An Untargeted NMR Metabolomics Platform for Functional Annotation of Natural Product Extracts.

项目摘要 从历史上看，对天然产物的研究一直极具挑战性 由于大多数天然产物来源的复杂性。试图准确地 描述复杂的这些样品的构成仍然是一个挑战，尽管 分析技术的进步。虽然没有单一的过程存在， 为了解决这个问题，来自正交技术的数据的组合可以被 组合以改进混合物的注释。利用NMR作为分析 平台，开发了一种方法，将正交信息从 HSQC和TOCSY实验，实现自旋系统特征的构建 可用于识别和描述单个成分， 混合物.使用这种方法，可以将相关的组成部分网络化， 多个样本以可视化特征的关系 假设驱动的调查。从代谢组学的角度探讨这个问题 Perspective利用了现有的自然产品工作流程， 可能导致大量的源生物的集合。进一步评价 这些网络中的大多数在足够精确地描述组件方面表现出了希望， 详细信息，不仅可以跟踪其在提取物中的流行程度，还可以提供 研究人员有足够的细节来了解分子支架和结构 这些代谢物的特征在广泛的色谱分离之前。 本提案中包括的未来努力和应用旨在将 由该NMR系统提供的结构信息， 其他分析平台中的现象，主要是MS。 ! !

PROJECT SUMMARY Investigations of natural products have, historically, been extremely challenging due to the complexity of most natural product sources. Attempts at accurately describing the constitution of complex these samples remains a challenge, despite advancements in analytical technologies. Although no singular process exists to solve this issue, combinations of data from orthogonal techniques can be combined to improve the annotation of a mixture. Utilizing NMR as an analytical platform, an approach was developed that integrates orthogonal information from HSQC and TOCSY experiments, enabling the construction of spin system features that can be used for identification and description of individual constituents in a mixture. Using this approach, it is possible to network related constituents across multiple samples to visualize relationships of the features aiding in further hypothesis driven investigations. Approaching this problem from a metabolomics perspective takes advantage of already existing natural product workflows that may result in a large number of collections of source organisms. Further evaluation of these networks show promise in accurately describing components in enough detail to not only track their prevalence across extracts, but provide the investigators with enough detail to know the molecular scaffold and structural features of these metabolites prior to extensive chromatographic separation. Future efforts and applications included in this proposal aim to connect the structural information afforded by this NMR system to structurally determined phenomena in other analytical platforms, predominantly with MS. ! !