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Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis
Interactions of 21 fentanyl derivatives with μ-opioid receptor (μOR) were studied using experimental and theoretical methods. Their binding to μOR was assessed with radioligand competitive binding assay. A uniform set of binding affinity data contains values for two novel and one previously uncharac...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412969/ https://www.ncbi.nlm.nih.gov/pubmed/30791394 http://dx.doi.org/10.3390/molecules24040740 |
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author | Lipiński, Piotr F. J. Kosson, Piotr Matalińska, Joanna Roszkowski, Piotr Czarnocki, Zbigniew Jarończyk, Małgorzata Misicka, Aleksandra Dobrowolski, Jan Cz. Sadlej, Joanna |
author_facet | Lipiński, Piotr F. J. Kosson, Piotr Matalińska, Joanna Roszkowski, Piotr Czarnocki, Zbigniew Jarończyk, Małgorzata Misicka, Aleksandra Dobrowolski, Jan Cz. Sadlej, Joanna |
author_sort | Lipiński, Piotr F. J. |
collection | PubMed |
description | Interactions of 21 fentanyl derivatives with μ-opioid receptor (μOR) were studied using experimental and theoretical methods. Their binding to μOR was assessed with radioligand competitive binding assay. A uniform set of binding affinity data contains values for two novel and one previously uncharacterized derivative. The data confirms trends known so far and thanks to their uniformity, they facilitate further comparisons. In order to provide structural hypotheses explaining the experimental affinities, the complexes of the studied derivatives with μOR were modeled and subject to molecular dynamics simulations. Five common General Features (GFs) of fentanyls’ binding modes stemmed from these simulations. They include: GF1) the ionic interaction between D147 and the ligands’ piperidine NH(+) moiety; GF2) the N-chain orientation towards the μOR interior; GF3) the other pole of ligands is directed towards the receptor outlet; GF4) the aromatic anilide ring penetrates the subpocket formed by TM3, TM4, ECL1 and ECL2; GF5) the 4-axial substituent (if present) is directed towards W318. Except for the ionic interaction with D147, the majority of fentanyl-μOR contacts is hydrophobic. Interestingly, it was possible to find nonlinear relationships between the binding affinity and the volume of the N-chain and/or anilide’s aromatic ring. This kind of relationships is consistent with the apolar character of interactions involved in ligand–receptor binding. The affinity reaches the optimum for medium size while it decreases for both large and small substituents. Additionally, a linear correlation between the volumes and the average dihedral angles of W293 and W133 was revealed by the molecular dynamics study. This seems particularly important, as the W293 residue is involved in the activation processes. Further, the Y326 (OH) and D147 (Cγ) distance found in the simulations also depends on the ligands’ size. In contrast, neither RMSF measures nor D114/Y336 hydrations show significant structure-based correlations. They also do not differentiate studied fentanyl derivatives. Eventually, none of 14 popular scoring functions yielded a significant correlation between the predicted and observed affinity data (R < 0.30, n = 28). |
format | Online Article Text |
id | pubmed-6412969 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64129692019-04-09 Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis Lipiński, Piotr F. J. Kosson, Piotr Matalińska, Joanna Roszkowski, Piotr Czarnocki, Zbigniew Jarończyk, Małgorzata Misicka, Aleksandra Dobrowolski, Jan Cz. Sadlej, Joanna Molecules Article Interactions of 21 fentanyl derivatives with μ-opioid receptor (μOR) were studied using experimental and theoretical methods. Their binding to μOR was assessed with radioligand competitive binding assay. A uniform set of binding affinity data contains values for two novel and one previously uncharacterized derivative. The data confirms trends known so far and thanks to their uniformity, they facilitate further comparisons. In order to provide structural hypotheses explaining the experimental affinities, the complexes of the studied derivatives with μOR were modeled and subject to molecular dynamics simulations. Five common General Features (GFs) of fentanyls’ binding modes stemmed from these simulations. They include: GF1) the ionic interaction between D147 and the ligands’ piperidine NH(+) moiety; GF2) the N-chain orientation towards the μOR interior; GF3) the other pole of ligands is directed towards the receptor outlet; GF4) the aromatic anilide ring penetrates the subpocket formed by TM3, TM4, ECL1 and ECL2; GF5) the 4-axial substituent (if present) is directed towards W318. Except for the ionic interaction with D147, the majority of fentanyl-μOR contacts is hydrophobic. Interestingly, it was possible to find nonlinear relationships between the binding affinity and the volume of the N-chain and/or anilide’s aromatic ring. This kind of relationships is consistent with the apolar character of interactions involved in ligand–receptor binding. The affinity reaches the optimum for medium size while it decreases for both large and small substituents. Additionally, a linear correlation between the volumes and the average dihedral angles of W293 and W133 was revealed by the molecular dynamics study. This seems particularly important, as the W293 residue is involved in the activation processes. Further, the Y326 (OH) and D147 (Cγ) distance found in the simulations also depends on the ligands’ size. In contrast, neither RMSF measures nor D114/Y336 hydrations show significant structure-based correlations. They also do not differentiate studied fentanyl derivatives. Eventually, none of 14 popular scoring functions yielded a significant correlation between the predicted and observed affinity data (R < 0.30, n = 28). MDPI 2019-02-19 /pmc/articles/PMC6412969/ /pubmed/30791394 http://dx.doi.org/10.3390/molecules24040740 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lipiński, Piotr F. J. Kosson, Piotr Matalińska, Joanna Roszkowski, Piotr Czarnocki, Zbigniew Jarończyk, Małgorzata Misicka, Aleksandra Dobrowolski, Jan Cz. Sadlej, Joanna Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis |
title | Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis |
title_full | Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis |
title_fullStr | Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis |
title_full_unstemmed | Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis |
title_short | Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis |
title_sort | fentanyl family at the mu-opioid receptor: uniform assessment of binding and computational analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412969/ https://www.ncbi.nlm.nih.gov/pubmed/30791394 http://dx.doi.org/10.3390/molecules24040740 |
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