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Updated: Mar 16, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
Bridging computational modeling with amino acid replacements to investigate GHS-R1a-peptidomimetic recognition
Jinqiang Hou1, Carlie L Charron2, Milan M Fowkes2
1London Regional Cancer Program, Lawson Health Research Institute, 790 Commissioners Road East, London, Ontario N6A 4L6, Canada.
Abstract:
The ghrelin receptor, also referred to as the growth hormone secretagogue receptor 1a (GHS-R1a), is a G protein-coupled receptor (GPCR) primarily expressed in the brain and pituitary. The wide spectrum of biological functions of GHS-R1a has rendered it a target for therapeutic drugs and for molecular imaging agents, for a variety of diseases. An improved understanding of the binding mechanism of a ligand to GHS-R1a would provide guidance on ligand design. This study investigates the binding of G-7039, a peptidomimetic agonist, to the GHS-R1a. A series of computational studies including homology modeling, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations were carried out in conjunction with amino acid replacements on G-7039. The results suggest that the first three residues on the N-terminal segment of the peptidomimetic are bound to three hydrophobic sub-pockets in the receptor binding site, with the driving force for binding mainly from hydrophobic interactions. It has been reported that a charge-charge interaction between the positively charged terminal amine of the agonist and Glu124 on the receptor serves as an anchor point for binding. However, our studies suggest that this interaction is not strong enough to anchor a ligand to the ghrelin receptor in the absence of hydrophobic interactions. The resulting computational model provides insight into structure activity relationship analysis for the ghrelin receptor and will assist in future ligand design.

