Literature DB >> 30935841

General mathematical formula for near equilibrium relaxation kinetics of basic enzyme reactions and its applications to find conformational selection steps.

Tsuyoshi Egawa1, Robert Callender2.   

Abstract

A general mathematical formula of basic enzyme reactions was derived with nearly no dependence on conditions nor assumptions on relaxation kinetic processes near equilibrium in a simple single-substrate-single-product enzyme reaction. The new formula gives precise relationships between the rate constants of the elementary reaction steps and the apparent relaxation rate constant, rather than the initial velocity that is generally used to determine enzymatic parameters according to the Michaelis-Menten theory. The present formula is shown to be complementary to the Michaelis-Menten formulae in a sense that the initial velocity and the relaxation rate constant data together could determine the enzyme-substrate dissociation constant KES, which has been usually conditionally approximated by the Michaelis constant KM within the framework of the Michaelis-Menten formulae. We also describe relaxation kinetics of enzyme reactions that include the conformational selection processes, in which only one enzymatic conformer among a conformational ensemble can bind with either the substrate or product. The present mathematical approaches, together with numerical computation analyses, suggested that the presence of conformational selection steps in enzymatic reactions can be experimentally detected simply by enzymatic assays with catalytic amounts of enzyme.
Copyright © 2019 Elsevier Inc. All rights reserved.

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Year:  2019        PMID: 30935841      PMCID: PMC6792049          DOI: 10.1016/j.mbs.2019.03.007

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  20 in total

1.  Enzyme kinetics at high enzyme concentration.

Authors:  S Schnell; P K Maini
Journal:  Bull Math Biol       Date:  2000-05       Impact factor: 1.758

2.  Antigen recognition by conformational selection.

Authors:  C Berger; S Weber-Bornhauser; J Eggenberger; J Hanes; A Plückthun; H R Bosshard
Journal:  FEBS Lett       Date:  1999-04-30       Impact factor: 4.124

3.  Michaelis-Menten kinetics at high enzyme concentrations.

Authors:  A R Tzafriri
Journal:  Bull Math Biol       Date:  2003-11       Impact factor: 1.758

4.  From induced fit to conformational selection: a continuum of binding mechanism controlled by the timescale of conformational transitions.

Authors:  Huan-Xiang Zhou
Journal:  Biophys J       Date:  2010-03-17       Impact factor: 4.033

5.  The dynamic energy landscape of dihydrofolate reductase catalysis.

Authors:  David D Boehr; Dan McElheny; H Jane Dyson; Peter E Wright
Journal:  Science       Date:  2006-09-15       Impact factor: 47.728

6.  Extending the quasi-steady state approximation by changing variables.

Authors:  J A Borghans; R J de Boer; L A Segel
Journal:  Bull Math Biol       Date:  1996-01       Impact factor: 1.758

Review 7.  Essential role of conformational selection in ligand binding.

Authors:  Austin D Vogt; Nicola Pozzi; Zhiwei Chen; Enrico Di Cera
Journal:  Biophys Chem       Date:  2013-09-25       Impact factor: 2.352

8.  Two rules of enzyme kinetics for reversible Michaelis-Menten mechanisms.

Authors:  T Keleti
Journal:  FEBS Lett       Date:  1986-11-10       Impact factor: 4.124

9.  Molecular dynamics simulations show that conformational selection governs the binding preferences of imatinib for several tyrosine kinases.

Authors:  Alexey Aleksandrov; Thomas Simonson
Journal:  J Biol Chem       Date:  2010-03-03       Impact factor: 5.157

Review 10.  The role of dynamic conformational ensembles in biomolecular recognition.

Authors:  David D Boehr; Ruth Nussinov; Peter E Wright
Journal:  Nat Chem Biol       Date:  2009-11       Impact factor: 15.040

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