On a Nonelementary Progress Curve Equation and Its Application in Enzyme Kinetics

2002 ◽  
Vol 42 (2) ◽  
pp. 157-161 ◽  
Author(s):  
Marko Goličnik
Keyword(s):  
Enzyme Kinetics ◽  
Progress Curve ◽  
Curve Equation

Application of progress curve analysis to in situ enzyme kinetics using 1H NMR spectroscopy

1986 ◽  
Vol 155 (1) ◽  
pp. 38-44 ◽  
Author(s):  
Jamie I. Vandenberg ◽  
Philip W. Kuchel ◽  
Glenn K. King
Keyword(s):  
Nmr Spectroscopy ◽  
Enzyme Kinetics ◽  
1H Nmr ◽  
1H Nmr Spectroscopy ◽  
Curve Analysis ◽  
Progress Curve

Effect of sucralose on the enzyme kinetics of invertase using real-time NMR spectroscopy and progress curve analysis

2018 ◽  
Vol 455 ◽  
pp. 5-9 ◽  
Author(s):  
Cheenou Her ◽  
Jaideep Singh ◽  
V.V. Krishnan
Keyword(s):  
Nmr Spectroscopy ◽  
Enzyme Kinetics ◽  
Real Time ◽  
Curve Analysis ◽  
Progress Curve ◽  
Kinetics Of

Thermodynamic Activity-Based Progress Curve Analysis in Enzyme Kinetics

2018 ◽  
Vol 36 (3) ◽  
pp. 234-238 ◽  
Author(s):  
Jürgen Pleiss
Keyword(s):  
Enzyme Kinetics ◽  
Thermodynamic Activity ◽  
Curve Analysis ◽  
Progress Curve

Steady-state kinetics

2000 ◽  
Author(s):  
Athel Cornish-Bowden
Keyword(s):  
Steady State ◽  
Enzyme Kinetics ◽  
Single Molecule ◽  
Transient State ◽  
Curve Analysis ◽  
Rate Equations ◽  
Progress Curve ◽  
Steady State Kinetics ◽  
Time Regime ◽  
Time Courses

All of chemical kinetics is based on rate equations, but this is especially true of steady-state enzyme kinetics: in other applications a rate equation can be regarded as a differential equation that has to be integrated to give the function of real interest, whereas in steady-state enzyme kinetics it is used as it stands. Although the early enzymologists tried to follow the usual chemical practice of deriving equations that describe the state of reaction as a function of time there were too many complications, such as loss of enzyme activity, effects of accumulating product etc., for this to be a fruitful approach. Rapid progress only became possible when Michaelis and Menten (1) realized that most of the complications could be removed by extrapolating back to zero time and regarding the measured initial rate as the primary observation. Since then, of course, accumulating knowledge has made it possible to study time courses directly, and this has led to two additional subdisciplines of enzyme kinetics, transient-state kinetics, which deals with the time regime before a steady state is established, and progress-curve analysis, which deals with the slow approach to equilibrium during the steady-state phase. The former of these has achieved great importance but is regarded as more specialized. It is dealt with in later chapters of this book. Progress-curve analysis has never recovered the importance that it had at the beginning of the twentieth century. Nearly all steps that form parts of the mechanisms of enzyme-catalysed reactions involve reactions of a single molecule, in which case they typically follow first-order kinetics: . . . v = ka . . . . . . 1 . . . or they involve two molecules (usually but not necessarily different from one another) and typically follow second-order kinetics: . . . v = kab . . . . . . 2 . . . In both cases v represents the rate of reaction, and a and b are the concentrations of the molecules involved, and k is a rate constant. Because we shall be regarding the rate as a quantity in its own right it is not usual in steady-state kinetics to represent it as a derivative such as -da/dt.

scholarly journals NMR Based Real-Time Enzyme Kinetics on Estimating the Inhibitory Effect of Sucralose in the Enzymatic Conversion of Sucrose

2020 ◽  
Author(s):  
Justin Vang ◽  
Cheenou Her ◽  
Krish Krishnan
Keyword(s):  
Enzyme Kinetics ◽  
Real Time ◽  
Potent Inhibitor ◽  
Inhibitory Effect ◽  
Lambert W Function ◽  
Enzymatic Conversion ◽  
Experimental Conditions ◽  
Enzymatic Production ◽  
Progress Curve

<p>Sucralose, one of the popular non-caloric artificial sweeteners, has been known to influence the enzymatic conversion of sucrose to glucose and fructose by invertase. In continuing the use of real-time NMR experiments and reaction progress curve analysis to measure enzyme kinetics, here we investigate the role of sucralose as an inhibitor. NMR based kinetic experiments were performed as a function of the substrate concentration for a range of sucralose concentrations, and the results were analyzed by fitting the progress curve to the Lambert-W function. The Michaelis-Menten parameters were then used to estimate the inhibitory constant of sucralose. To estimate the extent of sucralose inhibition on the enzymatic production of glucose, control experiments were performed with lactose as the inhibitor under similar experimental conditions. The results show that sucralose is a much more potent inhibitor than lactose, inhibiting the enzymatic conversion at least seven times more. <b><u></u></b></p>

scholarly journals Half-time analysis of the integrated Michaelis equation. Simulation and use of the half-time plot and its direct linear variant in the analysis of some α-chymotrypsin-, papain- and fumarase-catalysed reactions

1982 ◽  
Vol 203 (2) ◽  
pp. 351-360 ◽  
Author(s):  
Christopher W. Wharton ◽  
Ronald J. Szawelski
Keyword(s):  
Enzyme Kinetics ◽  
Linear Form ◽  
Substrate Concentration ◽  
Signal To Noise Ratio ◽  
Linear Regression Analysis ◽  
Low Noise ◽  
Half Time ◽  
Logarithmic Term ◽  
Progress Curve ◽  
Time Plot

Substitution of half-time parameters in the integrated form of the Michaelis–Menten equation for any enzyme-catalysed reaction yields an equation that gives a linear relationship between the half-time of the reaction and the substrate concentration at that point of the reaction. The logarithmic term of the integrated equation becomes a constant as a result of the substitution, which means that the use of the half-time plot of the equation requires calculation only of half-time and substrate-concentration values at various stages of the reaction. The half-time method is both simple and exact, being analogous to an [S0]/vi against [S0] plot. A direct linear form of the half-time plot has been devised that allows very simple estimation of Michaelis parameters and/or initial velocities from progress-curve data. This method involves no approximation and is statistically valid. Simulation studies have shown that linear-regression analysis of half-time plots provides unbiased estimates of the Michaelis parameters. Simulation of the effect of error in estimation of the product concentration at infinite time [P∞] reveals that this is always a cause for concern, such errors being magnified approximately an order of magnitude in the estimate of the Michaelis constant. Both the half-time plot and the direct linear form have been applied to the analysis of a variety of experimental data. The method has been shown to produce excellent results provided certain simple rules are followed regarding criteria of experimental design. A set of rules has been formulated that, if followed, allows progress-curve data to be acquired and analysed in a reliable fashion. It is apparent that the use of modern spectrophotometers in carefully designed experiments allows the collection of data characterized by low noise and accurate [P∞] estimates. [P∞] values have been found, in the present work, to be precise to within ±0.2% and noise levels have always been below 0.1% (signal-to-noise ratio≃1000). As a result of the considerations above, it is concluded that there is little to be feared with regard to the analysis of enzyme kinetics using complete progress curves, despite the generally lukewarm recommendations to be found in the literature. The saving in time, materials and experimental effort amply justify analysis of enzyme kinetics by progress-curve methods. Half-time plots linear to ≥90% of reaction have been obtained for some α-chymotrypsin-, papain- and fumarase-catalysed reactions.

scholarly journals Beyond the Michaelis-Menten equation: Accurate and efficient estimation of enzyme kinetic parameters

2017 ◽  
Author(s):  
Boseung Choi ◽  
Grzegorz A. Rempala ◽  
Jae Kyoung Kim
Keyword(s):  
Enzyme Kinetics ◽  
Kinetic Parameters ◽  
Cellular Systems ◽  
Efficient Estimation ◽  
Minimal Amount ◽  
Enzyme Kinetic ◽  
Optimal Experiment ◽  
Progress Curve ◽  
State Approximation ◽  
Canonical Approach

ABSTRACTExamining enzyme kinetics is critical for understanding cellular systems and for using enzymes in industry. The Michaelis-Menten equation has been widely used for over a century to estimate the enzyme kinetic parameters from reaction progress curves of substrates, which is known as the progress curve assay. However, this canonical approach works in limited conditions, such as when there is a large excess of substrate over enzyme. Even when this condition is satisfied, the identifiability of parameters is not always guaranteed, and often not verifiable in practice. To overcome such limitations of the canonical approach for the progress curve assay, here we propose a Bayesian approach based on an equation derived with the total quasi-steady-state approximation. In contrast to the canonical approach, estimates obtained with this proposed approach exhibit little bias for any combination of enzyme and substrate concentrations. Importantly, unlike the canonical approach, an optimal experiment to identify parameters with certainty can be easily designed without any prior information. Indeed, with this proposed design, the kinetic parameters of diverse enzymes with disparate catalytic efficiencies, such as chymotrypsin, fumarase, and urease, can be accurately and precisely estimated from a minimal amount of timecourse data. A publicly accessible computational package performing the Bayesian inference for such accurate and efficient enzyme kinetics is provided.

scholarly journals NMR Based Real-Time Enzyme Kinetics on Estimating the Inhibitory Effect of Sucralose in the Enzymatic Conversion of Sucrose

2020 ◽  
Author(s):  
Justin Vang ◽  
Cheenou Her ◽  
Krish Krishnan
Keyword(s):  
Enzyme Kinetics ◽  
Real Time ◽  
Potent Inhibitor ◽  
Inhibitory Effect ◽  
Lambert W Function ◽  
Enzymatic Conversion ◽  
Experimental Conditions ◽  
Enzymatic Production ◽  
Progress Curve

<p>Sucralose, one of the popular non-caloric artificial sweeteners, has been known to influence the enzymatic conversion of sucrose to glucose and fructose by invertase. In continuing the use of real-time NMR experiments and reaction progress curve analysis to measure enzyme kinetics, here we investigate the role of sucralose as an inhibitor. NMR based kinetic experiments were performed as a function of the substrate concentration for a range of sucralose concentrations, and the results were analyzed by fitting the progress curve to the Lambert-W function. The Michaelis-Menten parameters were then used to estimate the inhibitory constant of sucralose. To estimate the extent of sucralose inhibition on the enzymatic production of glucose, control experiments were performed with lactose as the inhibitor under similar experimental conditions. The results show that sucralose is a much more potent inhibitor than lactose, inhibiting the enzymatic conversion at least seven times more. <b><u></u></b></p>

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