In Silico-Enabled Discovery and Development of Potent and Selective CDK11 Inhibitors

Cyclin-dependent kinase 11 (CDK11) plays a critical role in cell cycle regulation and transcriptional control, making it a promising target for therapeutic intervention in cancer and other proliferative disorders. This study employs computationally driven approaches encompassing homology modelling, molecular dynamic simulations, ultralarge-scale virtual screening and medicinal chemistry optimisation to develop a series of novel inhibitors of CDK11. Our virtual screening pipeline led to the identification of two initial hits (compounds 3 and 4), which were further evaluated through structure-activity relationship (SAR) studies. Together with structure-guided molecular docking and design, these SAR analyses revealed key structural motifs and functional groups that are crucial for inhibitory activity and selectivity, providing insights into the efficient hit-to-lead optimisation. Compound 37 emerged as an optimised potent and selective CDK11 inhibitor (IC₅₀ 4 nM, kinome panel clean). In a lung tumour model, mice dosed twice daily with 100 mg/kg of compound 37 showed ∼30% tumour growth inhibition. Both in vitro absorption, distribution, metabolism and excretion and in vivo mouse pharmacokinetics (PK) profiling indicated that compound 37 possesses excellent PK/pharmacodynamic properties, positioning the compound for further development and evaluation as a lead candidate for CDK11-targeted therapy. Meanwhile, the series of compounds developed throughout this study represent novel tools for studying CDK11-mediated pathophysiology. The integration of in silico modelling, screening and structure-based drug design provides a robust strategy for accelerating the identification of potent and selective inhibitors for other CDK families.