Mining Public Domain Data to Develop Selective DYRK1A Inhibitors.
ACS Med Chem Lett
; 11(8): 1620-1626, 2020 Aug 13.
Article
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| MEDLINE
| ID: mdl-32832032
ABSTRACT
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 â¼500 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 ß (GSK3ß) and cyclin-dependent kinase (CDK) inhibition. Thus, in an efficient manner we repurpose a GSK3ß/CDK chemotype to deliver 8b, a highly selective DYRK1A inhibitor.
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ACS Med Chem Lett
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2020
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Article