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The Secret of Biased Agonists: How to Use Selectivity to Improve Drug Efficacy and Reduce Side Effects?
In today's era of rapid development of medical technology, functional selectivity has gradually become an important focus of drug research and development. This concept reveals ligand-dependent selectivity, which allows a specific ligand to activate or inhibit different signaling pathways at the same receptor. By gaining a deeper understanding of this phenomenon, the medical community hopes to find ways to improve drug efficacy while reducing side effects.
The discovery of functional selectivity not only breaks through the definition of traditional pharmacology, but also points the way for the development of new drugs.
The difference between functional selectivity and traditional selectivity
Traditional pharmacology usually classifies ligands as agonists, antagonists, or inverse agonists based on their interaction with receptors. However, as research progresses, more and more evidence shows that this simplified framework cannot fully explain the effects of certain ligands. Functional selectivity proposes that a ligand may have both agonist and antagonist properties depending on the effector pathway it activates upon binding to the receptor.
Functional selectivity emphasizes that the role of a ligand depends on its preferred signaling pathway, challenging the concept of rigid classification.
Practical applications of biased agonists
There are many examples of bias toward agonists in medical research that highlight their potential applications. For example, studies of G protein-biased agonists at the μ-opioid receptor have shown that these compounds are comparable in analgesic efficacy to traditional opioids but have properties that reduce the potential for addiction and the risk of respiratory depression. Furthermore, studies in chemokine receptor systems demonstrate the physiological importance of agonist bias.
Preclinical studies have shown that G-protein biased agonists have similar analgesic efficacy but reduce the risk of addiction and the potential for respiratory depression.
Specific examples of functional selectivity
The 5-HT2A receptor is a striking example of functional selectivity. The endogenous ligand serotonin activates phospholipase C but not phospholipase A2. Exogenous hallucinogens such as LSD exhibit different action properties. These observations suggest that different ligands based on the same receptor may be selected into different signal transduction pathways, resulting in different physiological effects.
LSD does not significantly activate IP3 signaling on the 5-HT2A receptor, but it can stimulate other pathways, showing the diversity of functional selectivity.
Future exploration
With further exploration in this field, functional selectivity may have a revolutionary impact on future drug design and therapy innovation. For example, the atypical antidepressant Tianeptine is believed to exhibit functional selectivity at the μ-opioid receptor, while Oliceridine, as a biased agonist of the μ-opioid receptor, helps achieve pain relief without inducing drug resistance. These findings demonstrate that functional selectivity is not only a new concept but may also open up entirely new therapeutic horizons.
Due to the existence of functional selectivity, scientists are redefining drug design and efficacy, and may be able to achieve more targeted therapies in the future.
In addition to analgesic and antidepressant applications, functional selectivity also has potential in drug development for other diseases. In the future, can we expect more biased agonists to build new bridges in safety and efficacy to improve our health?
