How can EnzymeML help you developing, implementing and analysing models? Here we present you one example to illustrate the power of EnzymeML for modelers.
Kinetic modeling of EnzymeML data with COPASI
Experimental data on enzyme kinetics (reaction conditions, enzyme concentration, time course of substrate and product concentrations) is stored in a single EnzymeML document and can uploaded to the biochemical system simulator COPASI. Within COPASI, different reaction mechanisms can be tested by selecting different kinetic laws and estimating kinetic parameters. The selected kinetic model and the estimated kinetic parameters are then added to the EnzymeML document.
COPASI can also be used to simulate the time course of a reaction, assuming a kinetic model and kinetic parameters. A kinetic model and kinetic parameters can be stored in an EnzymeML document and loaded to COPASI. The simulated time course of substrate and product concentrations are then added to the EnzymeML document.
Tools to integrate EnzymeML with COPASI
You can easily implement an EnzymeML read and write functionality in CPOPASI. You will only need to use a specific thin API layer to map EnzymeML objects to COPASI, and then use our API containing a Python and a Java library – JEnzyme and PyEnzyme.