Identification of metabolites and small compounds using mass spectrometry

使用质谱法鉴定代谢物和小化合物

• 批准号: 192186822
• 负责人: Privatdozent Dr. Wolfgang Brandt
• 金额: --
• 依托单位: Abteilung Natur- und Wirkstoffchemie
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2010
• 资助国家: 德国
• 起止时间: 2009-12-31 至 2014-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/192186822?language=en
• 关键词: Identification; metabolites; small; compounds; using

Mass spectrometry is a key technology for the identification of small molecules. Today, the identification of metabolites from mass spectra relies on the comparison with authentic compounds or reference spectra. The first are often expensive to obtain, the latter cover only a small portion of the vast chemical space. The key objective of the ChemFrag project is to identify compounds with tandem mass spectrometry in candidates obtained from general purpose compound libraries. Because a mechanistic simulation of the process is computationally infeasible, we develop simplified in-silico fragmentation methods, statistical models and apply machine learning to a large set of training spectra. Our approach screens a set of candidate molecules, to find molecular fragments which explain the experimentally measured peaks. In addition to a simple bond disconnection approach on the molecular graph, we incorporate the chemical context and precalculated bond energies and bond strain upon protonation.

质谱分析是鉴定小分子的关键技术。如今，从质谱中鉴定代谢物依赖于与真实化合物或参考光谱的比较。前者的获取成本通常很高，而后者仅涵盖了广阔的化学空间的一小部分。 ChemFrag 项目的主要目标是通过串联质谱法识别从通用化合物库中获得的候选化合物中的化合物。由于该过程的机械模拟在计算上是不可行的，因此我们开发了简化的计算机碎裂方法、统计模型，并将机器学习应用于大量训练光谱。我们的方法筛选一组候选分子，以找到解释实验测量峰的分子片段。除了分子图上的简单键断开方法之外，我们还结合了化学背景和预先计算的键能以及质子化时的键应变。