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Mining public domain data to develop selective DYRK1A inhibitors

Henderson, Scott H, Sorrell, Fiona, Bennett, James, Hanley, Marcus T, Robinson, Sean, Hopkins Navratilova, Iva, Elkins, Jonathan M and Ward, Simon E ORCID: 2020. Mining public domain data to develop selective DYRK1A inhibitors. ACS Medicinal Chemistry Letters 11 , pp. 1620-1626. 10.1021/acsmedchemlett.0c00279

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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.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Biosciences
MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Publisher: American Chemical Society
ISSN: 1948-5875
Date of First Compliant Deposit: 6 July 2020
Date of Acceptance: 22 May 2020
Last Modified: 04 May 2023 22:15

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