Encoding mu-opioid receptor biased agonism with interaction fingerprints
Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein biased agonists of the μ-opioid receptor (MOR) have shown safer therapeutic profiles than non-biased ligands. In this work, we performed exte...
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| Published in: | Journal of computer-aided molecular design Vol. 35; no. 11; pp. 1081 - 1093 |
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| Main Authors: | , , , , , |
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01-11-2021
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| Abstract | Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein biased agonists of the μ-opioid receptor (MOR) have shown safer therapeutic profiles than non-biased ligands. In this work, we performed extensive all-atom molecular dynamics simulations of two markedly biased ligands and a balanced reference molecule. From those simulations, we identified a protein–ligand interaction fingerprint that characterizes biased ligands. Then, we built and virtually screened a database containing 68,740 ligands with proven or potential GPCR agonistic activity. Exemplary molecules that fulfill the interacting pattern for biased agonism are showcased, illustrating the usefulness of this work for the search of biased MOR ligands and how this contributes to the understanding of MOR biased signaling. |
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| AbstractList | Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein biased agonists of the μ-opioid receptor (MOR) have shown safer therapeutic profiles than non-biased ligands. In this work, we performed extensive all-atom molecular dynamics simulations of two markedly biased ligands and a balanced reference molecule. From those simulations, we identified a protein-ligand interaction fingerprint that characterizes biased ligands. Then, we built and virtually screened a database containing 68,740 ligands with proven or potential GPCR agonistic activity. Exemplary molecules that fulfill the interacting pattern for biased agonism are showcased, illustrating the usefulness of this work for the search of biased MOR ligands and how this contributes to the understanding of MOR biased signaling. Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein biased agonists of the μ-opioid receptor (MOR) have shown safer therapeutic profiles than non-biased ligands. In this work, we performed extensive all-atom molecular dynamics simulations of two markedly biased ligands and a balanced reference molecule. From those simulations, we identified a protein–ligand interaction fingerprint that characterizes biased ligands. Then, we built and virtually screened a database containing 68,740 ligands with proven or potential GPCR agonistic activity. Exemplary molecules that fulfill the interacting pattern for biased agonism are showcased, illustrating the usefulness of this work for the search of biased MOR ligands and how this contributes to the understanding of MOR biased signaling. |
| Author | Marmolejo-Valencia, Andrés F. Cosme-Vela, Fernando Madariaga-Mazón, Abraham Nefzi, Adel Martinez-Mayorga, Karina Hernández-Alvarado, R. Bruno |
| Author_xml | – sequence: 1 givenname: R. Bruno orcidid: 0000-0001-6176-9639 surname: Hernández-Alvarado fullname: Hernández-Alvarado, R. Bruno organization: Instituto de Química, Universidad Nacional Autónoma de México – sequence: 2 givenname: Abraham orcidid: 0000-0002-8938-1318 surname: Madariaga-Mazón fullname: Madariaga-Mazón, Abraham email: amadariaga@iquimica.unam.mx organization: Instituto de Química, Universidad Nacional Autónoma de México – sequence: 3 givenname: Fernando orcidid: 0000-0002-8559-6856 surname: Cosme-Vela fullname: Cosme-Vela, Fernando organization: Instituto de Química, Universidad Nacional Autónoma de México – sequence: 4 givenname: Andrés F. orcidid: 0000-0002-3593-9005 surname: Marmolejo-Valencia fullname: Marmolejo-Valencia, Andrés F. organization: Facultad de Química, Universidad Nacional Autónoma de México – sequence: 5 givenname: Adel surname: Nefzi fullname: Nefzi, Adel organization: Center for Translational Science, Florida International University, Torrey Pines Institute for Molecular Studies – sequence: 6 givenname: Karina orcidid: 0000-0002-6974-7941 surname: Martinez-Mayorga fullname: Martinez-Mayorga, Karina email: kmtzm@unam.mx organization: Instituto de Química, Universidad Nacional Autónoma de México |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34713377$$D View this record in MEDLINE/PubMed |
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| CitedBy_id | crossref_primary_10_1039_D3CP05050E |
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| Keywords | Virtual screening Protein–ligand interaction fingerprint Herkinorin Mu-opioid receptor Biased factor Biased agonism |
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| Snippet | Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein... Opioids are potent painkillers, however, their therapeutic use requires close medical monitoring to diminish the risk of severe adverse effects. The G-protein... |
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| SubjectTerms | Algorithms Analgesics Analgesics, Opioid - pharmacology Animal Anatomy Chemistry Chemistry and Materials Science Computer Applications in Chemistry Fingerprints GTP-Binding Proteins - metabolism Histology Ligands Molecular Docking Simulation Molecular dynamics Molecular Dynamics Simulation Morphology Narcotics Physical Chemistry Protein Binding Proteins Receptors Receptors, Opioid, mu - agonists Receptors, Opioid, mu - metabolism Signal Transduction - drug effects |
| Title | Encoding mu-opioid receptor biased agonism with interaction fingerprints |
| URI | https://link.springer.com/article/10.1007/s10822-021-00422-5 https://www.ncbi.nlm.nih.gov/pubmed/34713377 https://www.proquest.com/docview/2597364038 https://search.proquest.com/docview/2590082726 |
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