Computational Modeling of ATM Signaling: A Predictive Framework for Drug Repurposing in Ataxia-telangiectasia

Ataxia-Telangiectasia (A-T) is a rare genetic disorder caused by ATM mutations, leading to impaired DNA repair, oxidative stress, and neurodegeneration. We developed a dynamic computational model of ATM-mediated signaling using ordinary differential equations in COPASI, capturing key molecular processes including DNA damage sensing, cell cycle regulation, autophagy, and oxidative stress response. The model simulates physiological, ATM-deficient, and drug-treated conditions to explore repurposing strategies. We evaluated the effects of spermidine, omaveloxolone, and HDAC4 inhibition, revealing distinct mechanisms by which these compounds modulate dysfunctional signaling. Sensitivity and stability analyses confirmed the model’s robustness, while enrichment analysis validated the involvement of key regulatory pathways. Our results highlight the synergistic potential of combining autophagy activation and epigenetic modulation to partially restore homeostasis in ATM-deficient cells. This work introduces a generalizable modeling framework for simulating disease-specific signaling dysfunction and identifying therapeutic interventions, illustrating the value of computational systems biology in rare disease drug repurposing.