Molecular Docking Studies for Designing and Identification of Novel Bitopic Ligands for Sigma-1 Receptor

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2023

Authors

Ponce, Aiyana
Kumari, Pratibha
Liu, Jin

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Abstract

Purpose: Our goal is to identify more specific ligands for the Sigma-1 Receptor (S1R) by designing and docking various bitopic ligands then ranking them based on their interactions. The S1R is an intracellular, multifunctional receptor that is a target in many pathologies. S1R is found throughout the body, within the membranes of the nucleus, ER, and mitochondria, and the CNS is the primary site of activity. Bitopic ligands are those that combine the high affinity by binding to orthosteric sites and high selectivity by binding to allosteric sites on the same receptor. They are used to gain insights on molecular functioning of the receptor.

Methods: A set of 3 linkers were tested with a known allosteric binding compound and the one with highest affinity was selected to continue in the design process. Nine bitopic ligands were designed using known allosteric compounds, the selected linker, and a high affinity orthosteric compound. Ligands were minimized with Avogadro then PDBQT files for minimized ligands and S1R open-state confirmation were prepared with AutoDock Tools. All newly designed ligands were docked on S1R using Vina to determine their binding affinities. Interactions were visualized using Pymol and quantified using Protein Ligand Interaction Profiler.

Results: After testing 3 linkers from the literature, we identified 1 that gave highest affinity with our allosteric compound and selected to use it in the design of new bitopic ligands. Our results shows that all ligands docked in a bend conformation in the S1R. Specifically, bitopic ligands having benzazepine derivatives showed greater affinity to S1R. The number of hydrophobic bonds, hydrogen bonds, pi bonds, and salt bridges were identified for each interaction between the ligand and S1R.

Conclusions: The 1-2 compounds with the highest affinity and favorable interactions are candidates to be used for future drug design models.

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