Interleukin-3 (IL-3) is a pivotal cytokine in immune regulation, making it a compelling target for therapeutic intervention in immune-related disorders. This study employs an integrative computational approach, combining site-directed mutagenesis, molecular dynamics simulations, and protein-protein docking, to systematically investigate the structural and functional consequences of IL-3 mutations. By mapping disease-associated variants and their mechanistic impact on IL-3 receptor (IL-3Rα) interactions, we uncover critical determinants of cytokine signaling and stability. Our findings reveal that mutations such as E41L, R127L, and W123E induce structural perturbations linked to disease phenotypes, underscoring their potential as therapeutic targets. Conversely, variants like H45R, D40A, and N124D exhibit altered receptor-binding affinities, presenting opportunities for rational drug design. Protein-protein docking further elucidates the molecular basis of IL-3Rα recognition, highlighting key residues that govern binding specificity. Notably, mutations affecting interface residues drive substantial changes in binding energetics, providing novel insights into IL-3-mediated signaling modulation. This study advances the understanding of IL-3 structural dynamics through a computational lens, offering a predictive framework for mutation-driven functional alterations. By integrating biophysical modeling with functional annotation, we establish a foundation for precision engineering of IL-3 variants with therapeutic potential. Despite the inherent limitations of in silico modeling, our approach provides preliminary computational insights into cytokine modulation and forms a foundation for future experimental validation aimed at exploring potential therapeutic avenues for IL-3-associated pathologies
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