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Updated: Apr 21, 2026

Identification of Kinase-substrate Pairs Using High Throughput Screening
Published on: August 29, 2015
Deciphering covalent kinase inhibitor binding landscape through structural kinome profiling
1School of Data Science and Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, 22904, United States of America.
Abstract:
Significant progress in kinase-targeted drug discovery has been made over the past two decades, with 100 FDA-approved kinase-targeted drugs and a substantial number of bioactive kinase inhibitors under preclinical study. However, given that more than 180 kinases have been implicated in disease, there remains a considerable need for continued kinase-targeted drug discovery. Covalent kinase inhibitors (CKIs) are a class of kinase inhibitors that form covalent interactions with kinase targets, valued for the potential for enhanced selectivity through anchoring nucleophiles. Here, we collate all the kinase structures from the PDB into dedicated structural kinome resources, containing: (i) the kinase domain structure database (6969 PDB structures); (ii) the kinase ligand-binding structure database (6122 PDB structures); and (iii) the kinase-CKI complex structure database (325 PDB structures). With these data, we systematically investigate the binding modes of CKIs, the fingerprint characteristics of kinase-CKI interactions, 21 types of electrophilic warheads, and 64 nucleophilic amino acids distributed in 15 corresponding spatial positions in kinase domains. We also mentioned covalent degraders and multi-warhead CKIs. Together, our results offer a comprehensive structural kinase resource and in-depth insights into CKI binding properties, supporting future kinase-targeted drug design. The databases are freely accessible at https://zhengzhster.github.io/KinaseStructureDatabase/.
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