Signaling bias makes reference to the capacity of G-protein coupled receptor (GPCR) ligands to direct pharmacological stimuli to a subset of effectors among all of those controlled by the receptor. This new signaling modality has added texture to the classical notion of efficacy. In doing so, it has opened new avenues for the development of therapeutic GPCR ligands that specifically modulate signals underlying desired effects while sparing those that support undesired drug actions. Essential to taking advantage of this texture is the ability to identify, quantify and represent bias in a reliable and intuitive manner that ensures comparison among ligands. Here, we present a practical guide on how the operational model may be used to evaluate ligand efficiency to induce different responses, how differences in response may be used to estimate bias and how quantitative information derived from this analysis may be graphically represented to recreate a drug's unique signaling footprint. The approach used is discussed in terms of data interpretation and limitations that may influence the conclusions drawn from the analysis.
Keywords: Bias; Drug development; Efficacy; Functional selectivity; Quantification; Texture.
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