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 selectivesmall-molecule kinase inhibitors, driven by advances in structural biology and computational chemistry. This reviewhighlights the central role of kinase conformational dynamics-particularly the “DFG-in” and “DFG-out” states—indictating inhibitor binding modes, selectivity, and mechanisms of resistance. By integrating insights fromhigh-resolution crystallography, molecular docking, virtual screening, and recent geometric deep-learning-basedmethods, we summarise contemporary strategies that enable precise exploration of kinase active and allostericpockets. 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-guidedoptimisation pipelines that accelerate lead discovery. We also examine emerging computational–experimental hybrid frameworks that enhance predictive accuracy, support exploration of undersampled chemical space, andenable the rational design of next-generation inhibitors with improved pharmacological profiles. Overall, this reviewunderscores how modern SBDD methodologies continue to advance kinase inhibitor discovery by addressinglongstanding challenges related to selectivity, resistance, and off-target effects, ultimately contributing tothedevelopment of safer and more effective therapeutic agents.
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