Literature DB >> 27677118

On the estimation errors of KM and V from time-course experiments using the Michaelis-Menten equation.

Wylie Stroberg1, Santiago Schnell2.   

Abstract

The conditions under which the Michaelis-Menten equation accurately captures the steady-state kinetics of a simple enzyme-catalyzed reaction is contrasted with the conditions under which the same equation can be used to estimate parameters, KM and V, from progress curve data. Validity of the underlying assumptions leading to the Michaelis-Menten equation are shown to be necessary, but not sufficient to guarantee accurate estimation of KM and V. Detailed error analysis and numerical "experiments" show the required experimental conditions for the independent estimation of both KM and V from progress curves. A timescale, tQ, measuring the portion of the time course over which the progress curve exhibits substantial curvature provides a novel criterion for accurate estimation of KM and V from a progress curve experiment. It is found that, if the initial substrate concentration is of the same order of magnitude as KM, the estimated values of the KM and V will correspond to their true values calculated from the microscopic rate constants of the corresponding mass-action system, only so long as the initial enzyme concentration is less than KM.
Copyright © 2016 Elsevier B.V. All rights reserved.

Keywords:  Experimental design; Inverse problem; Parameter estimation; Reproducibility

Mesh:

Substances:

Year:  2016        PMID: 27677118     DOI: 10.1016/j.bpc.2016.09.004

Source DB:  PubMed          Journal:  Biophys Chem        ISSN: 0301-4622            Impact factor:   2.352


  12 in total

1.  A confidence building exercise in data and identifiability: Modeling cancer chemotherapy as a case study.

Authors:  Marisa C Eisenberg; Harsh V Jain
Journal:  J Theor Biol       Date:  2017-07-19       Impact factor: 2.691

2.  Phase-plane geometries in coupled enzyme assays.

Authors:  Justin Eilertsen; Wylie Stroberg; Santiago Schnell
Journal:  Math Biosci       Date:  2018-09-24       Impact factor: 2.144

3.  Global optimization of the Michaelis-Menten parameters using physiologically-based pharmacokinetic (PBPK) modeling and chloroform vapor uptake data in F344 rats.

Authors:  Marina V Evans; Christopher R Eklund; David N Williams; Yusupha M Sey; Jane Ellen Simmons
Journal:  Inhal Toxicol       Date:  2020-04-02       Impact factor: 2.724

4.  Stamped multilayer graphene laminates for disposable in-field electrodes: application to electrochemical sensing of hydrogen peroxide and glucose.

Authors:  Loreen R Stromberg; John A Hondred; Delaney Sanborn; Deyny Mendivelso-Perez; Srikanthan Ramesh; Iris V Rivero; Josh Kogot; Emily Smith; Carmen Gomes; Jonathan C Claussen
Journal:  Mikrochim Acta       Date:  2019-07-15       Impact factor: 5.833

5.  On the Validity of the Stochastic Quasi-Steady-State Approximation in Open Enzyme Catalyzed Reactions: Timescale Separation or Singular Perturbation?

Authors:  Justin Eilertsen; Santiago Schnell
Journal:  Bull Math Biol       Date:  2021-11-26       Impact factor: 1.758

6.  The quasi-steady-state approximations revisited: Timescales, small parameters, singularities, and normal forms in enzyme kinetics.

Authors:  Justin Eilertsen; Santiago Schnell
Journal:  Math Biosci       Date:  2020-03-14       Impact factor: 2.144

7.  Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parameters.

Authors:  Boseung Choi; Grzegorz A Rempala; Jae Kyoung Kim
Journal:  Sci Rep       Date:  2017-12-05       Impact factor: 4.379

8.  Using singular perturbation theory to determine kinetic parameters in a non-standard coupled enzyme assay.

Authors:  Mohit P Dalwadi; Diego Orol; Frederik Walter; Nigel P Minton; John R King; Katalin Kovács
Journal:  J Math Biol       Date:  2020-08-06       Impact factor: 2.259

Review 9.  Enzyme Kinetics by Isothermal Titration Calorimetry: Allostery, Inhibition, and Dynamics.

Authors:  Yun Wang; Guanyu Wang; Nicolas Moitessier; Anthony K Mittermaier
Journal:  Front Mol Biosci       Date:  2020-10-19

Review 10.  Misuse of the Michaelis-Menten rate law for protein interaction networks and its remedy.

Authors:  Jae Kyoung Kim; John J Tyson
Journal:  PLoS Comput Biol       Date:  2020-10-22       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.