Enzyme Kinetics Calculator
Fit Michaelis-Menten kinetics from substrate-rate data or compute reaction velocity directly.
Learn more
What it does
The enzyme kinetics calculator fits Michaelis-Menten parameters from substrate-velocity data or computes reaction velocity directly. Biochemists and students use it to characterize enzyme efficiency, compare catalysts, and design assay conditions.
How it works
Michaelis-Menten kinetics describes velocity v as a function of substrate concentration: v equals Vmax times [S] divided by (Km plus [S]). Vmax is the maximal velocity at saturating substrate, and Km is the substrate concentration at which v equals Vmax divided by 2. The tool fits Vmax and Km by linear regression on the Lineweaver-Burk transform (1/v versus 1/[S]) and reports the R-squared of the fit; alternatively it computes v directly from entered Vmax, Km and [S].
Worked example
Given data points (0.5, 0.18), (1, 0.30), (2, 0.48) and (5, 0.71) in mM and mM per minute, the fit yields Vmax near 1.0 and Km near 1.0, so at [S] equals Km the velocity is about 0.5, which is half of Vmax.
When to use it
Estimate Km and Vmax from an enzyme assay time course to rank substrate preferences. Predict the rate at a chosen substrate concentration for experimental planning. Teach the Lineweaver-Burk linearization and the meaning of Km and Vmax.
FAQ
- What is the Michaelis-Menten equation?
- It is v equals Vmax times [S] divided by (Km plus [S]), relating reaction velocity to substrate concentration.
- How do you calculate Vmax and Km from data?
- Plot 1/v against 1/[S] (the Lineweaver-Burk transformation); linear regression gives a y-intercept of 1/Vmax and an x-intercept of negative 1/Km. The tool performs this fit automatically.
- What does Km tell you about an enzyme?
- Km is the substrate concentration at half-maximal velocity. A low Km means high apparent affinity, while a high Km means lower affinity for the substrate.
- What is a good R-squared in a kinetics fit?
- Closer to 1 indicates the data follow Michaelis-Menten behavior well; lower values suggest substrate inhibition, cooperativity, or measurement error, and the model may not apply.