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• W2501602017 abstract "Despite the considerable interest in protein kinase C-related kinase 1 (PRK1) as a target in cancer research, there is still a lack of PRK1 inhibitors with suitable selectivity profiles and physicochemical properties. To identify new PRK1 inhibitors we applied a virtual screening approach, which combines ensemble docking, minimization of the protein–ligand complex, binding free energy calculations, and application of quantitative structure–activity relationship (QSAR) models for predicting in vitro activity. The developed approach was then applied in a prospective manner to screen available libraries of kinase inhibitors from Selleck and GlaxoSmithKline (GSK). Compounds that showed favorable prediction were then tested in vitro for PRK1 inhibition. Some of the hits were found to inhibit PRK1 in the low-nanomolar range. Three in vitro hits were additionally tested in a mass-spectrometry-based cellular kinase profiling assay to examine selectivity. Our findings show that nanomolar and drug-like inhibitors can be identified by the virtual screening approach presented herein. The identified inhibitors are valuable tools for gaining a better understanding of PRK1 inhibition, and the identified hits can serve as starting points for further chemical optimization." @default.
• W2501602017 created "2016-08-23" @default.
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• W2501602017 date "2016-07-29" @default.
• W2501602017 modified "2023-10-14" @default.
• W2501602017 title "Identification of Highly Potent Protein Kinase C-Related Kinase 1 Inhibitors by Virtual Screening, Binding Free Energy Rescoring, and in vitro Testing" @default.
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• W2501602017 doi "https://doi.org/10.1002/cmdc.201600284" @default.
• W2501602017 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27472906" @default.
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