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首页> 外文期刊>Journal of the American Society for Mass Spectrometry >Identification of 'known unknowns' utilizing accurate mass data and chemspider
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Identification of 'known unknowns' utilizing accurate mass data and chemspider

机译:利用准确的质量数据和化学蜘蛛鉴定“未知未知物”

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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.
机译:在许多情况下,化学文献,参考数据库或互联网资源实际上是调查人员未知的。我们将这些类型的化合物称为“已知未知物”。 ChemSpider是一个非常有价值的已知化合物互联网数据库,可用于鉴定商业,环境,法医和天然产品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2600万个条目,并作为免费资源提供给社区。准确的质谱数据用于通过元素组成或单同位素质量查询数据库。按元素组成搜索是首选方法。但是,通常难以确定分子量大于600 Da的化合物的独特元素组成。在这些情况下,按单一同位素质量进行搜索是有利的。在任何一种情况下,搜索结果都是通过按降序对与每个化合物关联的参考文献数量进行排序来优化的。这将最有用的候选者排在列表的顶部,以进行进一步评估。这些方法被证明可以成功地识别我们实验室中提到的“未知未知物”以及其他人感兴趣的化合物。

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