Schild-plot analysis

Figure 4 Competitive antagonism of Y1 receptors by AXC01018. The NPY-induced inhibition of norepinephrine-stimulated cAMP accumulation in SK-N-MC cells was antagonized by pre-treating the cells with AXC01018. Analysis of the Schild plot shown in the inset gives a slope of 0.88 and Ai, of 400 nM.

Fig. 3.4 Schild analysis of agonist-antagonist competition. (A) Concentration-effect relationship for an agonist in the absence (curve 0) and the presence of three increasing concentrations of antagonist (curves 1, 2 and 3). (B) Schild plot generated from curve A (see text for explanations).

One shortcoming of Schild analysis is an overemphasized use of the control dose-response curve (i.e., the accuracy of every DR value depends on the accuracy of the control EC o value). An alternative method utilizes nonlinear regression of the Gaddum equation (with visualization of the data with a Clark plot [10], named for A. J. Clark). This method, unlike Schild analysis, does not emphasize control pECS0, thereby giving a more balanced estimate of antagonist affinity. This method, first described by Lew and Angus [11], is robust and theoretically more sound than Schild analysis. On the other hand, it is not as visual. Schild analysis is rapid and intuitive, and can be used to detect nonequilibrium steady states in the system that can corrupt... 

Figure 7.2. (A) The greased-gap technique for recording depolarizations of the rat isolated vagus nerve. (B) The effect of ondansetron on depolarizations of the rat isolated vagus nerve induced by 5-HT. Symbols indicate controls (9) or in the presence of ondansetron at I x 10 M (O), 3 X 70" M (M), I X 10 M (O) or 3 x 10 M (A). Results are the mean + S.E.M. of at least four determinations. Experiments were performed as described by Ireland and Tyers [21J. (C) Data from the experiments illustrated in B plotted according to Arunlakshana and Schild [22]. Each point is the result from a separate tissue. The gradient of straight line (95 Vo confidence limits) was determined using linear regression analysis.

The values are expressed or plotted as the means SE and pA2 values are calculated according to Arunlakshana and Schild (1959). Data are analyzed using the t-test, analysis of variance, Dunnett s test and... 

---