ReviewPLoS computational biology2020
Misuse of the Michaelis-Menten rate law for protein interaction networks and its remedy.
Review in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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42 citing papers in PubMed.
- Beyond the Michaelis-Menten: Evaluation of a tQSSA-Based IVIVE Approach for Predicting In Vivo Intrinsic Clearance From Hepatocyte Assays.CPT: pharmacometrics & systems pharmacology · 2026Article
- Transcription Factor Promiscuity Drives Regulatory Rewiring and Evolvability in Gene Networks in Bacteria.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Exact Formula of the Total Quasi-Steady State Approximation in Competitive Target-Mediated Drug Disposition.Computational and structural biotechnology journal · 2026Article
- Enhancing viral dynamics modeling: reliable initial estimation and validity conditions for quasi-steady state approximation (QSSA).BMC biology · 2025Article
- Understanding Immune Dynamics in Liver Transplant Through Mathematical Modeling.Bulletin of mathematical biology · 2025Article
- Optimizing enzyme inhibition analysis: precise estimation with a single inhibitor concentration.Nature communications · 2025Article
- Preparation for mitosis requires gradual CDK1 activation.iScience · 2025Article
- Combining lineage correlations and a small molecule inhibitor to detect circadian control of the cell cycle.iScience · 2025Article
- Building Localized NADP(H) Recycling Circuits to Advance Enzyme Cascadetronics.Angewandte Chemie (International ed. in English) · 2025Article
- Origins of Ultrasensitivity and Complex Signaling Dynamics of Cellular Hydrogen Peroxide and Peroxiredoxin.Antioxidants (Basel, Switzerland) · 2025Article
- Determining interaction directionality in complex biochemical networks from stationary measurements.Scientific reports · 2025Article
- From homogeneity to heterogeneity: Refining stochastic simulations of gene regulation.Computational and structural biotechnology journal · 2025Article
- Optimizing the standardized assays for determining the catalytic activity and kinetics of peroxidase-like nanozymes.Nature protocols · 2024Article
- Newton's cradle: Cell cycle regulation by two mutually inhibitory oscillators.Mathematical biosciences · 2024Article
- Beyond homogeneity: Assessing the validity of the Michaelis-Menten rate law in spatially heterogeneous environments.PLoS computational biology · 2024Article
- Validity conditions of approximations for a target-mediated drug disposition model: A novel first-order approximation and its comparison to other approximations.PLoS computational biology · 2024Article
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- First-order ultrasensitivity in phosphorylation cycles.Interface focus · 2024Article
- Generalized Michaelis-Menten rate law with time-varying molecular concentrations.PLoS computational biology · 2023Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
For over a century, the Michaelis-Menten (MM) rate law has been used to describe the rates of enzyme-catalyzed reactions and gene expression. Despite the ubiquity of the MM rate law, it accurately captures the dynamics of underlying biochemical reactions only so long as it is applied under the right condition, namely, that the substrate is in large excess over the enzyme-substrate complex. Unfortunately, in circumstances where its validity condition is not satisfied, especially so in protein interaction networks, the MM rate law has frequently been misused. In this review, we illustrate how inappropriate use of the MM rate law distorts the dynamics of the system, provides mistaken estimates of parameter values, and makes false predictions of dynamical features such as ultrasensitivity, bistability, and oscillations. We describe how these problems can be resolved with a slightly modified form of the MM rate law, based on the total quasi-steady state approximation (tQSSA). Furthermore, we show that the tQSSA can be used for accurate stochastic simulations at a lower computational cost than using the full set of mass-action rate laws. This review describes how to use quasi-steady state approximations in the right context, to prevent drawing erroneous conclusions from in silico simulations.
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