Kinetic method that is insensitive to variables affecting rate constants

Mieling, Glen E.; Pardue, Harry L.

doi:10.1021/ac50034a011

Cited by 92 publications

(48 citation statements)

References 6 publications

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“…Another improvement was to predict initial substrate concentration by nonlinear fitting of the instantaneous reaction rate (obtained by numerical differentiation) to the classical Michaelis-Menten equation. This expanded the upper limit to above twice the K m and eliminated the sensitivity to the variation of enzyme activity [4,5,6,7]. But its precision at higher substrate concentration was greatly reduced, and thus limited its application [7].…”

Section: Introductionmentioning

confidence: 99%

Kinetic substrate quantification by fitting the enzyme reaction curve to the integrated Michaelis–Menten equation

et al. 2003

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The reliability of kinetic substrate quantification by nonlinear fitting of the enzyme reaction curve to the integrated Michaelis-Menten equation was investigated by both simulation and preliminary experimentation. For simulation, product absorptivity epsilon was 3.00 mmol(-1) L cm(-1) and K(m) was 0.10 mmol L(-1), and uniform absorbance error sigma was randomly inserted into the error-free reaction curve of product absorbance A(i) versus reaction time t(i) calculated according to the integrated Michaelis-Menten equation. The experimental reaction curve of arylesterase acting on phenyl acetate was monitored by phenol absorbance at 270 nm. Maximal product absorbance A(m) was predicted by nonlinear fitting of the reaction curve to Eq. (1) with K(m) as constant. There were unique A(m) for best fitting of both the simulated and experimental reaction curves. Neither the error in reaction origin nor the variation of enzyme activity changed the background-corrected value of A(m). But the range of data under analysis, the background absorbance, and absorbance error sigma had an effect. By simulation, A(m) from 0.150 to 3.600 was predicted with reliability and linear response to substrate concentration when there was 80% consumption of substrate at sigma of 0.001. Restriction of absorbance to 0.700 enabled A(m) up to 1.800 to be predicted at sigma of 0.001. Detection limit reached A(m) of 0.090 at sigma of 0.001. By experimentation, the reproducibility was 4.6% at substrate concentration twice the K(m), and A(m) linearly responded to phenyl acetate with consistent absorptivity for phenol, and upper limit about twice the maximum of experimental absorbance. These results supported the reliability of this new kinetic method for enzymatic analysis with enhanced upper limit and precision.

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Section: Introductionmentioning

confidence: 99%

Kinetic substrate quantification by fitting the enzyme reaction curve to the integrated Michaelis–Menten equation

et al. 2003

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“…Similar results were found when temperature changes of several degrees were studied" with the molybdophosphate method for phos- predictive approach. 13 As an example of the predictive approach in our laboratory;" Fig. 7 second acquisition time to get convergence of the filter.…”

Section: Some Recent Trendsmentioning

confidence: 99%

Kinetic Methods of Analysis: How Do They Rate?

Crouch

1994

J Chinese Chemical Soc

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During the past few years there has been a resurgence of interest in kinetic aspects of analytical chemistry and in kinetic methods of analysis. The increased activity is a result of advances that have been made in instrumentation and in data processing techniques. Still, the kinetic approach is not widely applied by practicing analytical chemists. Why is this true? Why are kinetic methods not among the most common methods in use by analytical chemistry? This paper discusses the advantages and limitations of kinetic methods and addresses the probable reasons that they are not widely used. Several new principles have emerged that are guiding the development of new kinetic-based determinations. These developments have made it possible to compensate for errors that result from changes in reaction conditions and to determine accurately rnultiple components in mixtures. With these advances kinetic methods are approaching the reliability of traditional equilibrium-based determinations and should be re-evaluated by analytical chemists.lln"lQ,lII

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“…Various procedures can be used to reduce the sensitivity of kinetic methods to changes in the analytical variables (10)(11)(12)(13)(14)(15)(16)(17). Some of these have a "predictive" character because they are based on calculating the total change in absorbance expected if the reaction were to proceed to equilibrium, from the initial part of the absorbance-time curve (10)(11)(12).…”

Section: Introductionmentioning

confidence: 99%

“…Some of these have a "predictive" character because they are based on calculating the total change in absorbance expected if the reaction were to proceed to equilibrium, from the initial part of the absorbance-time curve (10)(11)(12). One of these procedures, based on the estimation of the total absorbance change by fitting absorbance vs. time data to a first-order model (11), was used by Bacon and Pardue for the enzymatic determination of creatinine in serum by using a reagent kit commercially available from Boehringer Mannheim (Creatinine PAP) (18).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of a Predictive Kinetic Procedure for the Enzymatic Measurement of Creatinine in Serum

Yago

Olmos²,

Gómez³

1998

CCLM

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We have evaluated the analytical performance of a predictive kinetic procedure for the enzymatic measurement of serum creatinine in comparison with equilibrium and kinetic fixed-time procedures. The procedure uses commercially available reagents and is based on calculating the total change in absorbance expected if the reaction were to proceed to equilibrium by fitting the initial part of the absorbance-time curve to a three-parameter function by non-linear regression. Total imprecision for different concentrations of creatinine ranges from 1.47 to 1.86% and is significantly better than that obtained for the fixed-time procedure. The results with the predictive procedure are less dependent on creatinine amidohydrolase activity in the reagent, pH of the reagent and temperature of analysis than are the results with the fixed-time procedure. All the procedures are interfered with by bilirubin and ascorbic acid to about the same extent. Recovery and linearity are quite acceptable, and the estimated accuracy is below 2.1%. However, in comparison with the equilibrium procedure, the predictive procedure tends to underestimate creatinine concentrations at values below 100 micromol/l, and the results obtained by the two procedures are not transferable. In conclusion, the predictive approach substantially improves the imprecision but not the specificity of the enzymatic assay of serum creatinine.

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Kinetic method that is insensitive to variables affecting rate constants

Cited by 92 publications

References 6 publications

Kinetic substrate quantification by fitting the enzyme reaction curve to the integrated Michaelis–Menten equation

Kinetic substrate quantification by fitting the enzyme reaction curve to the integrated Michaelis–Menten equation

Kinetic Methods of Analysis: How Do They Rate?

Evaluation of a Predictive Kinetic Procedure for the Enzymatic Measurement of Creatinine in Serum

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