Discovery of potentially biased agonists of mu-opioid receptor (MOR) through molecular docking, pharmacophore modeling, and MD simulation. (February 2021)

• Record Type: Journal Article
• Authors: Jiang, Xuan; Li, Shuxiang; Zhang, Hongbin; Wang, Liang-Liang
• Is Part Of: Computational biology and chemistry. Volume 90(2021)
• Publication Date: 2021-02
• Subjects: ASP Astex stastical potential -- GOLD Genetic optimization of ligand docking -- GPCRs G protein-coupled receptors -- GRK G protein-coupled receptor kinase -- MD Molecular dynamics simulations -- MOR μ-opioid receptor -- PDB Protein data bank -- RMSD Root mean square deviation -- TC Tanimoto Coefficient; μ-Opioid receptors (MOR) -- Biased ligands -- Molecular docking -- Hip-hop pharmacophore -- MD simulation; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2020.107405
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Four potential MOR sheet agonists were discovered through virtual screening. Highlights: Through virtual screening, 4 MOR biased agonistic candidate molecules were finally obtained. The four candidate molecules have different chemical backbones and bind to the key amino acid ASP147. Uses SeeSAR to predict the affinity of these four compounds has reached the nm level. After molecular dynamics simulations, the four compounds combined with MOR are more stable and tighter than BU72. Abstract: Opioids are well known for their potent analgesic efficacy and severe side effects. Studies have shown that analgesic effects are mediated by the downstream G-protein-dependent pathway of the μ-opioid receptor (MOR), and another β-arrestin-dependent pathway mediates side effects such as respiratory depression, constipation and tolerance etc . TRV130 is a biased ligand for G-protein-dependent pathway, which has high analgesia and has fewer side effects than morphine. In this study, the structure similarity search was performed on the IBSSC database using Oliceridine (TRV130) and PZM21 as templates. The 3D structure-based pharmacophore model was built and combined molecular docking prediction mode was selected to filter out small molecules, Finally, based on affinity prediction, four candidate molecules were obtained. Molecular dynamics simulations explored the detailed interaction mechanism of proteins with small molecules under dynamics. These results suggest that these candidate molecules are potential MOR agonists.