The Quasi-Steady State Assumption in an Enzymatically Open System
Ed Reznik, Daniel Segre, William Erik Sherwood

TL;DR
This paper extends the quasi-steady state assumption (QSSA) to enzymatically open systems with enzyme input and removal, providing new approximations, validity conditions, and analyzing oscillatory behavior in such systems.
Contribution
The authors develop a modified QSSA for open enzymatic systems, derive validity conditions, and compare approximations with full system dynamics across various parameters.
Findings
Approximations remain accurate even outside strict validity conditions.
Derived conditions ensure the validity of the new QSSA.
Numerical simulations reveal potential for damped oscillations.
Abstract
The quasi-steady state assumption (QSSA) forms the basis for rigorous mathematical justification of the Michaelis-Menten formalism commonly used in modeling a broad range of intracellular phenomena. A critical supposition of QSSA-based analyses is that the underlying biochemical reaction is enzymatically "closed," so that free enzyme is neither added to nor removed from the reaction over the relevant time period. Yet there are multiple circumstances in living cells under which this assumption may not hold, e.g. during translation of genetic elements or metabolic regulatory events. Here we consider a modified version of the most basic enzyme-catalyzed reaction which incorporates enzyme input and removal. We extend the QSSA to this enzymatically "open" system, computing inner approximations to its dynamics, and we compare the behavior of the full open system, our approximations, and the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsProtein Structure and Dynamics · Photosynthetic Processes and Mechanisms · Microbial Metabolic Engineering and Bioproduction
