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: 7934418
• 负责人: Rafael Bruschweiler
• 金额: $ 6.18万
• 依托单位: FLORIDA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7934418
• 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; 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; public health relevance; 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（由申请人提供）：本研究的总体目标是开发和应用新的核磁共振（NMR）方法和基于网络的技术，用于快速可靠地收集、处理和分析大小生物分子的NMR光谱。在上一个资助期开发的协方差NMR光谱学的原理将扩展到更高维的光谱学，包括GFT和投影重建NMR，以获得沿着间接维度的光谱分辨率的大幅增加，并实现蛋白质主链和侧链共振的自动分配。将为新的4D NOESY方案开发基于协方差的分辨率增强方法，以增加短距离和长距离NMR距离约束的数量，包括确定高质量蛋白质结构所需的立体特异性分配。协方差NMR和其他矩阵为基础的方法分析复杂的代谢物混合物将开发获得定量信息的混合物成分，不提供其他方法，对自动化的高通量指纹图谱和分析的目标在新兴的代谢组学领域。这些方法将通过一套相互连接的网络服务器提供给广大用户。公共卫生相关性：先进的协方差NMR方法能够有效分配共振和提取更好的距离信息，以准确测定蛋白质结构。这些是理解蛋白质功能和蛋白质-配体相互作用以开发新的和更好的药物的先决条件。新的基于NMR的代谢组学工具提供有关细胞、组织和生物流体化学的全面信息。它们将为疾病和治疗提供新的视角，并将引领个性化医疗。