The promise of biased ligands in therapeutics.

Discovered 40 years ago but underappreciated for decades, the paradigm of biased agonism has now become standard in G protein-coupled receptor (GPCR) pharmacology and drug discovery. Biased agonism refers to the phenomenon in which different agonists binding to the same receptor result in differential activation of signaling pathways downstream of the receptor. Biased agonists may have distinct physiological effects from the endogenous agonist or antagonists of a receptor, leading to unique pharmacological profiles that could serve as more effective drugs. This phenomenon is in part due to the stabilization of different ensembles of agonist:GPCR complexes leading to distinct transducer coupling. The delay in the appreciation of biased agonism likely reflects our prior inability to monitor different transducers and signaling pathways downstream of the receptor, as well as a lack of chemical diversity among tested agonists. Now, with a wealth of agonist:receptor:transducer structures, biased agonism is not the exception to GPCR pharmacology, but the rule. GPCR-biased signaling is encoded throughout a diversity of chemical space, from structurally distinct orthosteric agonists as well as allosteric modulators, which can engage receptors in distinct binding modes. Here, we review our current understanding of biased agonism, from pharmacological, mechanistic, and structural perspectives, and the current and potential impact of biased agonism on the development of new therapeutics. SIGNIFICANCE STATEMENT: Biased agonism has become a foundational paradigm in G protein-coupled receptor pharmacology that is fundamentally reshaping modern drug discovery by leveraging structural insights to selectively target distinct signaling pathways downstream of receptors. We review our current understanding of the structural mechanisms, pharmacology, and physiology of biased agonism, providing insights into how researchers can exploit this phenomenon to develop precise therapeutics with optimized pharmacological profiles.