Reaction site mapping of xenobiotic biotransformations
Reaction site mapping of xenobiotic biotransformations
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DOI：
10.1021/ci600376q
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发表时间：
2007-03-01
影响因子：
5.6
通讯作者：
Glen, Robert C.
中科院分区：
文献类型：
--
作者：
Boyer, Scott;Arnby, Catrin Hasselgren;Glen, Robert C.
预测代谢方法可用于药物发现项目，以增强对结构-代谢关系的理解。本研究采用数据挖掘方法，利用生物转化数据已记录在MDL代谢物数据库。反应中心指纹来自底物和数据库中列出的相应产物的比较。这个过程产生两个指纹数据库：所有衬底中的所有原子和所有反应中心。然后，通过提交新分子并在两个数据库中搜索与新分子中每个原子匹配的指纹来挖掘代谢反应数据。“出现率”来源于提交的化合物与反应中心和底物指纹数据库之间的指纹匹配。每个提交分子内发生率的归一化使得检索结果能够被排序，作为在提交分子内特定位点处发生的反应的相对频率的量度。预测性能，这将使这种方法被用于药物发现团队产生有用的假设结构代谢关系进行了观察。
Predictive metabolism methods can be used in drug discovery projects to enhance the understanding of structure-metabolism relationships. The present study uses data mining methods to exploit biotransformation data that have been recorded in the MDL Metabolite database. Reacting center fingerprints were derived from a comparison of substrates and their corresponding products listed in the database. This process yields two fingerprint databases: all atoms in all substrates and all reacting centers. The metabolic reaction data are then mined by submitting a new molecule and searching for fingerprint matches to every atom in the new molecule in both databases. An "occurrence ratio" is derived from the fingerprint matches between the submitted compound and the reacting center and substrate fingerprint databases. Normalization of the occurrence ratio within each submitted molecule enables the results of the search to be rank-ordered as a measure of the relative frequency of a reaction occurring at a specific site within the submitted molecule. Predictive performance that would allow this method to be used by drug discovery teams to generate useful hypotheses regarding structure metabolism relationships was observed.