2016 Conference on Computational Modelling with COPASI
Manchester Institute of Biotechnology, 12th – 13th May, 2016

In silico simulation of chronic oxidative stress interference with redox signalling

Alvaro Martinez Guimera1, Viktor Korolchuk1, Carole Proctor1, Daryl Shanley1

1 - Newcastle University, UK

Keywords: systems modelling, Nrf2 signalling, oxidative stress, skeletal muscle


Redox signalling underlies a number of beneficial responses triggered by skeletal muscle during a period of exercise. Aged skeletal muscle is associated with a state of damage and oxidative stress where the protective responses triggered by an exercise stimulus are blunted. However, it is mechanistically unclear if oxidative stress is the direct causative agent of the impaired redox signalling. The elucidation of the nature of this signalling dysfunctionality in skeletal muscle is a step towards improving the efficacy of exercise as a lifestyle intervention for the elderly.

Numerous ordinary differential equation (ODE) -based models have been constructed in an effort to understand the behaviour of redox signalling networks. The ability of these models to reproduce experimental data in a variety of biological settings argues for the employment of such methods to integrate experimental data into a coherent in silico physicochemical framework that aids the interpretation of such data and the generation of new hypotheses.

In this work we employ COPASI to create a simple kinetic model of Nrf2 signalling, which we calibrate with experimental data derived from C2C12 myotubes. We further explore in silico potential mechanisms of oxidative stress interference with signalling within the network.

Conference Program