Subpocket-Aware Fragment-Based Docking Pipeline for Kinase Ligand Design: Methodology and PKA Case Study

Protein kinases regulate signal transduction through phosphorylation, and their dysregulation drives diseases like cancer, making them key drug targets. Fragment-based drug design offers a powerful route to kinase inhibitors, but often neglects kinase-specific structural insights. While KinFragLib, a library consisting of 7486 fragments derived from kinase-ligand complexes, provides a rich resource, exhaustive recombination of its fragments is computationally demanding. Here, we present an efficient exploration strategy that integrates subpocket-guided fragment growing with template docking to navigate this vast chemical space. Our automated pipeline prioritizes kinase-specific structural information, enabling targeted generation of chemically diverse ligands. Applied to PKA kinase, the approach produced 33 758 candidate molecules with promising docking scores, based on which 15 were synthesized. Seven molecules reduced kinase activity by more than 50 % at an inhibitor concentration of 100 μM. Four of them showed promising activity even at 10 μM, with residual protein activity below 25 %. Crystallographic validation confirmed the predicted binding mode of the most potent compound. This methodology demonstrates how structure-informed guidance can transform fragment-based design into a scalable route for discovering novel kinase inhibitors.