Similarity-Based Classifier Using Topomers to Provide a Knowledge Base for hERG Channel Inhibition
Similarity-Based Classifier Using Topomers to Provide a Knowledge Base for hERG Channel Inhibition
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DOI：
10.1021/ci800304t
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发表时间：
2009-01
影响因子：
5.6
通讯作者：
Britta Nisius;A. Göller
中科院分区：
文献类型：
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作者：
Britta Nisius;A. Göller
在原理研究的证明中，我们表明相似性原理可以应用于预测ADMET特性，例如hERG K+通道抑制的情况。候选药物的hERG通道活性的早期预测在药物发现过程中变得越来越重要，因为hERG通道的阻断可能导致危及生命的心律失常。使用Tripos拓扑异构体搜索技术作为化合物相似性度量，我们在一组具有已知hERG活性的化合物中查询具有未知hERG活性的分子中的相似分子。然后基于其拓扑异构体搜索邻居的hERG活性及其与查询分子的距离预测查询分子的hERG活性。只要查询化合物的化学空间与参考数据集之间存在高度的结构重叠，就可以应用相似性原理来预测hERG抑制，具有良好的性能。我们表明，这是可以实现的数据库大小约10,000个结构不同的分子。在这种情况下，topoHERG是一种基于相似性的hERG分类器，也可作为hERG通道抑制的知识库。
In a proof of principle study we show that the similarity property principle can be applied to predict ADMET properties, exemplified on the case of hERG K+ channel inhibition. Early prediction of a drug candidate's hERG channel activity is becoming increasingly important in the drug discovery process because blockade of the hERG channel may lead to life-threatening cardiac arrhythmias. Using the Tripos Topomer Search technology as compound similarity measure, we query molecules with unknown hERG activity for similar molecules in a set of compounds with known hERG activity. The hERG activity of the query molecule is then predicted based on the hERG activity of its Topomer Search neighbors and their distances to the query molecule. The similarity property principle can be applied with promising performance to predict hERG inhibition as long as there is a high structural overlap between the chemical spaces of the query compounds and the reference data set. We show that this is achievable for database sizes of about 10,000 structurally diverse molecules. In this case topoHERG is a similarity-based hERG classifier, which also acts as a knowledge base for hERG channel inhibition.