4.5 Article

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

Journal

COMPUTATIONAL BIOLOGY AND CHEMISTRY
Volume 90, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.compbiolchem.2020.107405

Keywords

mu-Opioid receptors (MOR); Biased ligands; Molecular docking; Hip-hop pharmacophore; MD simulation

Funding

  1. National Natural Science Foundation of China [21772207]
  2. CAS' Light of West China' Programand Youth Innovation Promotion Association CAS
  3. The Thousand Talents Program of Yunnan Province

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Opioids are known for their potent analgesic effects and severe side effects. TRV130, a biased ligand for the G-protein-dependent pathway of the mu-opioid receptor, shows high analgesia and fewer side effects. Through structure similarity search and molecular dynamics simulations, four candidate molecules with potential MOR agonist activity were identified.
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 mu-opioid receptor (MOR), and another beta-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.

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