Detection of new biased agonists for the serotonin 5-HT2A receptor: modeling and experimental validation

Abstract

Detection of biased agonists for the serotonin 5-HT2A receptor can guide the discovery of safer and more efficient antipsychotic drugs. However, the rational design of such drugs has been hampered by the difficulty detecting the impact of small structural changes on signaling bias. To overcome these difficulties, we characterized the dynamics of ligand-receptor interactions of known biased and balanced agonists using molecular dynamics simulations. Our analysis revealed that interactions with residues S5.46 and N6.55 discriminate compounds with different functional selectivity. Based on our computational predictions, we selected three derivatives of the natural balanced ligand serotonin and experimentally validated their ability to act as biased agonists. Remarkably, our approach yielded compounds promoting an unprecedented level of signaling bias at the 5-HT2A receptor, which could help interrogate the importance of particular pathways in conditions like schizophrenia.