Quantitative assessment of ligand bias from bias plots: The bias coefficient "kappa"

Differential association of EphA2 intracellular regions in biased signaling

Biased signaling is the ability of a receptor to differentially activate certain signaling cascades in response to different ligands. Our previous work demonstrated that the monomeric ephrinA1 ligand and the widely used dimeric ephrinA1-Fc ligand induced EphA2 receptor tyrosine kinase (RTK)-biased signaling. The hypothesis that RTK biased signaling is a consequence of differential interactions between receptor intracellular regions when different ligands are bound to the extracellular region has not been experimentally verified thus far, in part because of the lack of high-resolution structures of full-length RTK oligomers. Here, we compare the effects of deletion of intracellular regions in EphA2 oligomers bound to the biased ligands, monomeric ephrinA1 or ephrinA1-Fc. Our data reveal distinct differences in the intracellular organization of EphA2 oligomers bound to the two ligands, supporting the hypothesis. They also suggest that EphA2 signaling could be modulated by agents that alter interactions between oligomerized EphA2 intracellular regions by binding at sites that can be distant from the ATP-binding pocket.

Quantitative receptor model for responses that are left- or right-shifted versus occupancy (are more or less concentration sensitive): the SABRE approach

Simple one-to three-parameter models routinely used to fit typical dose-response curves and calculate EC50 values using the Hill or Clark equation cannot provide the full picture connecting measured response to receptor occupancy, which can be quite complex due to the interplay between partial agonism and (pathway-dependent) signal amplification. The recently introduced SABRE quantitative receptor model is the first one that explicitly includes a parameter for signal amplification (γ) in addition to those for binding affinity (K d), receptor-activation efficacy (ε), constitutive activity (ε R0), and steepness of response (Hill slope, n). It can provide a unified framework to fit complex cases, where fractional response and occupancy do not match, as well as simple ones, where parameters constrained to specific values can be used (e.g., ε R0 = 0, γ = 1, or n = 1). Here, it is shown for the first time that SABRE can fit not only typical cases where response curves are left-shifted compared to occupancy (κ = K d/EC50 > 1) due to signal amplification (γ > 1), but also less common ones where they are right-shifted (i.e., less concentration-sensitive; κ = K d/EC50 < 1) by modeling them as apparent signal attenuation/loss (γ < 1). Illustrations are provided with μ-opioid receptor (MOPr) data from three different experiments with one left- and one right-shifted response (G protein activation and β-arrestin2 recruitment, respectively; EC50,Gprt < K d < EC50,βArr). For such cases of diverging pathways with differently shifted responses, partial agonists can cause very weak responses in the less concentration-sensitive pathway without having to be biased ligands due to the combination of low ligand efficacy and signal attenuation/loss-an illustration with SABRE-fitted oliceridine data is included.