| Abstract: | Several theories of chemoreceptor stimulation predict the samesimple relationship between response R and stimulus concentrationC:  (1 + K/C),(in which Rmax is maximum response and K an equilibriumconstant), also known as Beidler's taste equation. To test whetherdata points fit this equation and estimate Rmax and K, severaltransformations are in use which convert the theoretical curveinto a straight line (Lineweaver-Burk, Scatchard, Eadie-Hofsteeand Beidler plots). However, even modest amounts of responsevariability may interfere badly with the evaluation of theseplots. This is not always appreciated; therefore this paperpresents an illustration of the extent of this effect, usinga realistic example. In addition, this effect may also obscurethe presence of theoretically relevant deviations from the aboveequation, caused by multiple receptor sites, or convergenceof receptors, which are expressed in a Hill coefficient nH  1. These effects are also exemplified. The illustrations areshown graphically and by a Montre-Carlo computer simulation.The conclusion is drawn that the linearizing plots should notbe used at all for the quantitative evaluation of data. Direct,numerical iterative curve-fitting methods seem to give morereliable results. |
