Lineweaver-Burk Plot Calculator

Enter your Km (Michaelis Constant), Vmax (Maximum Reaction Velocity), and Substrate Concentrations to generate a Lineweaver-Burk Plot and calculate the Y-Intercept (1/Vmax), X-Intercept (-1/Km), Slope (Km/Vmax), and R² Correlation Coefficient — giving you a full double-reciprocal breakdown of your enzyme kinetics data.

mM

Substrate concentration at half maximum velocity

µmol/min

Maximum enzyme reaction velocity

Comma-separated substrate concentration values in mM

Results

Y-Intercept (1/Vmax)

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X-Intercept (-1/Km)

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Slope (Km/Vmax)

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R² (Correlation Coefficient)

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Lineweaver-Burk Plot (1/v vs 1/[S])

Results Table

Frequently Asked Questions

What is a Lineweaver-Burk plot used for?

The Lineweaver-Burk plot is used in enzyme kinetics to determine Km and Vmax values from experimental data. It transforms the hyperbolic Michaelis-Menten equation into a linear relationship by plotting 1/v against 1/[S].

How do I interpret the Lineweaver-Burk plot results?

The y-intercept equals 1/Vmax, the x-intercept equals -1/Km, and the slope equals Km/Vmax. These values allow you to calculate the actual Km and Vmax parameters for your enzyme.

What are the advantages of the Lineweaver-Burk plot?

The main advantage is that it linearizes the Michaelis-Menten equation, making it easier to determine Km and Vmax values graphically. It also allows for easy identification of different types of enzyme inhibition.

What are the limitations of Lineweaver-Burk plots?

The double reciprocal transformation amplifies errors in measurements, especially at low substrate concentrations. This can lead to inaccurate parameter estimates if the data contains experimental errors.

How should I choose substrate concentrations for the plot?

Use a range of substrate concentrations both below and above the Km value. Include at least 5-6 different concentrations spanning from 0.2×Km to 10×Km for the most accurate results.

What does the R² value tell me about my data?

The R² (correlation coefficient) indicates how well your data fits a linear relationship. Values closer to 1.0 indicate better linearity and more reliable Km and Vmax calculations.

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