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Method for the Compound Annotation of Conjugates in Nontargeted Metabolomics Using Accurate Mass Spectrometry, Multistage Product Ion Spectra and Compound Database Searching

机译:精确质谱,多级产物离子光谱和化合物数据库搜索的非目标代谢组学中缀合物的化合物批注方法

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Owing to biotransformation, xenobiotics are often found in conjugated form in biological samples such as urine and plasma. Liquid chromatography coupled with accurate mass spectrometry with multistage collision-induced dissociation provides spectral information concerning these metabolites in complex materials. Unfortunately, compound databases typically do not contain a sufficient number of records for such conjugates. We report here on the development of a novel protocol, referred to as ChemProphet, to annotate compounds, including conjugates, using compound databases such as PubChem and ChemSpider. The annotation of conjugates involves three steps: 1. Recognition of the type and number of conjugates in the sample; 2. Compound search and annotation of the deconjugated form; and 3. In silico evaluation of the candidate conjugate. ChemProphet assigns a spectrum to each candidate by automatically exploring the substructures corresponding to the observed product ion spectrum. When finished, it annotates the candidates assigning a rank for each candidate based on the calculated score that ranks its relative likelihood. We assessed our protocol by annotating a benchmark dataset by including the product ion spectra for 102 compounds, annotating the commercially available standard for quercetin 3-glucuronide, and by conducting a model experiment using urine from mice that had been administered a green tea extract. The results show that by using the ChemProphet approach, it is possible to annotate not only the deconjugated molecules but also the conjugated molecules using an automatic interpretation method based on deconjugation that involves multistage collision-induced dissociation and in silico calculated conjugation.
机译:由于生物转化,异源生物通常以缀合形式存在于生物样品(如尿液和血浆)中。液相色谱与多级碰撞诱导解离的精确质谱联用,可提供有关复杂材料中这些代谢物的光谱信息。不幸的是,化合物数据库通常没有足够数量的此类结合物记录。我们在这里报告了一种新的协议的开发,该协议称为ChemProphet,用于使用化合物数据库(例如PubChem和ChemSpider)注释化合物(包括共轭物)。共轭物的注释包括三个步骤:1.识别样品中共轭物的类型和数量; 2.复合搜索和解形形式的注释; 3.在计算机上评估候选缀合物。 ChemProphet通过自动探索​​与观察到的产物离子光谱相对应的亚结构,为每个候选物分配光谱。完成后,它会基于计算出的得分(对它的相对可能性进行排名),对为每个候选人分配排名的候选人进行注释。通过评估基准数据集,包括102种化合物的产物离子谱图,对槲皮素3-葡萄糖醛酸苷的市售标准进行注释,以及通过使用小鼠小鼠的尿液进行了模型实验,该实验已被给予绿茶提取物,我们评估了我们的方案。结果表明,通过使用ChemProphet方法,不仅可以注释解偶联的分子,而且可以使用基于解偶联的自动解释方法对偶联的分子进行注释,该解偶联涉及多阶段碰撞诱导的解离和计算机计算的偶联。

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