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Mining Public Domain Data to Develop Selective DYRK1A Inhibitors.

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.

SUBMITTER: Henderson SH

PROVIDER: S-EPMC7430967 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Mining Public Domain Data to Develop Selective DYRK1A Inhibitors.

Henderson Scott H SH Sorrell Fiona F Bennett James J Hanley Marcus T MT Robinson Sean S Hopkins Navratilova Iva I Elkins Jonathan M JM Ward Simon E SE

ACS medicinal chemistry letters 20200630 8

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 de ...[more]

PMID: 32832032

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