Systems Biology: Recipes for Advancing Predictive Biology

Directed control of angiogenesis can improve the treatment of over 70 diseases. We hypothesize that such control can be reached by computationally integrating two types of parameters: protein concentrations and protein-protein interaction (PPI) kinetics. In support of this hypothesis, we report three key advancements: (1) engineering of new quantitative fluorescent nanosensors (qFluors) to measure plasma membrane vascular endothelial growth factor receptor (VEGFR) (Fig. 1) and platelet derived growth factor receptor (PDGFR) concentrations and heterogeneity; (2) discovery and measurement of new cross-family interactions between PDGFs and VEGFR2 (Fig. 2); and (3) development of computational models that accurately predict VEGFR-mediated protein phosphorylation, cell proliferation, and cell migration (Fig. 3). Our approaches are advancing us towards the goal of directing the growth factor receptor signaling that underlies angiogenesis. Firstly, our qFluors are establishing a new method for quantifying biomarker heterogeneity, which can be translated to clinical pathology. More immediately, this approach is providing the receptor concentration data necessary for accurate computational model development. Additionally, our discovery and measurement of cross-family binding represents a paradigm shift, where PPI interaction kinetics, not family, define our view of protein function. More immediately, these kinetic measurements provide the necessary data for predicting cell responses. Finally, our computational models are integrating each of the parameters and providing validated predictions of angiogenic cell response. This material is based upon work supported by the National Science Foundation (NSF), American Heart Association (AHA), and American Cancer Society (ACS) under Grant #s: NSF CBET: 1512598; NSF CAREER: 1653925; NSF BPE: 1648454; AHA:16SDG26940002; and ACS-IL: 282802