Maini's many contributions to mathematical enzyme kinetics: A review.


Journal

Journal of theoretical biology
ISSN: 1095-8541
Titre abrégé: J Theor Biol
Pays: England
ID NLM: 0376342

Informations de publication

Date de publication:
21 11 2019
Historique:
received: 23 07 2018
revised: 29 11 2018
accepted: 03 12 2018
pubmed: 17 12 2018
medline: 13 8 2020
entrez: 17 12 2018
Statut: ppublish

Résumé

Modelling enzyme kinetics has a long history, as one of the earliest areas where mathematics was utilized to understand biological (in this case, biochemical) phenomena. By using differential equations and the law of mass action, many researchers have discovered information about the mechanisms of enzyme workings in the more than 100 years since Leonor Michaelis and Maud Menten published their classic paper in 1913. This work uses he laws obeyed by molecules during a reaction, translates them into mathematical equations, and then compares the results predicted by the equations to data obtained in laboratory conditions. This can inform whether the mechanism used to create the mathematical model is consistent with experimental results. Philip K. Maini has contributed to several significant results in the field of mathematical modelling in enzyme kinetics. Along with his collaborators, he has published results analyzing and extending the Quasi-Steady State Assumption, applying it to special enzyme reactions, and considering special conditions. This review paper will provide an overview of the contributions made by PK Maini to the field of modelling enzyme kinetics, summarize the main results and discuss their significance.

Identifiants

pubmed: 30553723
pii: S0022-5193(18)30593-9
doi: 10.1016/j.jtbi.2018.12.003
pii:
doi:

Substances chimiques

Enzymes 0

Types de publication

Historical Article Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

24-27

Informations de copyright

Copyright © 2018 Elsevier Ltd. All rights reserved.

Auteurs

Meghan A Burke (MA)

Department of Mathematics, Kennesaw State University, 370 Paulding Ave. NW Kennesaw. GA 30144, USA. Electronic address: mburke@kennesaw.edu.

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Classifications MeSH