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Mining Public Domain Data to Develop Selective DYRK1A Inhibitors.
ACS Medicinal Chemistry Letters ( IF 3.5 ) Pub Date : 2020-06-30 , DOI: 10.1021/acsmedchemlett.0c00279
Scott H Henderson 1 , Fiona Sorrell 2 , James Bennett 3 , Marcus T Hanley 4 , Sean Robinson 5 , Iva Hopkins Navratilova 5, 6 , Jonathan M Elkins 2, 7 , Simon E Ward 4
Affiliation  

Kinases represent one of the most intensively pursued groups of targets in modern-day drug discovery. Often it is desirable to achieve selective inhibition of the kinase of interest over the remaining ∼500 kinases in the human kinome. This is especially true when inhibitors are intended to be used to study the biology of the target of interest. We present a pipeline of open-source software that analyzes public domain data to repurpose compounds that have been used in previous kinase inhibitor development projects. We define the dual-specificity tyrosine-regulated kinase 1A (DYRK1A) as the kinase of interest, and by addition of a single methyl group to the chosen starting point we remove glycogen synthase kinase β (GSK3β) and cyclin-dependent kinase (CDK) inhibition. Thus, in an efficient manner we repurpose a GSK3β/CDK chemotype to deliver 8b, a highly selective DYRK1A inhibitor.

中文翻译:

挖掘公共领域数据以开发选择性 DYRK1A 抑制剂。

激酶代表了现代药物发现中最受关注的一组目标。通常需要对人类激酶组中剩余的约 500 种激酶实现对目标激酶的选择性抑制。当抑制剂旨在用于研究目标靶点的生物学时尤其如此。我们提供了一系列开源软件,可分析公共领域数据以重新利用以前激酶抑制剂开发项目中使用过的化合物。我们将双特异性酪氨酸调节激酶​​ 1A (DYRK1A) 定义为感兴趣的激酶,并通过在选定的起点添加单个甲基基团来去除糖原合酶激酶 β (GSK3β) 和细胞周期蛋白依赖性激酶 (CDK)抑制。因此,我们以一种有效的方式重新利用 GS​​K3β/CDK 化学型来提供8b,高选择性DYRK1A抑制剂。
更新日期:2020-08-14
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