Your browser doesn't support javascript.
loading
An algebraic model to determine substrate kinetic parameters by global nonlinear fit of progress curves.
Reytor González, Mey Ling; Cornell-Kennon, Susan; Schaefer, Erik; Kuzmic, Petr.
Afiliação
  • Reytor González ML; BioKin Ltd., Watertown, MA, USA.
  • Cornell-Kennon S; AssayQuant Technologies Inc., Marlborough, MA, USA.
  • Schaefer E; AssayQuant Technologies Inc., Marlborough, MA, USA.
  • Kuzmic P; BioKin Ltd., Watertown, MA, USA. Electronic address: pksci01@biokin.com.
Anal Biochem ; 518: 16-24, 2017 Feb 01.
Article em En | MEDLINE | ID: mdl-27823930
ABSTRACT
We propose that the time course of an enzyme reaction following the Michaelis-Menten reaction mechanism can be conveniently described by a newly derived algebraic equation, which includes the Lambert Omega function. Following Northrop's ideas [Anal. Biochem.321, 457-461, 1983], the integrated rate equation contains the Michaelis constant (KM) and the specificity number (kS≡kcat/KM) as adjustable parameters, but not the turnover number kcat. A modification of the usual global-fit approach involves a combinatorial treatment of nominal substrate concentrations being treated as fixed or alternately optimized model parameters. The newly proposed method is compared with the standard approach based on the "initial linear region" of the reaction progress curves, followed by nonlinear fit of initial rates to the hyperbolic Michaelis-Menten equation. A representative set of three chelation-enhanced fluorescence EGFR kinase substrates is used for experimental illustration. In one case, both data analysis methods (linear and nonlinear) produced identical results. However, in another test case, the standard method incorrectly reported a finite (50-70 µM) KM value, whereas the more rigorous global nonlinear fit shows that the KM is immeasurably high.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2017 Tipo de documento: Article