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A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods
Background: Selectively targeting dopamine receptors (DRs) has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases involving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific...
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/PMC6479630/ https://www.ncbi.nlm.nih.gov/pubmed/30934701 http://dx.doi.org/10.3390/molecules24071196 |
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author | Bueschbell, Beatriz Barreto, Carlos A. V. Preto, António J. Schiedel, Anke C. Moreira, Irina S. |
author_facet | Bueschbell, Beatriz Barreto, Carlos A. V. Preto, António J. Schiedel, Anke C. Moreira, Irina S. |
author_sort | Bueschbell, Beatriz |
collection | PubMed |
description | Background: Selectively targeting dopamine receptors (DRs) has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases involving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific binding mode on a molecular basis has not been fully elucidated. Methods: Homology modeling and molecular dynamics were applied to construct robust conformational models of all dopamine receptor subtypes (D(1)-like and D(2)-like). Fifteen structurally diverse ligands were docked. Contacts at the binding pocket were fully described in order to reveal new structural findings responsible for selective binding to DR subtypes. Results: Residues of the aromatic microdomain were shown to be responsible for the majority of ligand interactions established to all DRs. Hydrophobic contacts involved a huge network of conserved and non-conserved residues between three transmembrane domains (TMs), TM2-TM3-TM7. Hydrogen bonds were mostly mediated by the serine microdomain. TM1 and TM2 residues were main contributors for the coupling of large ligands. Some amino acid groups form electrostatic interactions of particular importance for D(1)R-like selective ligands binding. Conclusions: This in silico approach was successful in showing known receptor-ligand interactions as well as in determining unique combinations of interactions, which will support mutagenesis studies to improve the design of subtype-specific ligands. |
format | Online Article Text |
id | pubmed-6479630 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64796302019-04-30 A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods Bueschbell, Beatriz Barreto, Carlos A. V. Preto, António J. Schiedel, Anke C. Moreira, Irina S. Molecules Article Background: Selectively targeting dopamine receptors (DRs) has been a persistent challenge in the last years for the development of new treatments to combat the large variety of diseases involving these receptors. Although, several drugs have been successfully brought to market, the subtype-specific binding mode on a molecular basis has not been fully elucidated. Methods: Homology modeling and molecular dynamics were applied to construct robust conformational models of all dopamine receptor subtypes (D(1)-like and D(2)-like). Fifteen structurally diverse ligands were docked. Contacts at the binding pocket were fully described in order to reveal new structural findings responsible for selective binding to DR subtypes. Results: Residues of the aromatic microdomain were shown to be responsible for the majority of ligand interactions established to all DRs. Hydrophobic contacts involved a huge network of conserved and non-conserved residues between three transmembrane domains (TMs), TM2-TM3-TM7. Hydrogen bonds were mostly mediated by the serine microdomain. TM1 and TM2 residues were main contributors for the coupling of large ligands. Some amino acid groups form electrostatic interactions of particular importance for D(1)R-like selective ligands binding. Conclusions: This in silico approach was successful in showing known receptor-ligand interactions as well as in determining unique combinations of interactions, which will support mutagenesis studies to improve the design of subtype-specific ligands. MDPI 2019-03-27 /pmc/articles/PMC6479630/ /pubmed/30934701 http://dx.doi.org/10.3390/molecules24071196 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 Bueschbell, Beatriz Barreto, Carlos A. V. Preto, António J. Schiedel, Anke C. Moreira, Irina S. A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods |
title | A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods |
title_full | A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods |
title_fullStr | A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods |
title_full_unstemmed | A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods |
title_short | A Complete Assessment of Dopamine Receptor- Ligand Interactions through Computational Methods |
title_sort | complete assessment of dopamine receptor- ligand interactions through computational methods |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6479630/ https://www.ncbi.nlm.nih.gov/pubmed/30934701 http://dx.doi.org/10.3390/molecules24071196 |
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