Covariance-based NMR of Proteins and Complex Metabolite Mixtures

基于协方差的蛋白质和复杂代谢物混合物的 NMR

• 批准号: 8061968
• 负责人: Rafael Bruschweiler
• 金额: $ 25.3万
• 依托单位: FLORIDA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2013-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8061968
• 关键词: Algorithms; Antineoplastic Agents; Cancer cell line; Carbon; Cells; Chemicals; Chemistry; Collection; Complex; Computer software; Databases; Development; Dimensions; Disease; Evolution; Fingerprint; Funding; Goals; Health; Human; Internet; Lead; Ligands; Medicine; Metabolic; Methods; Monitor; NMR Spectroscopy; NOESY; Nuclear Magnetic Resonance; Online Systems; Pharmaceutical Preparations; Process; Property; Proteins; Research; Resolution; Sampling; Scheme; Screening procedure; Side; Spectrum Analysis; Structure; System; Technology; Testing; Tissues; Vertebral column; base; design; improved; metabolomics; novel; protein complex; protein function; protein structure; reconstruction; research study; response; small molecule; tool

DESCRIPTION (provided by applicant): The overall objectives of this research are to develop and apply new nuclear magnetic resonance (NMR) methods and web-based technology for the rapid and reliable collection, processing, and analysis of NMR spectra of large and small biomolecules. The principles of Covariance NMR Spectroscopy, developed in the previous funding period, will be extended to higher dimensional spectroscopy, including GFT and projection reconstruction NMR, in order to gain substantial increase in spectral resolution along indirect dimensions and to enable the automated assignment of backbone and side-chain resonances of proteins. Covariance-based resolution enhancement methods will be developed for new 4D NOESY-schemes to increase the number of short- and long-range NMR distance constraints, including stereo-specific assignments, necessary for the determination of high-quality protein structures. Covariance NMR and other matrix-based methods for the analysis of complex metabolite mixtures will be developed to obtain quantitative information on the mixture components, not available by other methods, with the goal toward automated high-throughput fingerprinting and profiling in the emerging field of metabolomics. The methods will be made available to a broad range of users through a suite of interconnected web servers. PUBLIC HEALTH RELEVANCE: Advanced covariance NMR methods enable the efficient assignment of resonances and the extraction of better distance information for the accurate determination of protein structures. These are a prerequisite for understanding protein function and protein-ligand interactions for the development of new and better drugs. New NMR-based metabolomics tools provide comprehensive information about the chemistry of cells, tissues, and biofluids. They will provide a new perspective on disease and treatment and will lead the way to personalized medicine.

描述(申请人提供)：本研究的总体目标是开发和应用新的核磁共振方法和基于网络的技术，以快速和可靠地收集、处理和分析大小生物分子的核磁共振谱。协方差核磁共振波谱的原理是在前一个资助期发展起来的，它将扩展到更高维的波谱，包括GFT和投影重建核磁共振，以获得沿间接维度的光谱分辨率的大幅提高，并能够自动指定蛋白质的主链和侧链共振。基于协方差的分辨率增强方法将被开发用于新的4D NOESY方案，以增加确定高质量蛋白质结构所必需的短程和长程核磁共振距离约束的数量，包括立体特定分配。将开发用于分析复杂代谢物混合物的协方差核磁共振和其他基于矩阵的方法，以获得关于混合物成分的定量信息，这是其他方法无法获得的，目标是在新兴的代谢组学领域实现自动化的高通量指纹和图谱分析。这些方法将通过一套互连的网络服务器提供给广泛的用户。公共卫生相关性：先进的协方差核磁共振方法能够有效地分配共振并提取更好的距离信息，以准确确定蛋白质结构。这些都是了解蛋白质功能和蛋白质-配体相互作用的先决条件，有助于开发新的和更好的药物。新的基于核磁共振的代谢组学工具提供了关于细胞、组织和生物体液化学的全面信息。它们将为疾病和治疗提供一个新的视角，并将引领个性化医疗的道路。