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利用精确质量数据和 ChemSpider 识别“已知的未知物”。

Identification of "known unknowns" utilizing accurate mass data and ChemSpider.

机构信息

Eastman Chemical Company, Kingsport, TN 37662, USA.

出版信息

J Am Soc Mass Spectrom. 2012 Jan;23(1):179-85. doi: 10.1007/s13361-011-0265-y. Epub 2011 Nov 2.

Abstract

In many cases, an unknown to an investigator is actually known in the chemical literature, a reference database, or an internet resource. We refer to these types of compounds as "known unknowns." ChemSpider is a very valuable internet database of known compounds useful in the identification of these types of compounds in commercial, environmental, forensic, and natural product samples. The database contains over 26 million entries from hundreds of data sources and is provided as a free resource to the community. Accurate mass mass spectrometry data is used to query the database by either elemental composition or a monoisotopic mass. Searching by elemental composition is the preferred approach. However, it is often difficult to determine a unique elemental composition for compounds with molecular weights greater than 600 Da. In these cases, searching by the monoisotopic mass is advantageous. In either case, the search results are refined by sorting the number of references associated with each compound in descending order. This raises the most useful candidates to the top of the list for further evaluation. These approaches were shown to be successful in identifying "known unknowns" noted in our laboratory and for compounds of interest to others.

摘要

在许多情况下,对于调查人员来说未知的实际上在化学文献、参考数据库或互联网资源中是已知的。我们将这些类型的化合物称为“已知的未知物”。ChemSpider 是一个非常有价值的互联网已知化合物数据库,可用于识别商业、环境、法医和天然产物样品中的这些类型的化合物。该数据库包含来自数百个数据源的超过 2600 万个条目,并作为免费资源提供给社区。通过元素组成或单同位素质量,使用精确质量质谱数据来查询数据库。通过元素组成进行搜索是首选方法。但是,对于分子量大于 600 Da 的化合物,通常很难确定其独特的元素组成。在这些情况下,通过单同位素质量进行搜索是有利的。在任何一种情况下,通过按与每个化合物相关的参考文献数量降序排列来对搜索结果进行细化。这将最有用的候选物提升到列表的顶部,以供进一步评估。这些方法已被证明可成功识别我们实验室中注意到的“已知的未知物”以及其他人感兴趣的化合物。

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