RT Journal Article
SR Electronic
T1 Identifying Functional Hotspot Residues for Biased Ligand Design in G-Protein-Coupled Receptors
JF Molecular Pharmacology
JO Mol Pharmacol
FD American Society for Pharmacology and Experimental Therapeutics
SP 288
OP 296
DO 10.1124/mol.117.110395
VO 93
IS 4
A1 Anita K. Nivedha
A1 Christofer S. Tautermann
A1 Supriyo Bhattacharya
A1 Sangbae Lee
A1 Paola Casarosa
A1 Ines Kollak
A1 Tobias Kiechle
A1 Nagarajan Vaidehi
YR 2018
UL http://molpharm.aspetjournals.org/content/93/4/288.abstract
AB G-protein-coupled receptors (GPCRs) mediate multiple signaling pathways in the cell, depending on the agonist that activates the receptor and multiple cellular factors. Agonists that show higher potency to specific signaling pathways over others are known as “biased agonists” and have been shown to have better therapeutic index. Although biased agonists are desirable, their design poses several challenges to date. The number of assays to identify biased agonists seems expensive and tedious. Therefore, computational methods that can reliably calculate the possible bias of various ligands ahead of experiments and provide guidance, will be both cost and time effective. In this work, using the mechanism of allosteric communication from the extracellular region to the intracellular transducer protein coupling region in GPCRs, we have developed a computational method to calculate ligand bias ahead of experiments. We have validated the method for several β-arrestin–biased agonists in β2-adrenergic receptor (β2AR), serotonin receptors 5-HT1B and 5-HT2B and for G-protein–biased agonists in the κ-opioid receptor. Using this computational method, we also performed a blind prediction followed by experimental testing and showed that the agonist carmoterol is β-arrestin–biased in β2AR. Additionally, we have identified amino acid residues in the biased agonist binding site in both β2AR and κ-opioid receptors that are involved in potentiating the ligand bias. We call these residues functional hotspots, and they can be used to derive pharmacophores to design biased agonists in GPCRs.