重要，因为已知的蛋白质3D结构数量越来越大，特别是在结构基因组学的背景下。该项目将提高我们对蛋白质相互作用的基本特性的理解，并将促进开发更好的工具以预测 蛋白质复合物。该项目的具体目的是：（1）蛋白质识别数据资源，（2）高级对接方法和（3）基于Web的集成环境。长期目标是：（a）开发自动化工具，用于对蛋白质相互作用的可靠建模，这将解释分子结构的动态变化和蛋白质关联的动力学，以及（b）利用该工具来了解蛋白质相互作用的原理。最终目标是重现基因组中蛋白质相互作用的网络，并了解这些相互作用的结构基机制。这些相互作用的系统，详细的描述将为分子LEVL生命过程的基本原理提供见解。该提案的重点是用于研究蛋白质 - 蛋白质3D相互作用的集成资源系统。 核心数据集由定期更新和注释的共结晶蛋白 - 蛋白质结构组成。实验确定和模拟未结合复合物的数据库将进一步扩展到核心数据集上。它将作为开发对接技术的全面基准设置。蛋白质模型复合物的数据库将为核心数据集提供独特的扩展，以开发蛋白质建模中的对接功能，包括全基因组研究。对接诱饵将为新的得分功能提供社区范围内的测试场。将进一步制定对接程序，以使其更加应对蛋白质蛋白质复合物的结构建模的挑战。该发展将利用蛋白质蛋白质复合物的实验确定结构的快速生长体。对接方法将利用有关蛋白质靶标的可用知识，并改善使用结构和物理化学识别因素。将系统地探索扩展坞的粗粒，以结构表示，能量函数和采样，利用界面rotamer库和构象转变的概率。对接 过程和相关数据库将继续作为基于Web的公共资源提供。