Development of a High-Fidelity Kinetic Modeling Framework for Quantifying nNOS Uncoupling and Cellular Redox Homeostasis

March 31, 2026
11:00 am

Speaker: Amnah Allboani

The transition of neuronal nitric oxide synthase (nNOS) from a signaling enzyme to a source of oxidative stress is a hallmark of neurodegeneration, yet the precise biochemical “tipping points” remain difficult to quantify in vivo. This presentation introduces a mechanistic computational framework developed to simulate the intricate biochemical pathways of nNOS.

Using mass-action kinetics and system-level differential equations (ODEs), this model combines nNOS enzyme cycling with downstream reactive oxygen and nitrogen species (ROS/RNS) flux, substrate competition, and cofactor availability. As part of a larger research effort involving three distinct biological models, this structure enables the identification of critical oxidative stress thresholds and the simulation of in silico therapeutic interventions.

The methodological challenges in building this platform will be discussed, including integrating experimental rate constants into a stable numerical solver and using sensitivity analysis to assess the impact of biopterin synthesis on redox balance. This work establishes a scalable computational foundation for predicting enzymatic dysfunction and evaluating multi-target antioxidant therapies in complex neuronal environments.

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