Data analysis

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The determination of inhibition mechanism became of great interest for several potent hits.

Cells were incubated for 30 minutes with a single concentration of selected test compound based on the previously determined inhibitory dose-response curves. Five different concentrations of test compound were tested in duplicates on one 96 well plate of cells, plus duplicates DMSO 1 % as positive control. Cells were stimulated with various ATP concentrations to create shift curves. The nature of the shift provides an indication how the test compounds affects receptor activation upon agonist presence. When full activation of receptor is reached even under influence of high inhibitor concentration, and the EC50 value of agonist is shifted to higher concentrations than the control, competitive receptor inhibition is indicated. The same EC50 value, but a decrease of agonist potency upon full stimulation points to an allosteric inhibition mechanism of the antagonist.

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Top and Bottom represent 100 and 0 % receptor activation, respectively, while X represents the concentration of the used ligand. No constraints were selected. Each experiment was repeated three times. The mean curve was calculated by averaging the mean data of each experiment, followed by sigmoidal dose response analysis with variable slope. This calculation was selected for every dose-response experiment, including testing for inhibitory potency and enhancement dose-dependency.

The bell-shaped curve analysis was selected for compounds showing inhibition in high and enhancement in low concentrations, using GraphPad® Prism 5.03 (GraphPad® Software, San Diego, California, USA). It follows the equation:

𝑌 = 𝐷𝑖𝑝 + 𝑃𝑙𝑎𝑡𝑒𝑎𝑢1 − 𝐷𝑖𝑝

1 + 10^{((𝐿𝑜𝑔𝐸𝐶50}_1−𝑋)×𝑛𝐻1))+ 𝑃𝑙𝑎𝑡𝑒𝑎𝑢2 − 𝐷𝑖𝑝 1 + 10^{((𝑙𝑜𝑔𝐸𝐶50}_2−𝑋)×𝑛𝐻2))

Plateau1 and Plateau2 are the plateaus at the left and right end of the curve. Dip represents the plateau level in the middle of the curve, LogEC50_1 and LogEC50_2 are the concentrations that give half-maximal stimulatory and inhibitory effects, and nH1 and nH2 represent the unitless Hill slopes.

ATP shift curves were conducted in order to gain more insight in the inhibition mechanism of the most interesting hits. The Gaddum/Schild analysis was selected for determination whether the shift of the ATP curve fits with competitive antagonism. The equations are:

𝐸𝐶50= 10^{𝑙𝑜𝑔𝐸𝐶50} 𝐿𝑜𝑔𝐸𝐶 = 𝐿𝑜𝑔 [𝐸𝐶50× (1 + ( 𝐵

10^{(−1×𝑝𝐴2)})

𝑆𝑐ℎ𝑖𝑙𝑑 𝑆𝑙𝑜𝑝𝑒

)]

𝑌 = 𝐵𝑜𝑡𝑡𝑜𝑚 + 𝑇𝑜𝑝 − 𝐵𝑜𝑡𝑡𝑜𝑚 1 + 10((𝑙𝑜𝑔𝐸𝐶−𝑋)×𝐻𝑖𝑙𝑙 𝑠𝑙𝑜𝑝𝑒)

Bottom and top represent the minimum and maximum responses, and X is the concentration of the used ligand in both sigmoidal dose response and Gaddum/Schild equations, respectively. The calculation of the dose ratio (DR) was needed for the linear regression. The dose ratio is defined as the quotient of the agonist EC50 concentration influenced by antagonist and the control

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agonist EC50 concentration. The concentration of antagonist is then plotted against DR-1 to create the linear regression of the Schild plot.

Some compounds tested in ATP shift curve experiment did not show a shift of EC50 value, but a concentration-dependent reduction of the maximal ATP effect. The fluorescence signal induced by the highest ATP concentration used in the experiment was calculated for those compounds.

The buffer control was based as 0 % and the respective highest ATP concentration as 100 %. The unpaired Student’s t-test of the respective means was conducted in order to determine whether the influence of the compound on the maximal ATP effect was statistically significantly different from the fluorescence increase caused by the highest ATP concentration of the control. The difference between mean pEC50 of ATP control and mean pEC50 of ATP influenced by respective test compound concentration was deemed significant, when the calculated P value was lower than 0.05. For all experiments, the two-tailed P value was selected. The same analysis was used to determine significance of maximal ATP effect of the control and after preincubation with respective test compound. Significant differences of the mean (P < 0.05) were marked with (*), very significant differences (p < 0.01) with (**) and highly significant differences (p < 0.001) with (***).

The unpaired Student’s t-test was also selected for the analysis of the data collected for the fluorescence signal enhancement caused by some test compounds. The pEC50Enhancement values and the enhancement of maximal ATP effect were analyzed with the same protocol as described for pEC50 values and maximal ATP effect determined out of ATP shift curves for inhibitory compounds. The ATP control was calculated from the results of the highest ATP concentration used in the respective experiment. It was perched at 100 % for the calculation of enhancement, the buffer control as 0 %. The ATP control was subtracted from the values of each sample to demonstrate the magnitude of enhancement.

The validity of each experiment at each receptor was determined by calculation of Z’-factor as described by Zhang et al. in 1999.¹⁹⁸ The Z’ factor is calculated by the following equation, with σ representing the standard deviation and μ the mean of the positive (index p) and negative control (index n), respectively.

𝑍^′ = 1 − |3 × 𝜎p+ 3 × 𝜎n|

|𝜇p− 𝜇n|

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The ATP values without addition of any inhibitor or test component were used as positive control. The negative control was calculated from the data obtained by preincubation with a standard antagonist. The concentration was selected high enough to completely block any receptor activity. When it was not possible to apply a standard antagonist on the assay plate, the buffer control was taken as the negative control instead. The Z’-factors from all experiments were averaged for each receptor and the standard error of the mean was calculated. At a Z’-factor higher than 0.5, the separation band between positive and negative control is large and the assay is deemed as suitable for high-throughput screening.