Ab Initio Structure Prediction of Quaternary Proteins

四元蛋白质的从头开始结构预测

• 批准号: 6857127
• 负责人: HEATHER D SCHAFROTH
• 金额: $ 1.99万
• 依托单位: CORNELL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-03-10 至 2005-08-01
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6857127
• 关键词: amyloid proteins; carbon nitrogen ligase; chemical reaction; conformation; energy source; molecular dynamics; p53 gene /protein; postdoctoral investigator; protein folding; protein protein interaction; protein sequence; protein structure function; quantum chemistry

DESCRIPTION (provided by applicant): Structure prediction of quaternary, or multi-chain, proteins using ab initio methods is a promising approach to determining how proteins fold into their native conformations. Computational structure prediction from protein sequences is critical because many quaternary proteins involved in cancer and other diseases have known sequences but structures, and thus possible biological mechanisms that are undetermined. Unlike knowledge-based methods such as homology modeling and threading, ab initio physics-based methods predict the structure of a protein from its sequence alone by finding the global minimum of a potential energy function describing the protein's interatomic interactions. The objectives of the proposed research are to incorporate innovative quaternary-specific protein representations and conformational searches into the ab initio hierarchical protein structure prediction procedure developed by Scheraga and co-workers, and to assess these new approaches in a series of test cases. Successful quaternary structure predictions would demonstrate understanding of how interatomic interactions determine structure and provide the opportunity to apply this understanding to applications such as drug design and other biological and health-related challenges.

描述(由申请人提供)：使用从头算方法预测四元或多链蛋白质的结构是确定蛋白质如何折叠成其天然构象的一种有前途的方法。蛋白质序列的计算结构预测是至关重要的，因为许多与癌症和其他疾病有关的四元蛋白质具有已知的序列但结构，因此可能的生物机制尚不确定。与同源建模和线索分析等基于知识的方法不同，基于从头算物理的方法通过寻找描述蛋白质原子间相互作用的势能函数的全局极小值，仅根据蛋白质的序列预测蛋白质的结构。这项拟议研究的目标是将创新的特定于四元组的蛋白质表示和构象搜索纳入Scheraga及其同事开发的从头算分层蛋白质结构预测程序中，并在一系列测试案例中评估这些新方法。成功的四级结构预测将展示对原子间相互作用如何确定结构的理解，并提供将这种理解应用于药物设计和其他与生物和健康有关的挑战的机会。