Maximum Entropy Deconvolution for Resolution & Sensitivity Enhancement in Bio-NMR

分辨率的最大熵反卷积

• 批准号: 8570412
• 负责人: JEFFREY C HOCH
• 金额: $ 23.85万
• 依托单位: UNIVERSITY OF CONNECTICUT SCH OF MED/DNT
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8570412
• 关键词: Biomolecular Nuclear Magnetic Resonance; Cells; Collection; Communities; Data; Data Set; Dimensions; Entropy; Fourier Transform; Housing; In Situ; Methods; Molecular Structure; NMR Spectroscopy; NOESY; Nuclear; Nuclear Magnetic Resonance; Performance; Physiologic pulse; Process; Proteins; Reporting; Resolution; Sampling; Solutions; Spectrum Analysis; Structure; Surveys; System; Testing; Twin Multiple Birth; Validation; base; computerized data processing; drug candidate; drug discovery; improved; instrument; instrumentation; magnetic field; metabolomics; public health relevance; reconstruction; research study; screening; structural biology; tool

DESCRIPTION (provided by applicant): Nuclear magnetic resonance (NMR) spectroscopy is one of the most versatile tools available for probing biomolecular structure, dynamics, and interactions. It is the only method capable of determining molecular structure in solution at atomic resolution, and it has a host of important biomedical applications, including screening potential drug candidates and quantifying metabolites in biofluids or intact cells. Sensitivity and resolution present twin challenges in biomolecular NMR. Both are improved by performing experiments at the highest attainable magnetic field, on instruments that can be staggeringly expensive. Signal processing methods have also long been used in NMR to enhance sensitivity and resolution to the fullest possible extent. Linear methods of signal processing based on the Fourier transform invariably encounter a sensitivity/resolution tradeoff, where one can be enhanced at the expense of the other, but both cannot be simultaneously optimized. Nonlinear methods of spectrum analysis can in some cases avoid this tradeoff, and simultaneously improve both sensitivity and resolution. Anecdotal examples of simultaneously improving sensitivity and resolution in one dimension using maximum entropy deconvolution have been reported, but the gains achieved with this approach are typically modest. In this project we will develop methods for employing maximum entropy to simultaneously deconvolve two or more dimensions to enhance sensitivity and resolution. Preliminary data indicate the resulting gains in sensitivity and resolution are substantially increased compared to one-dimensional deconvolution, and are comparable to the gains associated with collecting data at much higher magnetic field.

描述(申请人提供)：核磁共振(核磁共振)光谱学是可用于探测生物分子结构、动力学和相互作用的最通用工具之一。它是唯一能够在原子分辨率下确定溶液中分子结构的方法，它在生物医学上有许多重要的应用，包括筛选潜在的候选药物和定量生物液或完整细胞中的代谢物。敏感性和 在生物分子核磁共振中，分辨提出了双重挑战。通过在昂贵得令人震惊的仪器上进行实验，在可获得的最高磁场下进行实验，两者都得到了改进。信号处理方法也一直被用于核磁共振中，以最大限度地提高灵敏度和分辨率。基于傅里叶变换的线性信号处理方法总是会遇到灵敏度/分辨率的折衷，其中一个可以以牺牲另一个为代价来增强，但两者都不能同时优化。非线性频谱分析方法在某些情况下可以避免这种权衡，同时提高灵敏度和分辨率。已经报道了使用最大熵反褶积同时提高一维灵敏度和分辨率的轶事例子，但这种方法所获得的收益通常不大。在这个项目中，我们将开发使用最大熵来同时对两个或更多个维度进行去卷积的方法，以提高灵敏度和分辨率。初步数据表明，与一维反褶积相比，由此产生的灵敏度和分辨率的增益大大提高，与在高得多的磁场下收集数据所产生的增益相当。