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超级毒物:一个关于有毒化合物的综合数据库。

SuperToxic: a comprehensive database of toxic compounds.

作者信息

Schmidt Ulrike, Struck Swantje, Gruening Bjoern, Hossbach Julia, Jaeger Ines S, Parol Roza, Lindequist Ulrike, Teuscher Eberhard, Preissner Robert

机构信息

Structural Bioinformatics Group, Institute of Molecular Biology and Bioinformatics, Charité - University Medicine Berlin, Arnimallee 22, 14195 Berlin, Germany.

出版信息

Nucleic Acids Res. 2009 Jan;37(Database issue):D295-9. doi: 10.1093/nar/gkn850. Epub 2008 Nov 12.

Abstract

Within our everyday life, we are confronted with a variety of toxic substances of natural or artificial origin. Toxins are already used, e.g. in medicine, but there is still an increasing number of toxic compounds, representing a tremendous potential to extract new substances. Since predictive toxicology gains in importance, the careful and extensive investigation of known toxins is the basis to assess the properties of unknown substances. In order to achieve this aim, we have collected toxic compounds from literature and web sources in the database SuperToxic. The current version of this database compiles about 60,000 compounds and their structures. These molecules are classified according to their toxicity, based on more than 2 million measurements. The SuperToxic database provides a variety of search options like name, CASRN, molecular weight and measured values of toxicity. With the aid of implemented similarity searches, information about possible biological interactions can be gained. Furthermore, connections to the Protein Data Bank, UniProt and the KEGG database are available, to allow the identification of targets and those pathways, the searched compounds are involved in. This database is available online at: http://bioinformatics.charite.de/supertoxic.

摘要

在我们的日常生活中,我们会接触到各种天然或人工来源的有毒物质。毒素已经在医学等领域得到应用,但有毒化合物的数量仍在不断增加,这为提取新物质提供了巨大潜力。由于预测毒理学变得越来越重要,对已知毒素进行仔细而广泛的研究是评估未知物质特性的基础。为了实现这一目标,我们在SuperToxic数据库中从文献和网络来源收集了有毒化合物。该数据库的当前版本汇编了约60,000种化合物及其结构。这些分子根据其毒性进行分类,基于超过200万次测量。SuperToxic数据库提供了多种搜索选项,如名称、化学物质登记号(CASRN)、分子量和毒性测量值。借助已实施的相似性搜索,可以获得有关可能的生物相互作用的信息。此外,还提供与蛋白质数据库(Protein Data Bank)、通用蛋白质数据库(UniProt)和京都基因与基因组百科全书数据库(KEGG)的链接,以确定所搜索化合物涉及的靶点和途径。该数据库可在线获取:http://bioinformatics.charite.de/supertoxic

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4f5/2686515/a669977d4a50/gkn850f1.jpg

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