ANALYSIS OF ALGEBRAIC WEIGHTED LEAST-SQUARES ESTIMATORS FOR ENZYME PARAMETERS

An algorithm for the least-squares estimation of enzyme parameters K(m) and V(max.) is proposed and its performance analysed. The problem in non-linear, but the algorithm is algebraic and does not require initial parameter estimates. On a spreadsheet program such as MINITAB, it may be coded in as few as ten instructions. The algorithm derives an intermediate estimate of K(m) and V(max.) appropriate to data with a constant coefficient of variation and then applies a single reweighting. Its performance using simulated data with a variety of error structures is compared with that of the classical reciprocal transforms and to both appropriately and inappropriately weighted direct least-squares estimators. Three approaches to estimating the standard errors of the parameter estimates are discussed, and one suitable for spreadsheet implementation is illustrated.