ArticleACS omega2026
Analyzing the Chemical Space of Opioid Receptor Agonists and Antagonists: Insights from Computational Models.
Article in ACS omega, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The opioid crisis has imposed a significant financial burden on the United States, costing billions of dollars annually. The recent surge in opioid overdoses has further exacerbated this crisis, placing immense strain on public health resources and the criminal justice system. Currently, all four FDA-approved medications for medication-assisted treatment (MAT) of opioid use disorder (OUD) target opioid receptors (ORs), highlighting the importance of understanding their pharmacology. This computational study investigates the chemical space of agonists and antagonists of the three primary opioid receptorsmu-opioid receptor (MOR), kappa-opioid receptor (KOR), and delta-opioid receptor (DOR)by analyzing their physicochemical properties, Murcko scaffolds, and structure-activity relationships (SARs). Using data sets sourced from the ChEMBL database, the study focuses on IC
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Registered trials
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