Smooth signals: computational insights into autonomic vascular control

The regulation of vascular tone underlies normal cardiovascular homeostasis, ensuring appropriate distribution of blood flow to tissues and maintenance of blood pressure. Computational modeling and simulation constitute a powerful framework for deciphering plausible mechanisms of autonomic signaling in vascular smooth muscle across spatial and temporal scales and allow for the prediction of emergent nonlinear effects of perturbations. Integrative computational modeling approaches are now beginning to inform the precision use of calcium channel blockers, angiotensin II type 1 receptor antagonists, and lipid-modulating therapies in cardiovascular disease. By simulating system-level behavior under physiological and pathological conditions, computational models have the potential to enhance drug discovery, guide individualized treatment strategies, and generate testable hypotheses for experimental validation. This review highlights key molecular mechanisms, emerging modeling tools, and future directions for computational approaches to autonomic signaling in vascular smooth muscle.