Reduced models of networks of coupled enzymatic reactions

Physics – Mathematical Physics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

44 pages, 4 figures

Scientific paper

The Michaelis-Menten equation has played a central role in our understanding of biochemical processes. It has long been understood how this equation approximates the dynamics of irreversible enzymatic reactions. However, a similar approximation in the case of networks, where the product of one reaction can act as an enzyme in another, has not been fully developed. Here we rigorously derive such an approximation in a class of coupled enzymatic networks where the individual interactions are of Michaelis-Menten type. We show that the sufficient conditions for the validity of the total quasi steady state assumption (tQSSA), obtained in a single protein case by Borghans, de Boer and Segel can be extended to sufficient conditions for the validity of the tQSSA in a large class of enzymatic networks. Secondly, we derive reduced equations that approximate the network's dynamics and involve only protein concentrations. This significantly reduces the number of equations necessary to model such systems. We prove the validity of this approximation using geometric singular perturbation theory and results about matrix differentiation. The ideas used in deriving the approximating equations are quite general, and can be used to systematize other model reductions.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Reduced models of networks of coupled enzymatic reactions does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Reduced models of networks of coupled enzymatic reactions, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Reduced models of networks of coupled enzymatic reactions will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-398276

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.