New methods for mixture analysis by liquid state NMR

核磁共振波谱是我们确定未知化合物化学结构的最佳工具。核磁共振每年鉴定出数十万种结构，但几乎都是纯化合物的稀溶液：核磁共振很难分析混合物，因为很难，通常是不可能区分光谱中的哪些信号来自哪些物种。与此同时，混合物位于化学和生物化学的核心，例如在植物提取物中寻找药物，理解化学反应-或者仅仅是找出一种葡萄酒比另一种味道更好的原因。混合物分析的一大挑战是代谢组学领域，该领域研究遗传构成、疾病、药物等对生物液中代谢物出现的影响。从复杂混合物的不同分子中分离出结构信息的能力是开发这一领域和许多其他领域的关键。分离、提纯和浓缩单个组分是繁琐、昂贵和耗时的；需要的是确定单个物种的结构的方法，而不是将混合物分离为其单独的组分。通过将核磁共振与分离方法相结合，可以直接从混合物中获得光谱信息。最常见的例子是LC-核磁共振，在这种情况下，核磁共振光谱仪被用作液体色谱(LC)的检测器。混合物的样品流经含有细粉的柱子，然后进入核磁共振仪器。不同的物种对柱材料的附着程度不同，因此它们在不同的时间出现，并依次测量每个物种的核磁共振谱。这种方法很强大，但它们在仪器、材料和专业知识上都很昂贵，而且它们很难处理少量的材料或非常复杂的混合物。目前用于完整混合物核磁共振研究的最有效的方法是扩散有序光谱(DOSY)，它根据不同物种的扩散速度来分离它们的信号。DOSY已经在许多分析领域证明了它的价值，包括食品化学、生物流体、结合研究等，但它的使用受到限制，因为它只有在不同物种的核磁共振信号不重叠的地方才能很好地工作。我建议通过开发一种新的技术，并使用到目前为止大部分还没有被开发用于核磁共振数据的强大的数学方法，来显著增强核磁共振在研究混合物方面的能力。我将应用目前在磁共振成像中用于测量血流的技术，直接测量不同分子流过色谱柱的速度如何受到它们与色谱柱内容物相互作用的影响。因为这种方法测量的是平均流速，而不是保留时间，所以混合物可以在闭合循环中连续泵送通过柱，因此，与LC-核磁共振相比，我们可以对同一样品重复测量，直到获得清晰的结果和良好的信噪比。因为我们在这里测量的运动是相干的，而不是在剂量测量中测量的非相干扩散，所以对实验结果的分析是直接的，并且避免了当信号重叠时DOSY遇到的困难。基本剂量实验给出的数据有两种不同的变化方式；相比之下，给出作为三个不同变量-三线性数据函数的结果的同情性不同的实验在分析时具有特殊的优势。我将研究使用DOSY对复杂混合物(例如，代谢组学中发现的混合物)的核磁共振谱进行三线性数据分析。这里的价值在于能够从可能包含数百个这样的光谱的背景中提取感兴趣的化合物的完整的核磁共振光谱，利用通过结合扩散和层析信息而获得的增加的分辨率

Nuclear magnetic resonance (NMR) spectroscopy is the best tool we have for determining the chemical structures of unknown compounds. Hundreds of thousands of structures are identified by NMR each year, but almost all as dilute solutions of pure compounds: NMR struggles to analyse mixtures because it is very difficult, often impossible, to tell which signals in the spectrum come from which species. At the same time, mixtures lie at the heart of chemistry and biochemistry, for example in the search for drugs in plant extracts, in understanding chemical reactions - or simply in finding out what makes one wine taste better than another. One big challenge in mixture analysis is the field of metabolomics, which studies the effects of genetic makeup, disease, drugs etc. on the occurrence of metabolites in biofluids. The ability to disentangle structural information from different molecules in complex mixtures is the key to exploiting this and many other fields. Isolation, purification and concentration of individual components are tedious, expensive and time-consuming; what is needed are ways of determining the structures of individual species without separating a mixture into its individual components. By combining NMR with separation methods, spectral information can be obtained directly from mixtures. The most common example of this is LC-NMR, in which an NMR spectrometer is used as the detector for liquid chromatography (LC). A sample of a mixture flows through a column containing a fine powder, and thence into an NMR instrument. Different species stick to the column material to different extents so they emerge at different times, and the NMR spectrum of each species in turn is measured. Such methods are powerful, but they are expensive in instrumentation, in materials, and in expertise, and they struggle to deal with small amounts of material or very complex mixtures. The most potent method in current use for NMR studies of intact mixtures is diffusion-ordered spectroscopy (DOSY), which separate the signals of different species according to how rapidly they diffuse. DOSY has proven its worth in many areas of analysis, including food chemistry, biofluids, binding studies etc., but its use is limited because it only works well where the NMR signals of different species do not overlap. I propose to try to enhance significantly the power of NMR in studying mixtures by developing a new technique and by using powerful mathematical methods so far largely unexploited for NMR data. I will apply techniques currently used to measure blood flow in magnetic resonance imaging to measure directly how the rates at which different molecules flow through a chromatography column are affected by their interactions with the contents of the column. Because this method measures mean flow velocity rather than retention time, the mixture can be pumped continuously through the column in a closed cycle so, in contrast to LC-NMR, we can make repeated measurements on the same sample for as long as it takes to get a clear result with good signal-to-noise ratio. Because the motion that we measure here is coherent, as opposed to the incoherent diffusion measured in DOSY, analysis of the experimental results is straightforward and avoids the difficulties that DOSY encounters when signals overlap. The basic DOSY experiment gives data which vary in two different ways; in contrast experiments that give results which vary in sympathy as a function of three different variables - trilinear data - have special advantages when it comes to analysis. I will investigate using DOSY to allow trilinear data analysis of the NMR spectra of complex mixtures (e.g. those found in metabolomics). The prize here is to be able to extract the complete NMR spectrum of a compound of interest from a background potentially containing many hundreds of such spectra, exploiting the added resolution gained by combining diffusion and chromatographic information