Title | Schild Plot and Reuptake Extra Lecture (3a) |
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Author | Malachi Casey |
Course | Receptor Mechanisms |
Institution | University College London |
Pages | 2 |
File Size | 93.9 KB |
File Type | |
Total Downloads | 94 |
Total Views | 139 |
Receptor Mechanisms Level 7 Notes...
The impact of re-uptake of agonist on Schild analysis. Why the Schild plot is the way it is if we don’t take care of re-uptake processes that affect the agonist concentrations as we apply them. The easiest way to address that question is to consider some faked data e.g. Table 1 below. We start with the case where there is no problem with re- uptake. Table 1. A50: Agonist Conc producing 50% response (nM) 50 75 300 2550 25000 250000
Antagonist Concentration. 0 10 100 1000 10,000 100,000
Dose ratio (r)
1.5 6.0 51 500 5000
Log10(r-1)
-0.30 0.70 1.70 2.70 3.70
Log10[B]
1 2 3 4 5
The corresponding Schild plot is exactly what we expect for a reversible competitive antagonist – a straight line with a slope of “1”.
Figure 1. Schild plot generated using the data in Table 1, where there are no complications caused by re-uptake and the data fall on a straight line with a slope of “1”.
Now we think about what will happen to the A50 values when uptake mechanisms are not inhibited. The biggest impact will be on the lowest A50 values (i.e. before the uptake mechanisms saturate). In Table 2 (below) the A50 values from Table 1 have been altered to reflect this. The lowest concentration has been increased by a factor of 10. The next A50 value, which will be slightly less affected, has been increased by a factor of 8.6, the next by a factor of 3, the next by a factor of 1.17 and I have left the last two values unchanged (on the grounds that the uptake mechanisms will not be able to impact such high concentrations). Table 2. A50 values affected by re-uptake of agonist. A50: Agonist Conc producing 50% response (nM). 500 650 900 3000 25000 250000
Antagonist Concentration.
Dose ratio (r)
Log10(r-1)
0 10 100 1000 10,000 100,000
1.5 6.0 51 500 5000
-0.30 0.70 1.70 2.70 3.70
Log10[B]
1 2 3 4 5
The Schild plot (check it yourself using Table 2) then looks like this:
Fig. 2. The data plotted from Table 2 (filled circles), along with the line which the Schild data should fall on....