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Updated: May 25, 2026

A Bilingual Computational Workflow for Identifying Potential PLK1 Inhibitors in American Sign Language and English
Published on: April 3, 2026
Identification of novel CLK1 inhibitors by computational fragment-based ligand design, co-crystallization, chemical
Stéphane Bourg1, Matthieu Place1, Chloé Copin1
1Université d'Orléans, CNRS, ICOA, UMR 7311, Orléans, France.
Abstract:
CLK1 is one of the four human isoforms of the cdc2-like (CLK) kinases that has been suggested as a therapeutic target in diverse diseases based on its important role regulating mRNA splicing. For example, CLKs and closely related kinases such as DYRK1A have been targeted in Alzheimer's disease and other diseases in which splice site selection contributes to the disease development. Here we have developed an efficient in silico fragment-based ligand design approach to identify novel CLK1 inhibitors with excellent ligand efficiency based on an imidazo[2,1-b][1,3,4]thiadiazole fragment. More than one million docking poses were generated from 26,225 unique virtual compounds, and after applying several filtering steps, 11 compounds were selected, synthesized and their CLK1 inhibition and cellular potency were evaluated. Gratifyingly, inhibitor potencies were in excellent agreement with predicted values and crystallographic data of an inhibitor bound to CLK1 confirmed the unusual binding mode of the compounds.
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