Work

Structure-Guided Repurposing of Approved Drugs Identifies Aprepitant and Mavorixafor as Putative δ-Opioid Receptor Agonist Candidates

Year: 2026

Type: article

Abstract: δ-opioid receptor (DOR) is a promising therapeutic target for developing safer treatments for pain and neuroprotection. In this study, we applied a structure-guided drug-repurposing workflow to identify FDA-approved drugs with predicted DOR-binding and agonist-like structural features. Using a validated GNINA-based docking protocol with an active-state DOR model (PDB ID: 6PT3), we screened 2342 approved compounds and identified 39 candidates with predicted submicromolar binding affinities. These hits were further evaluated through molecular dynamics simulations, binding pocket volume analysis, and principal component analysis, which enabled the prioritization of two leading candidates, aprepitant and mavorixafor. Both compounds formed stable receptor-ligand complexes, maintained persistent interactions with Asp128, promoted contraction of the orthosteric pocket, and retained favorable redocking scores on the MD-refined receptor conformations. Overall, these results identify aprepitant and mavorixafor as promising putative DOR agonists and provide a rational foundation for their experimental validation through binding, functional, and in vivo pain studies in the future.

Source: International Journal of Molecular Sciences

DOI: 10.3390/ijms27093823

Authors: Rocco Buccheri, Carlo Reale, Alessandro Coco, Carmela Parenti, Lorella Pasquinucci, Antonio Rescifina

Institution: University of Catania

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,499