Pharmacological translation of cancer missense mutations for therapeutic targeting with small molecules

Targeted therapies built around specific genetic driver mutations have become a cornerstone of precision oncology. These mutations, often found in oncogenes such as Kirsten rat sarcoma (KRAS) or tumor suppressors such as TP53, contribute to tumor initiation, progression, and therapeutic resistance. Recent successes with KRAS inhibitors targeting G12C and G12D mutations highlight the clinical potential of mutation-specific drug design. Concurrently, advances in machine learning have enhanced predictions of missense variant effects by integrating amino acid dynamics, structural perturbations, and pathogenicity scores. This review synthesizes current computational tools and emerging therapeutic small-molecule inhibitors, protein degraders, and proximity-based therapeutics to provide a comprehensive framework that links structure-function relationships to the rational design of next-generation cancer treatments.