Next generation, 'Standards-Free' Metabolite Identification Pipeline

下一代“无标准”代谢物鉴定管道

• 批准号: 9433322
• 负责人: Thomas O Metz
• 金额: $ 19.01万
• 依托单位: BATTELLE PACIFIC NORTHWEST LABORATORIES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-21 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9433322
• 关键词: Alcohols; Alkaloids; Amino Acids; Antioxidants; Attributes of Chemicals; Biological; Biological Markers; Biomedical Research; Carbohydrates; Chemicals; Clinical; Collaborations; Communities; Complex; Computer Simulation; Computing Methodologies; Constitutional; Coupled; Data; Data Analyses; Databases; Dependency; Device or Instrument Development; Diet; Disease; Environment; Environmental Exposure; Flavonoids; Funding; Gases; Genome; Geometry; Glycosides; Goals; Health; Human; Individual; Insulin-Dependent Diabetes Mellitus; Isomerism; Isotopes; Knowledge; Laboratories; Libraries; Lipids; Mass Spectrum Analysis; Measurement; Measures; Metabolic; Methods; Mission; Molecular; Nucleotides; Outcome; Pacific Northwest; Peptides; Phase; Property; Research; Research Personnel; Research Project Grants; Resolution; Resources; Role; Sampling; Science; Siblings; Spectrometry; Speed; Standardization; Steroids; Structure; Supercomputing; United States National Institutes of Health; Urine; Validation; Vitamins; Work; base; biomarker discovery; chemical property; chemical standard; cheminformatics; combinatorial; comparative; computational chemistry; computerized tools; diagnosis evaluation; disease diagnosis; genetic information; genome sequencing; innovation; instrumentation; ion mobility; metabolome; metabolomics; molecular dynamics; next generation; non-diabetic; non-genetic; open source; organic acid; quantum; quantum chemistry; simulation; small molecule; small molecule libraries; tool; type I diabetic

Research Plan Abstract The capability to chemically identify thousands of metabolites and other chemicals in clinical samples will revolutionize the search for environmental, dietary, and metabolic determinants of disease. By comparison to near-comprehensive genetic information, comparatively little is understood of the totality of the human metabolome, largely due to insufficiencies in molecular identification methods. Through innovations in computational chemistry, we propose to overcome a significant, long standing obstacle in the field of metabolomics: the absence of methods for accurate and comprehensive identification of small molecules without relying on data from analysis of authentic chemical standards. A paradigm shift in metabolomics, we will use a gas-phase molecular property, collision cross section, that can be both accurately predicted computationally and consistently measured experimentally, and which can thus be used for comprehensive identification of the metabolome without the need for authentic chemical standards. The outcomes of this proposal directly advance the mission and goals of the NIH Common Fund by: (i) transforming metabolomics science by enabling consideration of the totality of the human metabolome through optimized identification of currently unidentifiable molecules, eventually reaching hundreds of thousands of molecules, and (ii) developing standardized computational tools to increase the national capacity for biomedical researchers to identify metabolites quickly and accurately. This work is significant because it enables comprehensive and confident chemical measurement of the metabolome. This work is innovative because it utilizes a high throughput, high accuracy, quantum-chemistry-based computational and chemical informatics platform to predict physical-chemical properties of metabolites from first principles.

研究计划摘要 化学识别成千上万的代谢产物和其他化学物质的能力将革新 寻找疾病的环境，饮食和代谢决定因素。相比之下 遗传信息对人类代谢组的总数相对较少，主要是由于 分子鉴定方法的不足。通过计算化学的创新，我们建议 克服代谢组学领域的重要，长期存在的障碍：缺乏准确和 对小分子的全面鉴定，而无需依赖于真实化学标准分析的数据。一个 代谢组学的范式转移，我们将使用气相分子特性，碰撞横截面，这两者都可以 准确地在计算和一致的实验中进行了测量，因此可以用于 无需真正的化学标准，对代谢组的全面识别。结果的结果 提案直接通过以下方式直接推进NIH共同基金的使命和目标：（i）通过 通过优化当前的识别，可以考虑人类代谢组的总体 无法识别的分子，最终达到数十万个分子，（ii）发展标准化 计算工具，以提高生物医学研究人员快速识别代谢物的国家能力 准确。这项工作很重要，因为它可以对 代谢组。这项工作具有创新性，因为它利用了高吞吐量，高精度，基于量子化学的化学 从第一 原则。