DEVELOPMENT OF AN IN-HOUSE PROTON SPIN NETWORK DATABASE TO CHARACTERIZE THE PHARMACOPHORES OF CENTELLA ASIATICA FOR STANDARDIZATION AND QUALITY CONTROL

项目总结 膳食补充剂(DS)的好处，包括植物性药物，都有很好的记录，因为它们被 约占美国成年人口的一半。出于安全和批次间一致性的目的， 必须进行植物来源DS的化学成分的鉴定和表征，尽管 混合物的复杂性和许多组成成分可能的活性贡献使 这项任务具有挑战性。基于液-质联用(LC-MS)的方法是 迄今在鉴定和表征植物学中已知的生物活性化合物方面最可靠的 DS.更可靠和更新的质谱学数据库和方法，以及新的 然而，仍然需要补充的方法来快速鉴定代谢物、活性 一致性和批次间质量控制。核磁共振波谱学长期以来一直与质量一起使用 光谱学在天然产物代谢组谱和明确确定有机化合物结构中的应用 化合物。然而，在许多基于核磁共振的代谢组学研究中，大多数图谱只关注可识别的(或 已知)主要化合物，留下了对复杂混合物产生的重叠信号的识别 化合物的使用是主要的挑战。此外，纯正的标准化合物显示质子和碳。 具有化学位移的信号与混合物和这些化学物质中的相同化合物的信号略有不同 位移差异使得基于核磁共振的代谢组学即使不是不准确，也是困难的。尽管如此，形状和 由于自旋网络中的耦合质子引起的信号分裂保持不变，尽管混合增强了 共振发生了变化。这些不变的自旋网络特征可以通过选择性的一维 TOCSY(S1DT)实验，它使用的脉冲序列显示信号灵敏度增加，特别是在 使用高场强核磁共振和高扫描次数。此外，许多同分异构体在 大多数MS分析可以使用其S1DT指纹生成的特征自旋网络进行区分。我们的 总体目标是将识别的S1DT指纹信息与现有的质谱学数据相结合 关于积雪草的信息目前可在BENFRA植物膳食补充剂中获得 研究中心(NIH/NCCIH U19 AT010829)和在本研究期间分离到的化合物的那些 补充LC-MS用于批次到批次的质量控制和活动一致性。目标1--全面 非靶向分离将提供参考标准化合物和一个强大的LC-MS数据库，该数据库将 用于该中心和其他研究社区的识别和标准化研究 在研究亚洲绒毛虫。此外，S1DT的新应用将有助于准确识别 用~1H自旋网络指纹图谱比较化学成分及其潜在的药效团 在分离出的化合物中与从萃取物的~1H核磁共振谱中得到的化合物进行鉴定 在目标2中开发。

PROJECT SUMMARY The benefits of dietary supplements (DS) including botanicals are well documented as they are consumed by about half of the adult population of the United States. For safety and batch-to batch consistency purposes, the identification and characterization of chemical constituents of DS of plant origin have to be performed although the complexity of the mixture and the possible activity contributions of many of the constituting components make the task challenging. Liquid chromatography coupled with mass spectrometry (LC-MS)-based methods are the most reliable so far in the identification and characterization of already known bioactive compounds in a botanical DS. More reliable and updated mass spectrometric databases and methodologies as well as new complementary methods are, however, still needed for rapid metabolite identification, activity consistency, and batch-to-batch quality controls. NMR spectroscopy has long been used with mass spectrometry in metabolomics profiling of natural products and to determine unambiguously structures of organic compounds. Most profiling in many NMR-based metabolomics studies, however, focus only on identifiable (or already known) major compounds, leaving the identification of overlapping signals arising from complex mixture of compounds as major challenges. Furthermore, pure authentic standard compounds display proton and carbon signals with chemical shifts slightly different from those of the same compounds in a mixture and these chemical shift differences make NMR-based metabolomics difficult if not inaccurate. Nevertheless, the shape and the splitting of the signals due to coupled protons in spin networks remain the same, despite mixture-enhanced resonance shifts. These unchanged spin network characteristics can be identified by selective one-dimensional TOCSY (S1DT) experiments, which use pulse sequences that show signal sensitivity increase especially when high-field strength NMR and high number of scans are used. Moreover, many isomers that are undiscernible in most MS analyses can be differentiated using their S1DT fingerprint generated characteristic spin networks. Our overall goal is to couple the identified S1DT fingerprint information with the existing mass spectrometric data information on Centella asiatica (gotu kola) at currently available at BENFRA Botanical Dietary Supplements Research Center (NIH/NCCIH U19 AT010829) and those of compounds isolated during the present study to complement LC-MS for batch-to batch quality control and activity consistencies. Aim 1 on comprehensive untargeted isolation will afford reference standard compounds and a robust LC-MS database that will be used for identification and standardization studies at the center and other research communities working on C. asiatica. In addition, a new application of S1DT that will help to accurately identify chemical constituents and their potential pharmacophores by comparing 1H spin network fingerprints identified in the isolated compounds with those derived from the 1H NMR spectra of the extract will be developed in Aim 2.