Nima,

To know if the antagonism is competitive or non-competitive, you just have to compare your slope to the theorical slope p=1, by a t test. t= |1-p o |/√(var p_o ) where po is the value of your observed slope.

if the t-test is not significant, then your slope is not significantly different from 1 and the antagonism is a competitive antagonism.

the pA2 value can be regarded as the value of the affinity constant of the antagonist for the receptor.

Nima,

My experience with Schild plots is a bit dated, so I am not sure I can offer specific help. In addition to the slope, the shape of the plot is important (as are the equations used to fit the curve to the data). An easy starting point for you might be the wikipedia entry (http://en.wikipedia.org/wiki/Schild_regression). At the bottom of the page there are some additional references (T. Kenakin) that could also be helpful in understanding your data.

Nima,

To know if the antagonism is competitive or non-competitive, you just have to compare your slope to the theorical slope p=1, by a t test. t= |1-p o |/√(var p_o ) where po is the value of your observed slope.

if the t-test is not significant, then your slope is not significantly different from 1 and the antagonism is a competitive antagonism.

the pA2 value can be regarded as the value of the affinity constant of the antagonist for the receptor.

thanks for the replies.

Well I've been told if the gradient of the slope is in between 0.8 and 1.2 then its a competitive antagonist.

Nima, you canno' say that's a competitive antagonism only if the observed slope is in between 0.8 and 1.2. You definitely have to do the t-test because it depends heavily on the variance of observed p (ispersion of your experimental points)

Jacques is right. You need to do the t-test, just to know if the slope is significantly different from 1.