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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/26/16/4767 |
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| author | Azzurra Stefanucci Valeria Iobbi Alice Della Valle Giuseppe Scioli Stefano Pieretti Paola Minosi Sako Mirzaie Ettore Novellino Adriano Mollica |
| author_facet | Azzurra Stefanucci Valeria Iobbi Alice Della Valle Giuseppe Scioli Stefano Pieretti Paola Minosi Sako Mirzaie Ettore Novellino Adriano Mollica |
| author_sort | Azzurra Stefanucci |
| collection | DOAJ |
| 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 <i>pharmacological</i> profile, in order to verify the features predicted by the in silico outcomes. |
| first_indexed | 2024-03-10T08:32:55Z |
| format | Article |
| id | doaj.art-26baa949ab1246b5be864d1c5b3f0890 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-10T08:32:55Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-26baa949ab1246b5be864d1c5b3f08902023-11-22T08:51:50ZengMDPI AGMolecules1420-30492021-08-012616476710.3390/molecules26164767In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR LigandsAzzurra Stefanucci0Valeria Iobbi1Alice Della Valle2Giuseppe Scioli3Stefano Pieretti4Paola Minosi5Sako Mirzaie6Ettore Novellino7Adriano Mollica8Department of Pharmacy, University G. d’Annunzio Chieti, Via dei Vestini 31, 66100 Chieti, ItalyDepartment of Pharmacy (DIFAR), University of Genova, 16128 Genova, ItalyDepartment of Pharmacy, University G. d’Annunzio Chieti, Via dei Vestini 31, 66100 Chieti, ItalyDepartment of Pharmacy, University G. d’Annunzio Chieti, Via dei Vestini 31, 66100 Chieti, ItalyCentro Nazionale Ricerca e Valutazione Preclinica e Clinica dei Farmaci, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, ItalyCentro Nazionale Ricerca e Valutazione Preclinica e Clinica dei Farmaci, Istituto Superiore di Sanità, Viale Regina Elena 299, 00161 Rome, ItalyAdvanced Pharmaceutics and Drug Delivery Laboratory, Leslie L. Dan Faculty of Pharmacy, University of Toronto, 27 King’s College Circle, Toronto, ON M5S 1A1, CanadaNGN Healthcare, Via Nazionale Torrette, 207, 83013 Mercogliano, ItalyDepartment of Pharmacy, University G. d’Annunzio Chieti, Via dei Vestini 31, 66100 Chieti, ItalyThe 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 <i>pharmacological</i> profile, in order to verify the features predicted by the in silico outcomes.https://www.mdpi.com/1420-3049/26/16/4767peptidesmolecular modellingk-opioid receptorantinociceptive effectbinding |
| spellingShingle | Azzurra Stefanucci Valeria Iobbi Alice Della Valle Giuseppe Scioli Stefano Pieretti Paola Minosi Sako Mirzaie Ettore Novellino Adriano Mollica In Silico Identification of Tripeptides as Lead Compounds for the Design of KOR Ligands Molecules peptides molecular modelling k-opioid receptor antinociceptive effect binding |
| 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 | peptides molecular modelling k-opioid receptor antinociceptive effect binding |
| url | https://www.mdpi.com/1420-3049/26/16/4767 |
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