DEVELOPMENT AND APPLICATION OF A HIERARCHICAL PROTOCOL FOR AB INITIO PREDICTION

从头预测的分层协议的开发和应用

• 批准号: 8364243
• 负责人: HAROLD A. SCHERAGA
• 金额: $ 0.11万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8364243
• 关键词: Amino Acid Sequence; Bioinformatics; Biological Process; Biomedical Research; Cereals; Computational Biology; Development; Funding; Grant; High Performance Computing; Lead; Methodology; National Center for Research Resources; Pathway interactions; Physics; Principal Investigator; Property; Proteins; Protocols documentation; Research; Research Infrastructure; Resources; Source; Structure; Thermodynamics; United States National Institutes of Health; base; cost; molecular dynamics; protein structure; three dimensional structure

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Most of current research in computational biology an bioinformatics is focused on predicting the three-dimensional structure of proteins. Using different approaches, researches are trying to develop methodology for predicting proteins structure based only on amino acid sequence. However, three-dimensional structure alone is not sufficient to understand many biological processes which involve proteins. Research presented in this proposal is based on parameterization of our physics-based coarse-grained force-filed UNRES using information not only about the three dimensional structure of the native state of proteins but also about their folding mechanism and thermodynamic stability. We expect that such parameterization and extensive conformational space search using molecular dynamics enable us to simultaneously predict two protein properties: structure and thermodynamic stability of the native state and folding pathway(s) which lead from the unfolded to the folded state.

该子项目是利用资源的众多研究子项目之一 由 NIH/NCRR 资助的中心拨款提供。子项目的主要支持 并且子项目的主要研究者可能是由其他来源提供的， 包括其他 NIH 来源。 子项目可能列出的总成本 代表子项目使用的中心基础设施的估计数量， NCRR 赠款不直接向子项目或子项目工作人员提供资金。 目前计算生物学和生物信息学的大多数研究都集中在预测蛋白质的三维结构。研究人员正在尝试使用不同的方法开发仅基于氨基酸序列预测蛋白质结构的方法。然而，仅三维结构不足以理解涉及蛋白质的许多生物过程。本提案中提出的研究基于我们基于物理的粗粒度力场 UNRES 的参数化，不仅使用有关蛋白质天然状态的三维结构的信息，还使用有关其折叠机制和热力学稳定性的信息。我们期望使用分子动力学的这种参数化和广泛的构象空间搜索使我们能够同时预测两种蛋白质特性：天然状态的结构和热力学稳定性以及从展开状态到折叠状态的折叠途径。