Structure-Based Optimization of TBK1 Inhibitors

TBK1 is a crucial kinase involved in immunity, inflammation, and autophagy with dysregulation linked to various diseases, making it a potential therapeutic target. In this study, we applied a structure-based lead optimization approach to design potent and selective TBK1 inhibitors. A focused virtual library containing over 5,000 compounds was constructed, sampled, and refined within the kinase binding site, followed by a 10 ns molecular dynamics simulation for each modeled binding complex. Based on MM/PBSA binding free energies and structural clustering, we selected 14 structurally diverse compounds for chemical synthesis and biological assays. This strategy yielded a potent TBK1 inhibitor (IC₅₀ = 775 pM) from an initial hit of 19.57 μM. This inhibitor features a novel scaffold and exhibits excellent enzymatic inhibition. Furthermore, it enhances immune-mediated cytotoxicity without exhibiting cytotoxicity when used as a single agent. These findings provide a foundation for the development of targeted therapies for the treatment of TBK1-associated diseases.