Literature DB >> 30209711

Michaelis-Menten from an In Vivo Perspective: Open Versus Closed Systems.

Johan Gabrielsson1, Lambertus A Peletier2.   

Abstract

After a century of applications of the seminal Michaelis-Menten equation since its advent it is timely to scrutinise its principal parts from an in vivo point of view. Thus, the Michaelis-Menten system was revisited in which enzymatic turnover, i.e. synthesis and elimination was incorporated. To the best of our knowledge, previous studies of the Michaelis-Menten system have been mainly based on the assumption that the total pool of enzyme, free and bound, is constant. However, in fact this may not always be the case, particularly for chronic indications. Chronic (periodic) administration of drugs is often related to induction or inhibition of enzymatic processes and even changes in the free enzymatic load per se. This may account for the fact that translation of in vitro metabolism data have shown to give systematic deviations from experimental in vivo data. Interspecies extrapolations of metabolic data are often challenged by poor predictability due to insufficient power of applied functions and methods. By incorporating enzyme turnover, a more mechanistic expression of substrate, free enzyme and substrate-enzyme complex concentrations is derived. In particular, it is shown that whereas in closed systems there is a threshold for chronic dosing beyond which the substrate concentration keeps rising, in open systems involving enzyme turnover this is no longer the case. However, in the presence of slow enzyme turnover, after an initial period of adjustment which may be quite long, the relation between substrate concentration and dose rate reduces to a linear expression. This new open framework is also applicable to transporter systems.

Keywords:  Michaelis-Menten kinetics; enzyme turnover; pharmacodynamics; pharmacokinetics; transporters

Mesh:

Substances:

Year:  2018        PMID: 30209711     DOI: 10.1208/s12248-018-0256-z

Source DB:  PubMed          Journal:  AAPS J        ISSN: 1550-7416            Impact factor:   4.009


  18 in total

1.  Pharmacokinetic Steady-States Highlight Interesting Target-Mediated Disposition Properties.

Authors:  Johan Gabrielsson; Lambertus A Peletier
Journal:  AAPS J       Date:  2017-01-31       Impact factor: 4.009

2.  Kinetic models of induction: I. Persistence of the inducing substance.

Authors:  F P Abramson
Journal:  J Pharm Sci       Date:  1986-03       Impact factor: 3.534

3.  Time-dependent kinetics. VI: Direct relationship between equations for drug levels during induction and those involving constant clearance.

Authors:  R H Levy; M S Dumain
Journal:  J Pharm Sci       Date:  1979-07       Impact factor: 3.534

4.  Clearance concepts in pharmacokinetics.

Authors:  M Rowland; L Z Benet; G G Graham
Journal:  J Pharmacokinet Biopharm       Date:  1973-04

5.  Comparison of four basic models of indirect pharmacodynamic responses.

Authors:  N L Dayneka; V Garg; W J Jusko
Journal:  J Pharmacokinet Biopharm       Date:  1993-08

Review 6.  Clearance (née Rowland) concepts: a downdate and an update.

Authors:  Leslie Z Benet
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-11-27       Impact factor: 2.745

Review 7.  Cytochrome p450 turnover: regulation of synthesis and degradation, methods for determining rates, and implications for the prediction of drug interactions.

Authors:  Jiansong Yang; Mingxiang Liao; Magang Shou; Masoud Jamei; Karen Rowland Yeo; Geoffrey T Tucker; Amin Rostami-Hodjegan
Journal:  Curr Drug Metab       Date:  2008-06       Impact factor: 3.731

8.  Slow recovery of human brain MAO B after L-deprenyl (Selegeline) withdrawal.

Authors:  J S Fowler; N D Volkow; J Logan; G J Wang; R R MacGregor; D Schyler; A P Wolf; N Pappas; D Alexoff; C Shea
Journal:  Synapse       Date:  1994-10       Impact factor: 2.562

9.  Metabolic turnover of synaptic proteins: kinetics, interdependencies and implications for synaptic maintenance.

Authors:  Laurie D Cohen; Rina Zuchman; Oksana Sorokina; Anke Müller; Daniela C Dieterich; J Douglas Armstrong; Tamar Ziv; Noam E Ziv
Journal:  PLoS One       Date:  2013-05-02       Impact factor: 3.240

10.  Systematic analysis of protein turnover in primary cells.

Authors:  Toby Mathieson; Holger Franken; Jan Kosinski; Nils Kurzawa; Nico Zinn; Gavain Sweetman; Daniel Poeckel; Vikram S Ratnu; Maike Schramm; Isabelle Becher; Michael Steidel; Kyung-Min Noh; Giovanna Bergamini; Martin Beck; Marcus Bantscheff; Mikhail M Savitski
Journal:  Nat Commun       Date:  2018-02-15       Impact factor: 14.919

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  1 in total

1.  Application of modified Michaelis - Menten equations for determination of enzyme inducing and inhibiting drugs.

Authors:  Saganuwan Alhaji Saganuwan
Journal:  BMC Pharmacol Toxicol       Date:  2021-10-11       Impact factor: 2.483

  1 in total

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