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Identification of 'known unknowns' utilizing accurate mass data and chemical abstracts service databases

机译:利用准确的质量数据和化学文摘服务数据库识别“已知未知物”

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In many cases, an unknown to an investigator is actually known in the chemical literature. We refer to these types of compounds as "known unknowns." Chemical Abstracts Service (CAS) Registry is a particularly good source of these substances as it contains over 54 million entries. Accurate mass measurements can be used to query the CAS Registry by either molecular formulae or average molecular weights. Searching the database by the web-based version of SciFinder is the preferred approach when molecular formulae are available. However, if a definitive molecular formula cannot be ascertained, searching the database with STN Express by average molecular weights is a viable alternative. The results from either approach are refined by employing the number of associated references or minimal sample history as orthogonal filters. These approaches were shown to be successful in identifying "known unknowns" noted in LC-MS and even GC-MS analyses in our laboratory. In addition, they were demonstrated in the identification of a variety of compounds of interest to others.
机译:在许多情况下,化学文献中实际上是已知研究人员未知的。我们将这些类型的化合物称为“已知未知物”。化学文摘社(CAS)注册表是这些物质的特别好来源,因为它包含超过5400万个条目。精确的质量测量可用于通过分子式或平均分子量查询CAS Registry。当分子式可用时,通过Web版本的SciFinder搜索数据库是首选方法。但是,如果无法确定确定的分子式,则可以使用STN Express通过平均分子量搜索数据库。通过采用关联参考的数量或最小样本历史记录作为正交过滤器,可以精炼来自这两种方法的结果。这些方法被证明可以成功地识别我们实验室中LC-MS甚至GC-MS分析中提到的“已知未知物”。此外,它们在鉴定其他人感兴趣的各种化合物中得到了证明。

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