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Molecular Modeling of µ Opioid Receptor Ligands with Various Functional Properties: PZM21, SR-17018, Morphine, and Fentanyl—Simulated Interaction Patterns Confronted with Experimental Data

Molecular modeling approaches are an indispensable part of the drug design process. They not only support the process of searching for new ligands of a given receptor, but they also play an important role in explaining particular activity pathways of a compound. In this study, a comprehensive molecu...

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Autores principales: Podlewska, Sabina, Bugno, Ryszard, Kudla, Lucja, Bojarski, Andrzej J., Przewlocki, Ryszard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7594085/
https://www.ncbi.nlm.nih.gov/pubmed/33053718
http://dx.doi.org/10.3390/molecules25204636
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author Podlewska, Sabina
Bugno, Ryszard
Kudla, Lucja
Bojarski, Andrzej J.
Przewlocki, Ryszard
author_facet Podlewska, Sabina
Bugno, Ryszard
Kudla, Lucja
Bojarski, Andrzej J.
Przewlocki, Ryszard
author_sort Podlewska, Sabina
collection PubMed
description Molecular modeling approaches are an indispensable part of the drug design process. They not only support the process of searching for new ligands of a given receptor, but they also play an important role in explaining particular activity pathways of a compound. In this study, a comprehensive molecular modeling protocol was developed to explain the observed activity profiles of selected µ opioid receptor agents: two G protein-biased µ opioid receptor agonists (PZM21 and SR-17018), unbiased morphine, and the β-arrestin-2-biased agonist, fentanyl. The study involved docking and molecular dynamics simulations carried out for three crystal structures of the target at a microsecond scale, followed by the statistical analysis of ligand–protein contacts. The interaction frequency between the modeled compounds and the subsequent residues of a protein during the simulation was also correlated with the output of in vitro and in vivo tests, resulting in the set of amino acids with the highest Pearson correlation coefficient values. Such indicated positions may serve as a guide for designing new G protein-biased ligands of the µ opioid receptor.
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spelling pubmed-75940852020-10-30 Molecular Modeling of µ Opioid Receptor Ligands with Various Functional Properties: PZM21, SR-17018, Morphine, and Fentanyl—Simulated Interaction Patterns Confronted with Experimental Data Podlewska, Sabina Bugno, Ryszard Kudla, Lucja Bojarski, Andrzej J. Przewlocki, Ryszard Molecules Article Molecular modeling approaches are an indispensable part of the drug design process. They not only support the process of searching for new ligands of a given receptor, but they also play an important role in explaining particular activity pathways of a compound. In this study, a comprehensive molecular modeling protocol was developed to explain the observed activity profiles of selected µ opioid receptor agents: two G protein-biased µ opioid receptor agonists (PZM21 and SR-17018), unbiased morphine, and the β-arrestin-2-biased agonist, fentanyl. The study involved docking and molecular dynamics simulations carried out for three crystal structures of the target at a microsecond scale, followed by the statistical analysis of ligand–protein contacts. The interaction frequency between the modeled compounds and the subsequent residues of a protein during the simulation was also correlated with the output of in vitro and in vivo tests, resulting in the set of amino acids with the highest Pearson correlation coefficient values. Such indicated positions may serve as a guide for designing new G protein-biased ligands of the µ opioid receptor. MDPI 2020-10-12 /pmc/articles/PMC7594085/ /pubmed/33053718 http://dx.doi.org/10.3390/molecules25204636 Text en © 2020 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
Podlewska, Sabina
Bugno, Ryszard
Kudla, Lucja
Bojarski, Andrzej J.
Przewlocki, Ryszard
Molecular Modeling of µ Opioid Receptor Ligands with Various Functional Properties: PZM21, SR-17018, Morphine, and Fentanyl—Simulated Interaction Patterns Confronted with Experimental Data
title Molecular Modeling of µ Opioid Receptor Ligands with Various Functional Properties: PZM21, SR-17018, Morphine, and Fentanyl—Simulated Interaction Patterns Confronted with Experimental Data
title_full Molecular Modeling of µ Opioid Receptor Ligands with Various Functional Properties: PZM21, SR-17018, Morphine, and Fentanyl—Simulated Interaction Patterns Confronted with Experimental Data
title_fullStr Molecular Modeling of µ Opioid Receptor Ligands with Various Functional Properties: PZM21, SR-17018, Morphine, and Fentanyl—Simulated Interaction Patterns Confronted with Experimental Data
title_full_unstemmed Molecular Modeling of µ Opioid Receptor Ligands with Various Functional Properties: PZM21, SR-17018, Morphine, and Fentanyl—Simulated Interaction Patterns Confronted with Experimental Data
title_short Molecular Modeling of µ Opioid Receptor Ligands with Various Functional Properties: PZM21, SR-17018, Morphine, and Fentanyl—Simulated Interaction Patterns Confronted with Experimental Data
title_sort molecular modeling of µ opioid receptor ligands with various functional properties: pzm21, sr-17018, morphine, and fentanyl—simulated interaction patterns confronted with experimental data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7594085/
https://www.ncbi.nlm.nih.gov/pubmed/33053718
http://dx.doi.org/10.3390/molecules25204636
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