Poster Presentation 2014 International Biophysics Congress

Generalised enzyme kinetics model for signalling systems (#679)

Martin K.L. Wong 1 , James Krycer 2 , James Burchfield 2 , David James 2 , Zdenka Kuncic 3
  1. Integrative Systems Lab, University of Sydney, Sydney, NSW, Australia
  2. Diabetes and Obesity Program, Gravan Institute of Medical Research, Sydney, NSW, Australia
  3. Institute of Medical Physics, University of Sydney, Sydney, NSW, Australia

Background: Cellular signalling systems are dominated by enzyme-mediated chemical reactions, so signalling systems can only be reliably modelled if the underlying enzyme kinetic model is simple and accurate. The traditional Michaelis Menten model is accurate at low enzyme concentrations but it is unclear to what extent this remains valid in vivo. Hence, we developed an enzyme kinetic model that is universally accurate whilst retaining the simplicity of the Michaelis Menten model.

Method: The mass action enzyme kinetic model was analysed using a more rigorous definition of the quasi-steady state. The resulting form was linearised to achieve a generalised model that can incorporate networks of any complexity. The model was then validated: in silico by comparing the time courses and dose responses generated by this model, the mass action model and the Michaelis Menten model; and in vitro by verifying the steady state of the reaction interconversion of pyruvate and lactate at a different concentrations of lactate dehydrogenase.

Results: The linearised quasi-steady state enzyme kinetic model matched the time course and dose response of the mass action enzyme kinetic model in silico while the Michaelis Menten model was different at high enzyme concentrations. The in vitro results are still forthcoming.

Conclusion: The linearised quasi-steady state enzyme kinetic model successfully replicates the steady state and time course of the mass action model at all enzyme concentrations.