A new procedure to derive weighting factors for nonlinear regression analysis applied to enzyme kinetic data

The experimental variance of enzymic steady-state kinetic experiments depends on velocity as approximated by a power function (Var(v) = K1 . valpha (Askelöf, P., Korsfeldt, M. and Mannervik, B. (1976) Eur. J. Biochem. 69, 61--67). The values of the constants (K1, alpha) can be estimated by making replicate measurements of velocity, and the inverse of the function can then be used as a weighting factor. In order to avoid measurement of a large number of replicates to establish the error structure of a kinetic data set, a different approach was tested. After a preliminary regression using a 'good model', which satisfies reasonable goodness-of-fit criteria, the residuals were taken to represent the experimental error. The neighbouring residuals were grouped together and the sum of their mean squared values was used as a measure of the variance in the neighbourhood of the corresponding measurements. The values of the constants obtained in this way agreed with those obtained by replicates.