3. Consider the following enzyme-catalyzed reaction of urea Urea + Urease (Urea. Urease)-> 2 NH, + CO2-urease ES The rate of reaction is given below as a function of the urea (substrate S) concentration Curea, kmol/m .30 0.65 0.25 0.17 0.061 0.0008 urea kmol/m-s 12.60 5.50 3.09 2.05 0.293 0,0035 a. Using Excel, determine the Michaelis-Menten rate equation parameters ra (also called V and K. by using the Lineweaver-Burke, Eadie-Hofstee and Hanes-Woolf equations (three separate plots). Show the model-predicted fit and clearly identify the three sets of rate equation parameters along with the regression statistics b. Using the above three sets of rate equation parameters, generate predicted values for ) vs Cs from Cs-0 to Cs-1.40 using a spacing of ACs-0.02. Compare the -S Cs data (solid points) with the predicted values using the rate equations parameters identified in step 2. (Lineweaver-Burke - solid line; Eadie-Hofstee-dashed line, and Hanes-Woolf- dotted line). Make sure to include a plot legend. e. Comment on the fit of the M-M curves from the estimates of kinetic parameters made in Part (a). Which approach was the best fit for the data? Explain why by looking up the three linear forms from an existing literature source and commenting on their statistical 'bias
3. Consider the following enzyme-catalyzed reaction of urea Urea + Urease (Urea. Urease)-> 2 NH, + CO2-urease ES The rate of reaction is given below as a function of the urea (substrate S) concentration Curea, kmol/m .30 0.65 0.25 0.17 0.061 0.0008 urea kmol/m-s 12.60 5.50 3.09 2.05 0.293 0,0035 a. Using Excel, determine the Michaelis-Menten rate equation parameters ra (also called V and K. by using the Lineweaver-Burke, Eadie-Hofstee and Hanes-Woolf equations (three separate plots). Show the model-predicted fit and clearly identify the three sets of rate equation parameters along with the regression statistics b. Using the above three sets of rate equation parameters, generate predicted values for ) vs Cs from Cs-0 to Cs-1.40 using a spacing of ACs-0.02. Compare the -S Cs data (solid points) with the predicted values using the rate equations parameters identified in step 2. (Lineweaver-Burke - solid line; Eadie-Hofstee-dashed line, and Hanes-Woolf- dotted line). Make sure to include a plot legend. e. Comment on the fit of the M-M curves from the estimates of kinetic parameters made in Part (a). Which approach was the best fit for the data? Explain why by looking up the three linear forms from an existing literature source and commenting on their statistical 'bias
Introduction to Chemical Engineering Thermodynamics
8th Edition
ISBN:9781259696527
Author:J.M. Smith Termodinamica en ingenieria quimica, Hendrick C Van Ness, Michael Abbott, Mark Swihart
Publisher:J.M. Smith Termodinamica en ingenieria quimica, Hendrick C Van Ness, Michael Abbott, Mark Swihart
Chapter1: Introduction
Section: Chapter Questions
Problem 1.1P
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Transcribed Image Text:3.
Consider the following enzyme-catalyzed reaction of urea
Urea + Urease
(Urea. Urease)-> 2 NH, + CO2-urease
ES
The rate of reaction is given below as a function of the urea (substrate S) concentration
Curea, kmol/m
.30
0.65
0.25
0.17
0.061
0.0008
urea kmol/m-s
12.60
5.50
3.09
2.05
0.293
0,0035
a. Using Excel, determine the Michaelis-Menten rate equation parameters ra (also called V and K.
by using the Lineweaver-Burke, Eadie-Hofstee and Hanes-Woolf equations (three separate plots). Show
the model-predicted fit and clearly identify the three sets of rate equation parameters along with the
regression statistics
b. Using the above three sets of rate equation parameters, generate predicted values for ) vs Cs from
Cs-0 to Cs-1.40 using a spacing of ACs-0.02. Compare the -S Cs data (solid points) with the
predicted values using the rate equations parameters identified in step 2. (Lineweaver-Burke - solid line;
Eadie-Hofstee-dashed line, and Hanes-Woolf- dotted line). Make sure to include a plot legend.
e. Comment on the fit of the M-M curves from the estimates of kinetic parameters made in Part (a).
Which approach was the best fit for the data? Explain why by looking up the three linear forms from an
existing literature source and commenting on their statistical 'bias
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