2018
DOI: 10.12793/tcp.2018.26.1.39
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Comparison of various estimation methods for the parameters of Michaelis-Menten equation based on in vitro elimination kinetic simulation data

Abstract: The Michaelis-Menten equation is one of the best-known models describing the enzyme kinetics of in vitro drug elimination experiments, and takes a form of equation relating reaction rate (V) to the substrate concentration ([S]) via the maximum reaction rate (V max ) and the Michaelis constant (K m ). The current study was conducted to compare the accuracy and precision of the parameter estimates in the Michaelis-Menten equation from various estimation methods using simulated data. One thousand replicates of si… Show more

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Cited by 29 publications
(22 citation statements)
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“…6a), indicating inhibition by the substrate. Based on these data, kinetic constants were calculated with a non-linear model due to superior precision compared to linear methods like Lineweaver-Burk plots (Cho and Lim 2018). Phenylacetonitrile was converted at 37°C with a K M of 1.29 mM and V max of 13.85 U/mg, reaching the saturation point at 6 mM (Fig.…”
Section: Characterization Of Arylacetonitrilase Nit09mentioning
confidence: 99%
“…6a), indicating inhibition by the substrate. Based on these data, kinetic constants were calculated with a non-linear model due to superior precision compared to linear methods like Lineweaver-Burk plots (Cho and Lim 2018). Phenylacetonitrile was converted at 37°C with a K M of 1.29 mM and V max of 13.85 U/mg, reaching the saturation point at 6 mM (Fig.…”
Section: Characterization Of Arylacetonitrilase Nit09mentioning
confidence: 99%
“…It was clearly seen from Figure S4 that the obtained K m and V max from nonlinear Michaelis-Menten equation was shown better fit with the experimental results. This can be explained with the reported disadvantage of linearized Michaelis-Menten equations that results in poor estimation of K m andV max as it compresses data points at high substrate concentrations into a small region and highlights data at lower substrate concentrations (Cho and Lim, 2018;Hernández and Ruiz, 1998;Kemmer and Keller, 2010;Marasović et al, 2017).…”
Section: Kinetic Parametersmentioning
confidence: 99%
“…Con respecto a la linealización de Agustinson tiene una mejor distribución de datos entre las tres. Sin embargo, su principal inconveniente es que, de nuevo, ni las ordenadas ni las abscisas representan valores independientes, pues se denota dependencia de la concentración del sustrato y, como resultado, la medida del ajuste, el coeficiente de correlación R, no es aplicable [49,50].…”
Section: Estudio Cinético Y Determinación De Los Parámetros Cinéticos En El Bca Y Bofunclassified