The influence of signal noise on the accuracy of kinetic constants measured by surface plasmon resonance experiments

An analysis is carried out to investigate the accuracy of kinetic parameters obtained using surface plasmon resonance methodology with a BIAcore instrument. The Cramer Rao lower bound for the least possible variance of an estimator of the kinetic parameters is determined. Using simulations it is shown that the standard least-squares estimation technique provides estimates that achieve this bound. The theoretical and simulation results are compared with experimental data obtained from an analysis of the interaction of the myc peptide with the anti-myc antibody, 9E10. This investigation indicates that the accuracy of the results depends on the signal level which has particular relevance to the design of experiments with low signal levels. It is shown how the accuracy of the estimates of the kinetic constants depends on the kinetic constants themselves and how the accuracy of the association constants depends on the concentration of the analyte that is used in the experiment. In addition, the effects of increasing the number of data points in the analysis of dissociation data on the accuracy of the estimates are quantitated. It is also demonstrated that signal averaging of data derived from repeat sensorgrams can result in a significant decrease in the standard deviation of the estimates. (C) 1999 Academic Press.