Data Analysis—Concentration—Response Assays

Data were analyzed using GraphPad PRISM versions 6, 7, and 8. For each individual experiment, concentration response curves were fit using three-parameter nonlinear regression. A response was only deemed a curve when at least two data-points were above the response to media control, otherwise the response was deemed unquantifiable and referred to as a flat-line. If a response was deemed a curve, but did not appear to reach its maximal response within the tested concentration range, the curve-fit was constrained using the mean response at the highest concentration of peptide as the E_max for the peptide.

In the case of weak agonists or weakly coupled pathways, there were some instances in which a peptide could stimulate a measurable response during some experiments and not in others. In these cases the outcome from the majority of independent experiments has been reported. When reporting these results, the experiments from the minority are excluded from the reported n numbers, and a note is included in the legend to indicate this.

From curve fits we obtained the pEC₅₀ and E_max. Individual pEC₅₀ and E_max values were combined to generate mean data. pEC₅₀ data were analyzed using either repeated measures one-way analysis of variance (ANOVA) with posthoc Tukey’s test (endogenous ligand characterization), or paired Student’s t-tests (characterization of analogues/fragments). These different approaches are justified in the above section “Experimental design”. To analyze the differences in E_max between endogenous ligands, the raw E_max values were log-transformed, then the resultant values were compared using a repeated measures one-way ANOVA with posthoc Tukey’s test.¹⁰⁵ Raw E_max values for analogues and fragments were compared to the relevant control using a paired ratio Student’s t-test.

For ease of comparison, and to take into account day-to-day variability associated with transient transfections, data were normalized for presentation in the manuscript. This involved normalizing each experiment to the fitted maximum and minimum of the relevant control included on each plate. Normalized curves were then generated by combining the mean of data points from individual experiments.