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

Abstract

Abstract Protein kinases regulate signal transduction through phosphorylation, and their dysregulation drives diseases like cancer, autoimmune disorders, and Alzheimer’s, 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 the PKA kinase, the approach produced 33758 candidate molecules with promising docking scores, of which 15 were synthesized. Seven molecules reduced kinase activity by more than 50% at an inhibitor concentration of 100 μM, and five of these compounds also showed promising efficacy at a concentration of 10 μM. The IC50 determination ultimately revealed that five of the molecules were effective in the two- to three-digit nanomolar range. 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.

The authors' abstract, as published at the source. Journal of Chemical Information and Modeling, 2026 · DOI ↗