The Angiopoietin‐Tie (Ang‐Tie) pathway is a key signaling pathway regulating vascular stability and permeability, and it significantly intersects and crosstalk with the vascular endothelial growth factor (VEGF) signaling pathway, a major signaling pathway regulating angiogenesis and vascular permeability. Disrupted Ang‐Tie and VEGF signaling is linked to vascular dysfunction related to cancer, systemic inflammation, cardiovascular disease, and diabetic macular edema. Ang‐Tie pathway is regulated by various molecular mechanisms, including ligand‐receptor interactions, receptor multimerization, binding of co‐receptor Tie1, inhibition by vascular endothelial protein tyrosine phosphatase (VE‐PTP), receptor extracellular domain shedding, junctional localization, trafficking, and turnover. VEGF pathway is regulated by ligand binding, homo‐ and heterodimerization of VEGF receptors VEGFR1 and VEGFR2, interaction with neuropilin, thrombospondin‐1/CD47, receptor internalization, recycling, and degradation. Ang‐Tie and VEGF signaling pathways also share crosstalk mechanisms and integrative downstream signaling through phosphoinositide 3‐kinases (PI3K)/Akt, sphingosine‐dependent Erk activation, Src sequestration via RhoA/mDia, and calcium cycling, forming a complex reaction network that requires an integrative model to study the signaling outcomes on a systems level. The present study uses a mechanistic computational model of the Ang‐Tie and VEGF signaling pathways, their regulatory mechanisms, crosstalk, and integrative downstream signaling to quantitatively characterize the molecular control of vascular growth, permeability, and stability by endothelial cells. The model captures and reproduces key experimental observations of the Ang‐Tie/VEGF signaling network with detailed molecular mechanisms. The model significantly expands our previous computational models of the Ang‐Tie signaling pathway [1,2] and integrates our systems biology understanding of the VEGF pathway and their crosstalk. The model serves as a platform for quantitatively predicting the signaling outcome of varying ligand concentrations and receptor expressions in physiological and pathological conditions, identifying molecular mechanisms and targets for therapeutic interventions targeting the signaling network, and simulating the effects of drugs and their combinations on the signaling outcome on a network level.
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