Misuse of the Michaelis-Menten rate law for protein interaction networks and its remedy

Area of Science:

• Biochemistry
• Systems Biology
• Computational Biology

Background:

• The Michaelis-Menten (MM) rate law has been a cornerstone in enzyme kinetics and gene expression modeling for over a century.
• Its accurate application relies on the substrate being in large excess over the enzyme-substrate complex, a condition often unmet in complex biological systems like protein interaction networks.

Purpose of the Study:

• To highlight the inaccuracies and misinterpretations arising from the misuse of the MM rate law in biochemical modeling.
• To introduce and advocate for the total quasi-steady state approximation (tQSSA) as a robust alternative.
• To demonstrate the benefits of tQSSA for accurate and computationally efficient simulations.

Main Methods:

• Reviewing the limitations and common misapplications of the Michaelis-Menten rate law.
• Illustrating the distortions in system dynamics, parameter estimation, and prediction of features like ultrasensitivity and bistability caused by MM law misuse.
• Describing the implementation and advantages of the total quasi-steady state approximation (tQSSA).

Main Results:

• Inappropriate use of the MM rate law leads to distorted system dynamics, inaccurate parameter estimates, and false predictions of key biological features.
• The tQSSA resolves these issues by providing a more accurate representation of biochemical reaction dynamics.
• tQSSA enables accurate stochastic simulations with reduced computational cost compared to full mass-action models.

Conclusions:

• The MM rate law's validity is conditional; its misuse can lead to erroneous conclusions in computational simulations.
• The tQSSA offers a reliable and computationally efficient method for modeling biochemical systems, particularly when MM assumptions are violated.
• Proper application of quasi-steady state approximations is crucial for drawing valid conclusions from in silico studies.