Protein Surface Mapping: Experimentation and Computation

蛋白质表面绘图：实验和计算

• 批准号: 7067112
• 负责人: ROBERT L. HETTICH
• 金额: $ 24.85万
• 依托单位: UT-BATTELLE, LLC-OAK RIDGE NATIONAL LAB
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2009-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7067112
• 关键词: aminoacid; chemical models; computer simulation; conformation; mass spectrometry; protein folding; protein structure; reagent /indicator; structural biology; technology /technique development

DESCRIPTION (provided by applicant): The proposed research is directed at demonstration of a protein surface mapping technique based on novel chemical labeling methods that can be combined with high resolution mass spectrometric characterization to identify surface accessible amino acids residues in native-folded proteins. This information then will be utilized in an integrated fashion with computational structural prediction methods to enhance their accuracies and throughput. If successful, this method could enhance dramatically the structural characterization throughput (albeit at moderate resolution) of a wide range of proteins, and provide critical input into the refinement of computational prediction methods. To achieve this goal, four specific aims are proposed. Specific Aim 1 focuses on formulation and characterization of an experimental surface mapping protocol that includes a toolbox of labeling reagents for protein structural determinations. We propose to optimize our radical labeling approach by defining the experimental parameters for quantitative labeling, background reduction, and alternate reagent development. The goal of this task will be to develop an experimental toolbox for labeling that includes a variety of reagents. Specific Aim 2 is directed toward demonstration of the surface mapping technique for large proteins and protein mixtures, two areas that are difficult for XRC and NMR techniques to examine. Specific Aim 3 involves demonstration of the surface mapping technique for characterizing protein conformational changes, to illustrate how this experimental approach can provide more than only low resolution structural information. Specific Aim 4 seeks to integrate surface mapping data as experimental constraints for computational protein structural prediction, involving both protein threading algorithms (PROSPECT) and ab initio methods (Rosetta). One favorable outcome if the proposed experimental approach is successful is the large amount of structural data at moderate resolution that can be generated from protein mixtures. At present, this experimental capability is non-existent.

描述（由申请人提供）：拟议的研究旨在演示基于新型化学标记方法的蛋白质表面绘图技术，该技术可以与高分辨率质谱表征相结合，以识别天然折叠蛋白质中表面可接近的氨基酸残基。然后，这些信息将与计算结构预测方法以集成的方式加以利用，以提高其准确性和吞吐量。如果成功，该方法可以显著提高多种蛋白质的结构表征吞吐量（尽管在中等分辨率下），并为改进计算预测方法提供关键输入。为实现这一目标，提出了四个具体目标。具体目标1侧重于制定和表征一个实验表面制图方案，包括一个工具箱的标记试剂的蛋白质结构测定。我们建议通过定义定量标记、背景还原和替代试剂开发的实验参数来优化我们的自由基标记方法。这项任务的目标将是开发一个实验工具箱，用于标记，包括各种试剂。具体目标2旨在演示大蛋白质和蛋白质混合物的表面制图技术，这两个领域是XRC和NMR技术难以检测的。具体目标3涉及表征蛋白质构象变化的表面映射技术的演示，以说明这种实验方法如何提供不仅仅是低分辨率结构信息。Specific Aim 4旨在整合表面映射数据作为计算蛋白质结构预测的实验约束，包括蛋白质线程算法（PROSPECT）和从头算方法（Rosetta）。如果提出的实验方法成功，一个有利的结果是可以从蛋白质混合物中产生大量中等分辨率的结构数据。目前，这种实验能力还不存在。