4.5 Article

A method to describe enzyme-catalyzed reactions by combining steady state and time course enzyme kinetic parameters

Journal

BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS
Volume 1800, Issue 1, Pages 1-5

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.bbagen.2009.10.007

Keywords

beta-galactosidase; Enzyme kinetics; Equation modeling; Global data fitting

Funding

  1. Alzheimer Society of Nova Scotia
  2. Canadian Institutes of Health Research
  3. Vascular Health and Dementia Initiative (through the partnership of the Canadian Institutes of Health Research, the Heart & Stroke Foundation of Canada, the Alzheimer Society of Canada and Pfizer Canada Inc.) [DOV-78344]
  4. Natural Sciences and Engineering Research Council of Canada
  5. National Institute of Neurological Disorders and Stroke [NS057429]
  6. Capital District Health Authority Research Fund
  7. Nova Scotia Health Research Foundation
  8. Brain Tumour Foundation of Canada
  9. Committee on Research and Publications of Mount Saint Vincent University
  10. NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R21NS057429] Funding Source: NIH RePORTER

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Background: Complete analysis of single substrate enzyme-catalyzed reactions has required a separate use of two distinct approaches. Steady state approximations are employed to obtain substrate affinity and initial velocity information. Alternatively, first order exponential decay models permit simulation of the time course data for the reactions. Attempts to use integrals of steady state equations to describe reaction time courses have so far met with little success. Methods: Here we use equations based on steady state approximations to directly model time course plots. Results: Testing these expressions with the enzyme beta-galactosidase, which adheres to classical Michaelis-Menten kinetics, produced a good fit between observed and calculated values. General significance: This study indicates that, in addition to providing information on initial kinetic parameters, steady state approximations can be employed to directly model time course kinetics. Integrated forms of the Michaelis-Menten equation have previously been reported in the literature. Here we describe a method to directly apply steady state approximations to time course analysis for predicting product formation and simultaneously obtain multiple kinetic parameters. (C) 2009 Elsevier B.V. All rights reserved.

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