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Displaying enzyme kinetic data on a Lineweaver Burk plot
The best way to analyze enzyme kinetic data is to fit the data directly to the MichaelisMenten equation using nonlinear regression. Before nonlinear regression was available, investigators had to transform curved data into straight lines, so they could analyze with linear regression. One way to do this is with a LineweaverBurk plot. Take the inverse of the MichaelisMenten equation and simplify: Ignoring experimental error, a plot of 1/V vs. 1/S will be linear, with a Yintercept of 1/Vmax and a slope equal to Km/Vmax. The Xintercept equals ?1/Km. Use the LineweaverBurk plot only to display your data. Don't use the slope and intercept of a linear regression line to determine values for Vmax and KM. If you do this, you won't get the most accurate values for Vmax and KM. The problem is that the transformations (reciprocals) distort the experimental error, so the doublereciprocal plot does not obey the assumptions of linear regression. Use nonlinear regression to obtain the most accurate values of KM and Vmax (see Avoid Scatchard, LineweaverBurk and similar transforms). Tip. You should analyze enzyme kinetic data with nonlinear regression, not with LineweaverBurk plots. Use LineweaverBurk plots to display data, not to analyze data. To create a LineweaverBurk plot with Prism, start from a table where X is substrate concentration and Y is velocity. Click Analyze, and choose a builtin analysis. Then choose Transformations from the list of data manipulations. Check the option boxes to transform both X to be 1/X, and Y to be 1/Y. Be sure to check the option to create a new graph of the results. From that graph, click Analyze and choose linear regression to superimpose the regression line. This linear regression line should NOT be used to obtain values for Vmax and Km. The Xintercept of the regression line will be near 1/KM, and the negative inverse of the slope will be near the Vmax. However, the Vmax and KM values determined directly with nonlinear regression will be more accurate. It is better to draw the line that corresponds to the nonlinear regression fit. To create a LineweaverBurk line corresponding to the nonlinear regression fit, follow these steps:

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