Novel Kinase Ligand Generation Using Subpocket-Based Docking

Protein kinases are crucial for signal transduction by catalyzing phosphorylation. Dysregulation is linked to diseases like cancer, autoimmune disorders, and Alzheimer's, making them key drug targets. High interest in this protein family has yielded large amounts of available structure and ligand data. Fragment-based drug design has shown promise in developing kinase inhibitors, but often ignores kinase-specific knowledge. The KinFragLib library addresses this by fragmenting co-crystallized kinase ligands based on functionally relevant subpockets, resulting in a library of 7486 fragments from 2553 kinase-ligand complexes. Despite the extensive chemical space spanned by this library, enumerating all possible recombinations is computationally infeasible. To tackle this, we developed an automated Python pipeline that orchestrates fragment growing within the binding site of any protein kinase of interest, employing SeeSAR's docking engine. A guided template docking search, informed by subpocket-specific information, reduces the combinatorial space, ensuring efficient ligand generation. In a case study, we applied our subpocket-based docking approach on a PKA kinase, generating 33,758 compounds. 1154 of these compounds were considered drug-like according to the Rule of Five and have HYDE affinity scores in the nM range. When compared to the space covered by ChEMBL33, these compounds exhibit novel chemical matter of more than 99.1% considering a similarity cut-off greater or equal 0.9. After further filtering steps, eleven molecules were selected for synthesis, seven of which were slightly modified to simplify synthesis. Similar variants of some proposed molecules were added, resulting in fifteen molecules that were ultimately synthesized and tested. Seven molecules reduced kinase activity by more than 50% at an inhibitor concentration of 100 μM. Remarkably, six of them showed promising activity even at 10 μM inhibitor concentration, with residual protein activity below 25%.