Department of Medicine and Public Health, Unit of Forensic Medicine, University of Verona, Verona, Italy.
J Mass Spectrom. 2010 Mar;45(3):261-71. doi: 10.1002/jms.1710.
High-resolution mass spectrometry (HRMS) enables the identification of a chemical formula of small molecules through the accurate measurement of mass and isotopic pattern. However, the identification of an unknown compound starting from the chemical formula requires additional tools: (1) a database associating chemical formulas to compound names and (2) a way to discriminate between isomers. The aim of this present study is to evaluate the ability of a novel 'metabolomic' approach to reduce the list of candidates with identical chemical formula. Urine/blood/hair samples collected from real positive cases were submitted to a screening procedure using ESI-MS-TOF (positive-ion mode) combined with either capillary electrophoresis or reversed phase liquid chromatography (LC). Detected peaks were searched against a Pharmaco/Toxicologically Relevant Compounds database (ca 50,500 compounds and phase I and phase II metabolites) consisting of a subset of PubChem compounds and a list of candidates was retrieved. Then, starting from the mass of unknown, mass shifts corresponding to pre-defined biotransformations (e.g. demethylation, glucuronidation, etc.) were calculated and corresponding mass chromatograms were extracted from the total ion current (TIC) in order to search for metabolite peaks. For each candidate, the number of different functional groups in the molecule was automatically calculated using E-Dragon software (Talete srl, Milan, Italy). Then, the presence of metabolites in the TIC was matched with functional groups data in order to exclude candidates with structures not compatible with observed biotransformations (e.g. loss of methyl from a structure not bearing methyls). The procedure was tested on 108 pharmaco-toxicologically relevant compounds (PTRC) and their phase I metabolites were detected in real positive samples. The mean list length (MLL) of candidates retrieved from the database was 7.01 +/- 4.77 (median, 7; range, 1-28) before the application of the 'metabolomic' approach, and after the application it was reduced to 4.08 +/- 3.11 (median 3, range 1-17). HRMS allows a much broader screening for PTRC than other screening approaches (e.g. library search on mass spectra databases). The 'metabolomic' approach enables the reduction of the list of candidate isomers.
高分辨率质谱(HRMS)通过准确测量质量和同位素模式,实现小分子化学公式的鉴定。然而,从化学公式开始鉴定未知化合物需要额外的工具:(1)将化学公式与化合物名称相关联的数据库,(2)一种区分异构体的方法。本研究旨在评估一种新型“代谢组学”方法减少具有相同化学公式的候选者名单的能力。从真实阳性病例中采集的尿液/血液/头发样本,采用 ESI-MS-TOF(正离子模式)与毛细管电泳或反相液相色谱(LC)相结合的筛选程序进行检测。检测到的峰与一个 Pharmaco/Toxicologically Relevant Compounds 数据库(约 50,500 种化合物和 I 相和 II 相代谢物)进行搜索,该数据库由 PubChem 化合物的子集和候选者名单组成。然后,从未知物的质量开始,计算出对应于预定义生物转化(例如去甲基化、葡萄糖醛酸化等)的质量位移,并从总离子流(TIC)中提取相应的质量色谱图,以搜索代谢物峰。对于每个候选者,使用 E-Dragon 软件(意大利米兰的 Talete srl)自动计算分子中不同官能团的数量。然后,将 TIC 中代谢物的存在与官能团数据进行匹配,以排除与观察到的生物转化不兼容的结构的候选者(例如,从不含有甲基的结构中失去甲基)。该方法在 108 种药物毒理学相关化合物(PTRC)及其 I 相代谢物在真实阳性样本中的检测中进行了测试。在应用“代谢组学”方法之前,从数据库中检索到的候选者的平均列表长度(MLL)为 7.01 +/- 4.77(中位数 7;范围 1-28),应用后降至 4.08 +/- 3.11(中位数 3,范围 1-17)。HRMS 允许比其他筛选方法(例如,基于质谱数据库的库搜索)更广泛地筛选 PTRC。“代谢组学”方法可以减少候选异构体的列表。