Henderson, Scott H, Sorrell, Fiona, Bennett, James, Hanley, Marcus T, Robinson, Sean, Hopkins Navratilova, Iva, Elkins, Jonathan M and Ward, Simon E  ORCID: https://orcid.org/0000-0002-8745-8377
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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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 ∼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: | Schools > Biosciences Schools > Medicine Research Institutes & Centres > 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 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/133166 |
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