STRUCTURE-BASED KINASE INHIBITOR DESIGN: BINDING-MODE TAXONOMY, DFG-STATE TARGETING, AND ALLOSTERIC STRATEGIES

Structure-based drug design (SBDD) has emerged as a transformative approach in the development of selective small-molecule kinase inhibitors, driven by advances in structural biology and computational chemistry. This review highlights the central role of kinase conformational dynamics-particularly the “DFG-in” and “DFG-out” states—in dictating inhibitor binding modes, selectivity, and mechanisms of resistance. By integrating insights from high-resolution crystallography, molecular docking, virtual screening, and recent geometric deep-learning-based methods, we summarise contemporary strategies that enable precise exploration of kinase active and allosteric pockets. Key trends discussed include the preferential targeting of the DFG-out conformation to improve specificity, the rise of allosteric modulators to overcome ATP-competitive limitations, and iterative structure-guided optimisation pipelines that accelerate lead discovery. We also examine emerging computational–experimental hybrid frameworks that enhance predictive accuracy, support exploration of undersampled chemical space, and enable the rational design of next-generation inhibitors with improved pharmacological profiles. Overall, this review underscores how modern SBDD methodologies continue to advance kinase inhibitor discovery by addressing longstanding challenges related to selectivity, resistance, and off-target effects, ultimately contributing to the development of safer and more effective therapeutic agents.