Literature DB >> 19562082

Uses and misuses of progress curve analysis in enzyme kinetics.

Natalia Nikolova1, Kiril Tenekedjiev, Krasimir Kolev.   

Abstract

Progress curve analysis is a convenient tool for the characterization of enzyme action: a single reaction mixture provides multiple experimental measured points for continuously varying amounts of substrates and products with exactly the same enzyme and modulator concentrations. The determination of kinetic parameters from the progress curves, however, requires complex mathematical evaluation of the time-course data. Some freely available programs (e.g. FITSIM, DYNAFIT) are widely applied to fit kinetic parameters to user-defined enzymatic mechanisms, but users often overlook the stringent requirements of the analytic procedures for appropriate design of the input experiments. Flaws in the experimental setup result in unreliable parameters with consequent misinterpretation of the biological phenomenon under study. The present commentary suggests some helpful mathematical tools to improve the analytic procedure in order to diagnose major errors in concept and design of kinetic experiments.

Entities:  

Year:  2008        PMID: 19562082      PMCID: PMC2701647          DOI: 10.2478/s11535-008-0035-4

Source DB:  PubMed          Journal:  Cent Eur J Biol        ISSN: 1895-104X


  7 in total

1.  Quantitative analysis of the time courses of enzyme-catalyzed reactions.

Authors:  R G Duggleby
Journal:  Methods       Date:  2001-06       Impact factor: 3.608

2.  Monte Carlo method for determining complete confidence probability distributions of estimated model parameters.

Authors:  M Straume; M L Johnson
Journal:  Methods Enzymol       Date:  1992       Impact factor: 1.600

3.  Program DYNAFIT for the analysis of enzyme kinetic data: application to HIV proteinase.

Authors:  P Kuzmic
Journal:  Anal Biochem       Date:  1996-06-01       Impact factor: 3.365

4.  Analysis of progress curves by simulations generated by numerical integration.

Authors:  C T Zimmerle; C Frieden
Journal:  Biochem J       Date:  1989-03-01       Impact factor: 3.857

5.  The effect of systematic error on the accuracy of Michaelis constants and maximum velocities estimated by using the integrated Michaelis-Menten equation.

Authors:  P F Newman; G L Atkins; I A Nimmo
Journal:  Biochem J       Date:  1974-12       Impact factor: 3.857

6.  Missense mutations in pancreatic secretory trypsin inhibitor (SPINK1) cause intracellular retention and degradation.

Authors:  Orsolya Király; Thomas Wartmann; Miklós Sahin-Tóth
Journal:  Gut       Date:  2007-05-24       Impact factor: 23.059

7.  Suppressed catalytic efficiency of plasmin in the presence of long-chain fatty acids. Identification of kinetic parameters from continuous enzymatic assay with Monte Carlo simulation.

Authors:  Anna Tanka-Salamon; Kiril Tenekedjiev; Raymund Machovich; Krasimir Kolev
Journal:  FEBS J       Date:  2008-02-12       Impact factor: 5.542

  7 in total
  5 in total

1.  Involvement of the host DNA-repair enzyme TDP2 in formation of the covalently closed circular DNA persistence reservoir of hepatitis B viruses.

Authors:  Christian Königer; Ida Wingert; Moritz Marsmann; Christine Rösler; Jürgen Beck; Michael Nassal
Journal:  Proc Natl Acad Sci U S A       Date:  2014-09-08       Impact factor: 11.205

2.  Asymmetric reduction of ketones and β-keto esters by (S)-1-phenylethanol dehydrogenase from denitrifying bacterium Aromatoleum aromaticum.

Authors:  A Dudzik; W Snoch; P Borowiecki; J Opalinska-Piskorz; M Witko; J Heider; M Szaleniec
Journal:  Appl Microbiol Biotechnol       Date:  2014-12-31       Impact factor: 4.813

3.  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

4.  The Removal of Time-Concentration Data Points from Progress Curves Improves the Determination of Km: The Example of Paraoxonase 1.

Authors:  Boštjan Petrič; Marko Goličnik; Aljoša Bavec
Journal:  Molecules       Date:  2022-02-15       Impact factor: 4.411

5.  Improved inhibitor screening experiments by comparative analysis of simulated enzyme progress curves.

Authors:  Fredrik Tholander
Journal:  PLoS One       Date:  2012-10-10       Impact factor: 3.240

  5 in total

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