Automated NMR Assignment and Protein Structure Determination

描述（由申请人提供）：虽然自动化正在彻底改变生物学的许多方面，但三维（3D）蛋白质结构的测定仍然是一项长期，困难和昂贵的任务。为了在更大范围内应用基于结构的药物设计和结构蛋白质组学等现代技术，生物分子核磁共振的新算法和计算方法是必要的。传统的（半）自动化方法通过核磁共振光谱测定蛋白质结构需要大量的实验和大量的光谱仪时间，使其难以完全自动化。利用核磁共振技术确定三维蛋白质结构的主要瓶颈是生物聚合物中化学位移和核Overhauser效应（NOE）约束的分配。因此，我们提出了一个新的攻击分配问题，使高通量核磁共振结构确定。同样，仅使用稀疏数据很难准确地确定蛋白质结构。稀疏数据不仅出现在高通量环境中，也出现在较大的蛋白质、膜蛋白和对称蛋白质复合物中。新的算法将实现处理增加的光谱复杂性和稀疏的信息内容获得这样的困难的蛋白质。拟议的研究旨在尽量减少必须进行的核磁共振实验的数量和类型，以及解释实验结果所需的人力，同时仍然产生准确的蛋白质结构分析。我们项目的长期目标是解决核磁共振结构生物学中的关键计算瓶颈。在过去的拨款期间，我们报告了自动分配，蛋白质结构测定的新算法，蛋白质复合物和膜蛋白的表征以及仅使用未分配的NMR数据进行折叠识别的进展。我们将开发新的几何算法来改进和扩展这些技术，重点关注四个关键领域：(a)核矢量替换（NVR），一种类似分子替换的基于结构的赋值技术；(b)利用精确解和系统搜索从残余偶极偶联（rdc）中确定蛋白质结构的稀疏数据算法；(c)膜蛋白和复合物，特别是对称寡聚物的结构测定；(d)单体和配合物中NOE约束的自动分配。我们将开发和扩展上述软件工具，在一套集成程序自动折叠识别，分配，单体和寡聚物结构的确定。所有程序都将在实验核磁共振数据上进行测试，并使用我们的算法确定新的结构。

DESCRIPTION (provided by applicant): While automation is revolutionizing many aspects of biology, the determination of three-dimensional (3D) protein structure remains a long, hard, and expensive task. Novel algorithms and computational methods in biomolecular NMR are necessary to apply modern techniques such as structure-based drug design and structural proteomics on a much larger scale. Traditional (semi-) automated approaches to protein structure determination through NMR spectroscopy require a large number of experiments and substantial spectrometer time, making them dif - cult to fully automate. A chief bottleneck in the determination of 3D protein structures by NMR is the assignment of chemical shifts and nuclear Overhauser effect (NOE) restraints in a biopolymer. Therefore, we propose a novel attack on the assignment problem, to enable high-throughput NMR structure determination. Similarly, it is difficult to determine protein structures accurately using only sparse data. Sparse data arises not only in high-throughput settings, but also for larger proteins, membrane proteins, and symmetric protein complexes. New algorithms will be implemented to handle the increased spectral complexity and sparser information content obtained for such difficult proteins. The proposed research aims to minimize the number and types of NMR experiments that must be performed and the amount of human effort required to interpret the experimental results, while still producing an accurate analysis of the protein structure. The long-term goal of our project is to address key computational bottlenecks in NMR structural biology. In the past grant period, we have reported progress in automated assignments, novel algorithms for protein structure determination, characterization of protein complexes and membrane proteins, and fold recognition using only unassigned NMR data. We will develop novel geometric algorithms to improve and extend these techniques, focusing on four key areas: (a) Nuclear Vector Replacement (NVR), a molecular replacement-like technique for structure-based assignment; (b) sparse-data algorithms for protein structure determination from residual dipolar couplings (RDCs) using exact solutions and systematic search; (c) structure determination of membrane proteins and complexes, especially symmetric oligomers; and (d) automated assignment of NOE restraints in both monomers and complexes. We will develop and extend the software tools above in a set of integrated programs for automated fold recognition, assignment, monomeric and oligomeric structure determination. All programs will be tested on experimental NMR data, and new structures will be determined using our algorithms. Project Narrative While automation is revolutionizing many aspects of biology, the determination of three-dimensional protein structure remains a long, hard, and expensive task. Determination of protein structures by nuclear magnetic resonance (NMR) is valuable in many biomedical applications such as structure-based drug design. Since structural studies of proteins can not only provide clues to disease causes but also provide a basis for the rational design of therapeutic interventions, we propose novel algorithms and computational methods in biomolecular NMR, which are necessary to apply modern techniques such as structure-based drug design and structural proteomics on a much larger scale.