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

开发内部质子自旋网络数据库来表征积雪草药效团，以实现标准化和质量控制

• 批准号: 10706478
• 负责人: Liva Harinantenaina Rakotondraibe
• 金额: $ 7.88万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-19 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10706478
• 关键词: Acids; Adult; Aging; Alzheimer' s Disease; Amino Acids; Antioxidants; Apiaceae; Biological; Biological Markers; Botanical dietary supplements; Botanicals; Carbon; Cell Nucleus; Characteristics; Chemicals; Cognition Disorders; Communities; Complement; Complex Mixtures; Consumption; Coupled; Coupling; Data; Databases; Development; Drug Kinetics; Engineering; Equipment; Face; Family; Feasibility Studies; Fingerprint; Funding; Goals; Gotu kola; Individual; Isomerism; Liquid Chromatography; Machine Learning; Manuals; Mass Spectrum Analysis; Metabolic; Methodology; Methods; Minor; Modeling; NMR Spectroscopy; National Center for Complementary and Integrative Health; Natural Products; Neurologic; Nuclear Magnetic Resonance; Ohio; Oxidative Stress; Physiologic pulse; Plants; Population; Procedures; Protons; Quality Control; Reference Standards; Reporting; Research; Safety; Sampling; Scanning; Shapes; Signal Transduction; Spectrum Analysis; Standardization; Structure; TOCSY; Techniques; Technology; Terpenes; United States; United States National Institutes of Health; Universities; Update; Water; analytical method; attenuation; cognitive benefits; cryogenics; dietary constituent; dietary supplements; experimental study; ionization technique; metabolomics; milligram; mitochondrial dysfunction; novel therapeutics; pharmacophore; preclinical study; resilience; response; three dimensional structure

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.

项目摘要 膳食补充剂（DS）的好处，包括植物，是有据可查的，因为他们是消费 大约是美国成年人口的一半出于安全性和批次间一致性的目的， 尽管必须对植物来源DS的化学成分进行鉴定和表征， 混合物的复杂性和许多组成成分的可能活性贡献使得 任务的挑战性。基于液相色谱-质谱联用（LC-MS）的方法是 迄今为止，在鉴定和表征植物中已知的生物活性化合物方面最可靠的方法是 DS.更可靠和更新的质谱数据库和方法以及新的 然而，仍然需要补充方法用于快速代谢物鉴定、活性测定、 一致性和批次间质量控制。核磁共振光谱学长期以来一直与质谱联用。 光谱法在天然产物代谢组学分析中的应用，并明确确定有机化合物的结构 化合物.然而，在许多基于NMR的代谢组学研究中，大多数谱分析仅关注可识别的（或 已知的）主要化合物，留下由复杂混合物产生的重叠信号的识别 化合物是主要的挑战。此外，纯的真实标准化合物显示质子和碳 信号的化学位移与混合物中相同化合物的化学位移略有不同， 移位差异使得基于NMR代谢组学即使不是不准确也是困难的。然而，形状和 由于自旋网络中耦合质子的信号分裂保持不变，尽管混合增强 共振位移这些不变的自旋网络特征可以通过选择性的一维 TOCSY（S1 DT）实验，其使用显示信号灵敏度增加的脉冲序列，特别是当 使用高场强NMR和大量扫描。此外，许多异构体在 大多数MS分析可以使用它们的S1 DT指纹产生的特征自旋网络来区分。我们 总体目标是将识别的S1 DT指纹信息与现有质谱数据相结合 BENFRA植物性膳食补充剂上现有的关于Centella asiatica（gotu kola）的信息 研究中心（NIH/NCCIH U19 AT 010829）和本研究期间分离的化合物的那些， 补充LC-MS进行批间质量控制和活性测定。目标1：全面 非靶向分离将提供参考标准化合物和稳健的LC-MS数据库， 用于中心和其他研究团体的识别和标准化研究 工作在C。亚洲菜此外，S1 DT的新应用将有助于准确识别 化学成分及其潜在药效团的比较1H自旋网络指纹图谱 在分离的化合物中鉴定的化合物与提取物的1H NMR光谱中鉴定的化合物将 在Aim 2中开发。