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In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands
The kappa opioid receptor (KOR) represents an attractive target for the development of drugs as potential antidepressants, anxiolytics and analgesics. A robust computational approach may guarantee a reduction in costs in the initial stages of drug discovery, novelty and accurate results. In this wor...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399634/ https://www.ncbi.nlm.nih.gov/pubmed/34443366 http://dx.doi.org/10.3390/molecules26164767 |
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author | Stefanucci, Azzurra Iobbi, Valeria Della Valle, Alice Scioli, Giuseppe Pieretti, Stefano Minosi, Paola Mirzaie, Sako Novellino, Ettore Mollica, Adriano |
author_facet | Stefanucci, Azzurra Iobbi, Valeria Della Valle, Alice Scioli, Giuseppe Pieretti, Stefano Minosi, Paola Mirzaie, Sako Novellino, Ettore Mollica, Adriano |
author_sort | Stefanucci, Azzurra |
collection | PubMed |
description | The kappa opioid receptor (KOR) represents an attractive target for the development of drugs as potential antidepressants, anxiolytics and analgesics. A robust computational approach may guarantee a reduction in costs in the initial stages of drug discovery, novelty and accurate results. In this work, a virtual screening workflow of a library consisting of ~6 million molecules was set up, with the aim to find potential lead compounds that could manifest activity on the KOR. This in silico study provides a significant contribution in the identification of compounds capable of interacting with a specific molecular target. The main computational techniques adopted in this experimental work include: (i) virtual screening; (ii) drug design and leads optimization; (iii) molecular dynamics. The best hits are tripeptides prepared via solution phase peptide synthesis. These were tested in vivo, revealing a good antinociceptive effect after subcutaneous administration. However, further work is due to delineate their full pharmacological profile, in order to verify the features predicted by the in silico outcomes. |
format | Online Article Text |
id | pubmed-8399634 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83996342021-08-29 In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands Stefanucci, Azzurra Iobbi, Valeria Della Valle, Alice Scioli, Giuseppe Pieretti, Stefano Minosi, Paola Mirzaie, Sako Novellino, Ettore Mollica, Adriano Molecules Article The kappa opioid receptor (KOR) represents an attractive target for the development of drugs as potential antidepressants, anxiolytics and analgesics. A robust computational approach may guarantee a reduction in costs in the initial stages of drug discovery, novelty and accurate results. In this work, a virtual screening workflow of a library consisting of ~6 million molecules was set up, with the aim to find potential lead compounds that could manifest activity on the KOR. This in silico study provides a significant contribution in the identification of compounds capable of interacting with a specific molecular target. The main computational techniques adopted in this experimental work include: (i) virtual screening; (ii) drug design and leads optimization; (iii) molecular dynamics. The best hits are tripeptides prepared via solution phase peptide synthesis. These were tested in vivo, revealing a good antinociceptive effect after subcutaneous administration. However, further work is due to delineate their full pharmacological profile, in order to verify the features predicted by the in silico outcomes. MDPI 2021-08-06 /pmc/articles/PMC8399634/ /pubmed/34443366 http://dx.doi.org/10.3390/molecules26164767 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Stefanucci, Azzurra Iobbi, Valeria Della Valle, Alice Scioli, Giuseppe Pieretti, Stefano Minosi, Paola Mirzaie, Sako Novellino, Ettore Mollica, Adriano In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands |
title | In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands |
title_full | In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands |
title_fullStr | In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands |
title_full_unstemmed | In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands |
title_short | In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands |
title_sort | in silico identification of tripeptides as lead compounds for the design of kor ligands |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8399634/ https://www.ncbi.nlm.nih.gov/pubmed/34443366 http://dx.doi.org/10.3390/molecules26164767 |
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