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Is nontarget screening of emerging contaminants by LC-HRMS successful? A plea for compound libraries and computer tools

机译:通过LC-HRMS对新兴污染物进行非目标筛查是否成功?化合物库和计算机工具的请求

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This review focuses on the possibilities and limits of nontarget screening of emerging contaminants, with emphasis on recent applications and developments in data evaluation and compound identification by liquid chromatography–high-resolution mass spectrometry (HRMS). The general workflow includes determination of the elemental composition from accurate mass, a further search for the molecular formula in compound libraries or general chemical databases, and a ranking of the proposed structures using further information, e.g., from mass spectrometry (MS) fragmentation and retention times. The success of nontarget screening is in some way limited to the preselection of relevant compounds from a large data set. Recently developed approaches show that statistical analysis in combination with suspect and nontarget screening are useful methods to preselect relevant compounds. Currently, the unequivocal identification of unknowns still requires information from an authentic standard which has to be measured or is already available in user-defined MS/MS reference databases or libraries containing HRMS spectral information and retention times. In this context, we discuss the advantages and future needs of publicly available MS and MS/MS reference databases and libraries which have mostly been created for the metabolomic field. A big step forward has been achieved with computer-based tools when no MS library or MS database entry is found for a compound. The numerous search results from a large chemical database can be condensed to only a few by in silico fragmentation. This has been demonstrated for selected compounds and metabolites in recent publications. Still, only very few compounds have been identified or tentatively identified in environmental samples by nontarget screening. The availability of comprehensive MS libraries with a focus on environmental contaminants would tremendously improve the situation.
机译:这篇综述着重于对新兴污染物进行非目标筛查的可能性和局限性,重点是液相色谱-高分辨率质谱(HRMS)在数据评估和化合物鉴定中的最新应用和发展。一般的工作流程包括根据准确的质量确定元素组成,在化合物库或常规化学数据库中进一步搜索分子式以及使用进一步的信息(例如质谱(MS)碎裂和保留)对拟议结构进行排名次。非靶标筛选的成功在某种程度上限于从大量数据集中预选相关化合物。最近开发的方法表明,将统计分析与可疑筛查和非靶标筛查相结合是预先选择相关化合物的有用方法。当前,对未知物的明确鉴定仍然需要来自可靠标准的信息,该信息必须进行测量,或者已经在用户定义的MS / MS参考数据库或包含HRMS光谱信息和保留时间的库中提供。在这种情况下,我们讨论了大多数为代谢组学领域创建的可公开获得的MS和MS / MS参考数据库和库的优势和未来需求。当找不到化合物的MS库或MS数据库条目时,使用基于计算机的工具已迈出了一大步。大型化学数据库中的大量搜索结果可以通过计算机片段化精简为少数几个。在最近的出版物中已针对选定的化合物和代谢物证明了这一点。尽管如此,通过非靶标筛选在环境样品中仅鉴定或初步鉴定出很少的化合物。侧重于环境污染物的全面MS库的可用性将极大地改善这种情况。

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