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

项目总结 从历史上看，对天然产品的调查一直是极具挑战性的。 由于大多数天然产品来源的复杂性。试图准确地 描述这些样本的复杂结构仍然是一个挑战，尽管 分析技术的进步。尽管不存在单一的过程来 解决这个问题，来自正交技术的数据组合可以 组合在一起以改进混合的批注。利用核磁共振作为分析手段 平台上，开发了一种集成来自 HSQC和TOCSY实验，使自旋系统功能得以构建 可用于标识和描述 混合物。使用这种方法，有可能将相关的组成部分连接到 多个样本以可视化要素之间的关系，有助于进一步 假设驱动的调查。从代谢组学的角度看这一问题 透视利用已有的天然产品工作流， 可能会导致大量来源生物体的收集。进一步评估 这些网络中，有希望以足够准确的方式描述组件 详细信息，不仅跟踪它们在提取物中的流行情况，而且提供 调查人员有足够的细节来了解分子支架和结构 这些代谢物在广泛的层析分离之前的特征。 该提案中包含的未来工作和应用程序旨在将 由该核磁共振系统提供的结构信息用于结构确定 其他分析平台中的现象，主要是MS。 好了！ 好了！

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. ! !