A computational analysis of in vivo VEGFR activation by multiple co-expressed ligands.
The splice isoforms of vascular endothelial growth A (VEGF) each have different affinities for the extracellular matrix (ECM) and the coreceptor NRP1, which leads to distinct vascular phenotypes in model systems expressing only a single VEGF isoform. ECM-immobilized VEGF can bind to and activate VEGF receptor 2 (VEGFR2) directly, with a different pattern of site-specific phosphorylation than diffusible VEGF. To date, the way in which ECM binding alters the distribution of isoforms of VEGF and of the related placental growth factor (PlGF) in the body and resulting angiogenic signaling is not well-understood. Here, we extend our previous validated cell-level computational model of VEGFR2 ligation, intracellular trafficking, and site-specific phosphorylation, which captured differences in signaling by soluble and immobilized VEGF, to a multi-scale whole-body framework. This computational systems pharmacology model captures the ability of the ECM to regulate isoform-specific growth factor distribution distinctly for VEGF and PlGF, and to buffer free VEGF and PlGF levels in tissue. We show that binding of immobilized growth factor to VEGF receptors, both on endothelial cells and soluble VEGFR1, is likely important to signaling in vivo. Additionally, our model predicts that VEGF isoform-specific properties lead to distinct profiles of VEGFR1 and VEGFR2 binding and VEGFR2 site-specific phosphorylation in vivo, mediated by Neuropilin-1. These predicted signaling changes mirror those observed in murine systems expressing single VEGF isoforms. Simulations predict that, contrary to the 'ligand-shifting hypothesis,' VEGF and PlGF do not compete for receptor binding at physiological concentrations, though PlGF is predicted to slightly increase VEGFR2 phosphorylation when over-expressed by 10-fold. These results are critical to design of appropriate therapeutic strategies to control VEGF availability and signaling in regenerative medicine applications.
Institute for Computational Medicine, Institute for NanoBioTechnology, and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
Lindsay E
0000-0001-8558-9341
LE
Clegg
Institute for Computational Medicine, Institute for NanoBioTechnology, and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.|Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
Feilim
0000-0003-3481-7740
F
Mac Gabhann
D003198:Computer Simulation; D016326:Extracellular Matrix Proteins / Q000378:metabolism*; D006801:Humans; D008565:Membrane Proteins / Q000378:metabolism*; D008956:Models, Chemical; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods; D014018:Tissue Distribution; D042461:Vascular Endothelial Growth Factor A / Q000378:metabolism*; D040281:Vascular Endothelial Growth Factor Receptor-1 / Q000378:metabolism*; D040301:Vascular Endothelial Growth Factor Receptor-2 / Q000378:metabolism*
D016326:Extracellular Matrix Proteins; D008565:Membrane Proteins; C098069:PIGF protein, human; C467484:VEGFA protein, human; D042461:Vascular Endothelial Growth Factor A; C000588866:KDR protein, human; D040281:Vascular Endothelial Growth Factor Receptor-1; D040301:Vascular Endothelial Growth Factor Receptor-2