Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational Analysis Article Swipe
YOU?
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· 2019
· Open Access
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· DOI: https://doi.org/10.3390/molecules24040740
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).
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/molecules24040740
- https://www.mdpi.com/1420-3049/24/4/740/pdf?version=1550560519
- OA Status
- gold
- Cited By
- 57
- References
- 89
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2914462445
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2914462445Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/molecules24040740Digital Object Identifier
- Title
-
Fentanyl Family at the Mu-Opioid Receptor: Uniform Assessment of Binding and Computational AnalysisWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-02-19Full publication date if available
- Authors
-
Piotr F. J. Lipiński, Piotr Kossoń, Joanna Matalińska, Piotr Roszkowski, Zbigniew Czarnocki, Małgorzata Jarończyk, Aleksandra Misicka, Ján Cz. Dobrowolski, Joanna SadlejList of authors in order
- Landing page
-
https://doi.org/10.3390/molecules24040740Publisher landing page
- PDF URL
-
https://www.mdpi.com/1420-3049/24/4/740/pdf?version=1550560519Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1420-3049/24/4/740/pdf?version=1550560519Direct OA link when available
- Concepts
-
Chemistry, Molecular dynamics, Stereochemistry, Moiety, Dihedral angle, Affinities, Substituent, Ligand (biochemistry), Radioligand, Ring (chemistry), Opioid receptor, Ionic bonding, Piperidine, Binding site, Computational chemistry, Receptor, Molecule, Opioid, Ion, Hydrogen bond, Organic chemistry, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
57Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 7, 2024: 6, 2023: 10, 2022: 11, 2021: 11Per-year citation counts (last 5 years)
- References (count)
-
89Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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