Toward Predictive Models of Biased Agonists of the Mu Opioid Receptor

The mu-opioid receptor (MOR), a member of the G-protein-coupled receptor superfamily, is pivotal in pain modulation and analgesia. Biased agonism at MOR offers a promising avenue for developing safer opioid therapeutics by selectively engaging specific signaling pathways. This study presents a compr...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Fernando J. Tun-Rosado (21072443) (author)
مؤلفون آخرون:	Elier E. Abreu-Martínez (21072446) (author), Axel Magdaleno-Rodriguez (21072449) (author), Karina Martinez-Mayorga (1928074) (author)
منشور في:	2025
الموضوعات:	Biochemistry Genetics Molecular Biology Pharmacology Immunology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified maximum common substructures induced conformational states including key residues biological effects still annotated activity data analyzing molecules collectively activity cliff identification safer opioid therapies coupled receptor superfamily toward predictive models modulating signaling pathways newly curated database biased agonists using mu opioid receptor opioid receptor biased signaling biased agonists predictive modeling database provided database described biased ligands biased agonism work underscores study presents starting point specific interactions promising avenue pain modulation interaction patterns experimental approaches comprehensive analysis comparative studies combining computational arrestin assays
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Toward Predictive Models of Biased Agonists of the Mu Opioid Receptor

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