From Sea to Synapse: Molecular Docking and Dynamics Study of Aplysinopsin Analogues as Selective 5-HT₂C Ligands

This is the authors' abstract. We don't add key points for this paper.

Background: Selective modulation of the serotonin 5-HT₂C receptor is a promising strategy for treating conditions, such as obesity and neuropsychiatric disorders. Aplysinopsins, a class of marine indole alkaloids, have emerged as potential 5-HT₂C-selective scaffolds. Objective: This work aims to assess the potential of aplysinopsin-based analogues as selective 5-HT₂C ligands. Methods: study of a library of aplysinopsin analogues and related indole alkaloids using induced-fit molecular docking, molecular dynamics (MD) simulations, and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profiling. Results: Dozens of analogues were docked into a serotonin receptor model, revealing sub-micromolar predicted binding affinities for several compounds. Top-ranked ligands, such as tubastrindole C, achieved docking scores around -12.7 kcal/mol and maintained stable binding poses in 100-ns MD simulations. Key ligand-receptor interactions included hydrogen bonding to the conserved Asp residue in the binding pocket and extensive π-π contacts with aromatic side chains. Notably, certain analogues with modest docking scores (e.g., N-propionyl-aplysinopsin) exhibited very favorable molecular mechanics generalized born surface area (MMGBSA) binding free energies, suggesting significant induced-fit effects upon binding. Predicted pharmacokinetic properties of the lead compounds were encouraging: all hits obeyed drug-likeness rules (0-1 Lipinski's rule violations) and showed high oral absorption prospects. While polar analogues had limited blood-brain barrier permeability, several top candidates displayed moderate central nervous system (CNS) penetration scores. Conclusion: These results highlight aplysinopsin-based analogues as attractive selective 5-HT₂C ligand candidates and provide molecular insights to guide future optimization and experimental validation.