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BioE Seminar: “Peering into the “black-box” of protein signaling: quantifying protein-protein interaction kinetics and protein concentrations to computationally predict cell response?”

Seminar: BioE Seminars: Seminars of interest | February 22 | 12-1 p.m. | 290 Hearst Memorial Mining Building


Princess Imoukhuede, University of Illinois -- Urbana Champaign

Bioengineering (BioE)


Spring 2017 Seminar Series

Wednesday, February 22
12noon - 1:00pm
290 Hearst Mining Building

“Peering into the “black-box” of protein signaling:
quantifying protein-protein interaction kinetics and protein concentrations to computationally predict cell response?”

Princess Imoukhuede
Assistant Professor of Bioengineering
University of Illinois -- Urbana Champaign

Directed control of angiogenesis can improve the treatment of over 70 diseases. Understanding how to control angiogenesis can be achieved by deterministic computational modeling that both mathematically describes angiogenic signaling pathways and simulates how these pathways will respond to biological perturbations. Towards this goal, we have arrived at three key advancements: (1) development of multiplexed fluorescent sensors of angiogenic protein concentrations, (2) discovery and measurement of new protein-protein interaction (PPI) kinetics; and (3) computational simulation of angiogenic signaling, which predicts VEGFR-mediated second messenger phosphorylation, cell proliferation, and cell migration.

Our approaches are advancing us towards the much needed goal of directed angiogenic control. Firstly, our multiplexed fluorescence sensors are establishing a new method for quantifying angiogenesis biomarkers, 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 novel PPIs represents a paradigm shift, where kinetics, not protein family, defines our view of protein function. More immediately, these kinetic measurements provide the necessary data for predictive modeling. Finally, our computational models are integrating each of the aforementioned parameters and providing validated predictions of angiogenic cell response.

This material is based upon work supported by the National Science Foundation under Grant #1512598. This work was also supported by American Heart Association Grant #16SDG26940002.


510-642-5833