UC2 搜索：通过基于质谱的代谢组学中的数据库搜索，利用未带电化合物的独特连通性进行代谢物注释。
UC2 search: using unique connectivity of uncharged compounds for metabolite annotation by database searching in mass spectrometry-based metabolomics.
机构信息
Department of Technology Development, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan.
Department of Agricultural Biotechnology, National Institute of Agricultural Sciences, Jeonju 54874, Korea.
出版信息
Bioinformatics. 2018 Feb 15;34(4):698-700. doi: 10.1093/bioinformatics/btx649.
SUMMARY
For metabolite annotation in metabolomics, variations in the registered states of compounds (charged molecules and multiple components, such as salts) and their redundancy among compound databases could be the cause of misannotations and hamper immediate recognition of the uniqueness of metabolites while searching by mass values measured using mass spectrometry. We developed a search system named UC2 (Unique Connectivity of Uncharged Compounds), where compounds are tentatively neutralized into uncharged states and stored on the basis of their unique connectivity of atoms after removing their stereochemical information using the first block in the hash of the IUPAC International Chemical Identifier, by which false-positive hits are remarkably reduced, both charged and uncharged compounds are properly searched in a single query and records having a unique connectivity are compiled in a single search result.
AVAILABILITY AND IMPLEMENTATION
The UC2 search tool is available free of charge as a REST web service (http://webs2.kazusa.or.jp/mfsearcher) and a Java-based GUI tool.
CONTACT
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
摘要
在代谢组学的代谢物注释中，化合物（带电分子和多个成分，如盐）的注册状态的变化及其在化合物数据库中的冗余可能导致错误注释，并阻碍在使用质谱测量的质量值进行搜索时对代谢物独特性的即时识别。我们开发了一个名为 UC2（未带电化合物的独特连接性）的搜索系统，其中化合物被暂时中和成不带电状态，并在使用 IUPAC 国际化学标识符的哈希值的第一块去除其立体化学信息后，基于其原子的独特连接性进行存储，由此显著减少了假阳性命中，在单个查询中适当地搜索带电和不带电的化合物，并将具有独特连接性的记录编制到单个搜索结果中。
可用性和实现
UC2 搜索工具可免费作为 REST Web 服务（http://webs2.kazusa.or.jp/mfsearcher）和基于 Java 的 GUI 工具使用。
联系人
补充信息
补充数据可在 Bioinformatics 在线获得。
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