Cargando…

Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening

Morphine, oxycodone, fentanyl, and other µ-opioid receptors (MOR) agonists have been used for decades in antinociceptive therapies. However, these drugs are associated with numerous side effects, such as euphoria, addiction, respiratory depression, and adverse gastrointestinal reactions, thus, circu...

Descripción completa

Detalles Bibliográficos
Autores principales: Poli, Giulio, Dimmito, Marilisa Pia, Mollica, Adriano, Zengin, Gokhan, Benyhe, Sandor, Zador, Ferenc, Stefanucci, Azzurra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6865014/
https://www.ncbi.nlm.nih.gov/pubmed/31717871
http://dx.doi.org/10.3390/molecules24213872
_version_ 1783472010689511424
author Poli, Giulio
Dimmito, Marilisa Pia
Mollica, Adriano
Zengin, Gokhan
Benyhe, Sandor
Zador, Ferenc
Stefanucci, Azzurra
author_facet Poli, Giulio
Dimmito, Marilisa Pia
Mollica, Adriano
Zengin, Gokhan
Benyhe, Sandor
Zador, Ferenc
Stefanucci, Azzurra
author_sort Poli, Giulio
collection PubMed
description Morphine, oxycodone, fentanyl, and other µ-opioid receptors (MOR) agonists have been used for decades in antinociceptive therapies. However, these drugs are associated with numerous side effects, such as euphoria, addiction, respiratory depression, and adverse gastrointestinal reactions, thus, circumventing these drawbacks is of extensive importance. With the aim of identifying novel peptide ligands endowed with MOR inhibitory activity, we developed a virtual screening protocol, including receptor-based pharmacophore screening, docking studies, and molecular dynamics simulations, which was used to filter an in-house built virtual library of tetrapeptide ligands. The three top-scored compounds were synthesized and subjected to biological evaluation, revealing the identity of a hit compound (peptide 1) endowed with appreciable MOR inverse agonist effect and selectivity over δ-opioid receptors. These results confirmed the reliability of our computational approach and provided a promising starting point for the development of new potent MOR modulators.
format Online
Article
Text
id pubmed-6865014
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-68650142019-12-06 Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening Poli, Giulio Dimmito, Marilisa Pia Mollica, Adriano Zengin, Gokhan Benyhe, Sandor Zador, Ferenc Stefanucci, Azzurra Molecules Article Morphine, oxycodone, fentanyl, and other µ-opioid receptors (MOR) agonists have been used for decades in antinociceptive therapies. However, these drugs are associated with numerous side effects, such as euphoria, addiction, respiratory depression, and adverse gastrointestinal reactions, thus, circumventing these drawbacks is of extensive importance. With the aim of identifying novel peptide ligands endowed with MOR inhibitory activity, we developed a virtual screening protocol, including receptor-based pharmacophore screening, docking studies, and molecular dynamics simulations, which was used to filter an in-house built virtual library of tetrapeptide ligands. The three top-scored compounds were synthesized and subjected to biological evaluation, revealing the identity of a hit compound (peptide 1) endowed with appreciable MOR inverse agonist effect and selectivity over δ-opioid receptors. These results confirmed the reliability of our computational approach and provided a promising starting point for the development of new potent MOR modulators. MDPI 2019-10-27 /pmc/articles/PMC6865014/ /pubmed/31717871 http://dx.doi.org/10.3390/molecules24213872 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
Poli, Giulio
Dimmito, Marilisa Pia
Mollica, Adriano
Zengin, Gokhan
Benyhe, Sandor
Zador, Ferenc
Stefanucci, Azzurra
Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening
title Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening
title_full Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening
title_fullStr Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening
title_full_unstemmed Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening
title_short Discovery of Novel µ-Opioid Receptor Inverse Agonist from a Combinatorial Library of Tetrapeptides through Structure-Based Virtual Screening
title_sort discovery of novel µ-opioid receptor inverse agonist from a combinatorial library of tetrapeptides through structure-based virtual screening
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6865014/
https://www.ncbi.nlm.nih.gov/pubmed/31717871
http://dx.doi.org/10.3390/molecules24213872
work_keys_str_mv AT poligiulio discoveryofnovelμopioidreceptorinverseagonistfromacombinatoriallibraryoftetrapeptidesthroughstructurebasedvirtualscreening
AT dimmitomarilisapia discoveryofnovelμopioidreceptorinverseagonistfromacombinatoriallibraryoftetrapeptidesthroughstructurebasedvirtualscreening
AT mollicaadriano discoveryofnovelμopioidreceptorinverseagonistfromacombinatoriallibraryoftetrapeptidesthroughstructurebasedvirtualscreening
AT zengingokhan discoveryofnovelμopioidreceptorinverseagonistfromacombinatoriallibraryoftetrapeptidesthroughstructurebasedvirtualscreening
AT benyhesandor discoveryofnovelμopioidreceptorinverseagonistfromacombinatoriallibraryoftetrapeptidesthroughstructurebasedvirtualscreening
AT zadorferenc discoveryofnovelμopioidreceptorinverseagonistfromacombinatoriallibraryoftetrapeptidesthroughstructurebasedvirtualscreening
AT stefanucciazzurra discoveryofnovelμopioidreceptorinverseagonistfromacombinatoriallibraryoftetrapeptidesthroughstructurebasedvirtualscreening