Determination of solution structures by NMR

描述（由申请人提供）：该项目的主要目标是开发算法，使人们能够充分利用核磁共振数据来确定生物分子的溶液结构，以系统的方式评估其准确性和精度，并探索从核磁共振数据中提取动态信息的程度。这将涉及以下组件：更新的细化方法。将开发使用现代蛋白质和核酸力场与广义Born或显式溶剂化模型相结合的改进模型，并通过使用大分子部分的多个副本的“局部增强采样”模型纳入构象紊乱。蛋白质和核酸动力学研究。长时间尺度的分子动力学模拟将用于模拟核磁共振弛豫，并关注各向异性翻滚、内部和整体运动之间的相关性以及构象紊乱。这将包括分析内部运动对化学位移各向异性（CSA）弛豫和CSA-偶极交叉相关弛豫的贡献。弛豫色散实验揭示的较慢的微秒到毫秒的运动将使用新的模型来识别次要的构象并估计它们与其他构象的相互转换速率。最初的应用将是蛋白质G、核糖核酸酶A和二氢叶酸还原酶。核磁共振（NMR）光谱学为在活细胞等条件下探测蛋白质和核酸的特性提供了一个强大的工具。该项目使用计算工具来帮助从核磁共振中获得最多的信息，促进我们对健康和患病细胞的基本生化过程的理解。这里研究的两种蛋白质（核糖核酸酶和二氢叶酸还原酶）是癌症化疗的重要靶点。

DESCRIPTION (provided by applicant): The principal goals of this project are the development of algorithms that allow one to make the best use of NMR data to determine solution structures of biomolecules, to assess in a systematic fashion their accuracy and precision, and to explore the extent to which dynamical information can be extracted from NMR data. This will involve the following components: Updated refinement methods. Refinement models will be developed that use modern protein and nucleic acid force fields in combination with generalized Born or explicit solvation models, and which incorporate conformational disorder through the "locally enhanced sampling" model that uses multiple copies of portions of the macromolecule. Studies on protein and nucleic acid dynamics. Long-time scale molecular dynamics simulations will be used to model NMR relaxation, with attention paid to anisotropic tumbling, to the correlation between internal and overall motions, and to conformational disorder. This will include an analysis of contributions from internal motions to chemical shift anisotropy (CSA) relaxation and to CSA-dipolar cross-correlated relaxation. Slower, microsecond to millisecond motions uncovered by relaxation dispersion experiments will be studied using novel models to identify minor conformers and to estimate their rates of interconversion with other conformations. Initial applications will be to protein G, ribonuclease A, and dihydrofolate reducatase. Nuclear magnetic resonance (NMR) spectroscopy provides a powerful tool for probing the properties of proteins and nucleic acids under conditions like those in living cells. The project uses computational tools to help gain the most information from NMR, promoting our understanding of basic biochemical processes that underlie both healthy and diseased cells. Two of the proteins studied here (ribonuclease and dihydrofolate reductase) are important targets for cancer chemotherapy.