CD40-Immunosome: A Systems Modeling Framework for CD40–TRAF6 Signaling and CRISPR Synergy

Background: The CD40–TRAF6 signaling axis regulates dendritic cell activation through tightly controlled NF-κB dynamics. The signal amplitude and duration are governed by intracellular negative feedback mechanisms, particularly SOCS1-mediated attenuation. Understanding how structural clustering and genetic perturbations reshape these dynamics requires mechanistic modeling. Methods: We developed the CD40-Immunosome, an interactive systems immunology framework integrating a three-variable ordinary differential equation (ODE) model of TRAF6, NF-κB, and SOCS1 kinetics. The platform implements (i) null-model comparison without feedback, (ii) stochastic Monte Carlo robustness analysis under ±20% parameter perturbations, and (iii) quantitative synergy scoring using area-under the-curve (AUC) metrics. Results: The feedback-enabled model produced transient NF-κB activation, followed by rapid attenuation, whereas the null model exhibited sustained activation consistent with chronic inflammatory dynamics. Monte Carlo simulations (n = 50) confirmed robustness to parameter perturbation (mean peak NF-κB = 1.59 ± 0.27 SD). Simulated SOCS1 deletion increased the cumulative signaling output by ∼ 3.2-fold relative to that of wild-type cells. Furthermore, structural stability simulations prioritized TMEM256 as a candidate modulator under modeled conditions. Conclusion: CD40-Immunosome provides a reproducible computational framework for exploring feedback-regulated immune signaling dynamics. The platform serves as a hypothesis-generating framework to support the mechanistic exploration of receptor clustering, structural perturbations, and targeted immunotherapies.