Nonlinear Least Squares Curve Fitter For Enzyme Kinetics

This page lets you fit enzyme kinetic data to the Michaelis-Menten equation to determine the Km and Vmax of the enzyme. Replace the sample data with your own data (in the format [S],Vo), set the correct number of data pairs, and supply reasonable estimates for the values of Vmax and Km. When you click the Iterate button, the JavaScript program refines these estimates to produce what should be a better set of parameters. This process is iterative, so with good guesses (and good luck), the calculation usually converges to the least squares solution in five to ten iterations. This program can fit other equations if entered in a format with variables of x and y and parameters of a and b. The sample data and equation provided is for an enzyme that obeys the Michaelis-Menten equation, with y = Vo, x = [S], a = Vmax, and b = Km

Instructions:

  1. Enter the number of data points:
  2. Enter the formula for the function to be fitted: y =
  3. Type (or paste) the [x,y] data:


  4. Enter your best guesses for the parameters:
    a (Vmax)=
    b (Km)=
    correlation coefficient =
  5. Click the button and observe how the parameters change in the boxes above.
  6. If the new parameter values seem reasonable, click the Iterate button again, and continue until the parameters converge. Always click the Iterate button an extra time after convergence has been attained.

  7. If you encounter problems getting the parameters to converge, you can specify a fractional adjustment factor here: Values less than 1.0 will apply only that fraction of the calculated adjustment to the parameters, making the convergence slower but more stable. Change this value back to 1.0 once the iterations seem to be converging.
  8. If any parameters seem to be diverging, enter a more reasonable value and click the Iterate button again.