Abstract

Vascular endothelial growth factor (VEGF) is an important regulator of blood vessel growth. Matrix-binding and non-matrix-binding isoforms of VEGF stimulate production of blood vessel networks that are structurally and functionally different. Here, we develop a computational model of the binding of soluble and immobilized ligands to VEGF receptor 2 (VEGFR2), endosomal trafficking of VEGFR2, and site-specific VEGFR2 tyrosine phosphorylation to study differences in induced signaling between these VEGF isoforms. We build our model using experimental data in multiple cell lines, under different conditions, from several groups. In capturing essential features of VEGFR2 signaling and trafficking, our model suggests that VEGFR2 trafficking parameters are largely consistent across multiple endothelial cell lines. Simulations demonstrate distinct cellular localization of VEGFR2 phosphorylated on tyrosines 1175 and 1214. This is the first model to clearly show that differences in site-specific VEGFR2 activation when stimulated with immobilized VEGF compared to soluble VEGF can be accounted for by altered trafficking of VEGFR2 without an intrinsic difference in receptor activation. The model predicts that Neuropilin-1 can induce differences in the surface-to-internal distribution of VEGFR2, and that ligated VEGFR2 and phosphorylated VEGFR2 levels diverge over time following stimulation. We validated our model by successfully predicting changes in VEGFR2 phosphorylation resulting from perturbations of multiple phosphatases acting on VEGFR2. Using this model, we identify multiple key levers that alter how VEGF binding to VEGFR2 results in different coordinated patterns of multiple downstream signaling pathways. Specifically, simulations predict that perturbations of VEGFR2 trafficking (e.g. via VEGF immobilization), interactions with Neuropilin-1, and changes in expression or activity of phosphatases acting on VEGFR2 all affect the magnitude, duration, and relative strength of VEGFR2 phosphorylation on Y1175 and Y1214, and they do so predictably within our single consistent model framework.

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