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The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity
Designer benzodiazepines (DBZDs) represent a serious health concern and are increasingly reported in polydrug consumption-related fatalities. When new DBZDs are identified, very limited information is available on their pharmacodynamics. Here, computational models (i.e., quantitative structure-activ...
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/PMC8398354/ https://www.ncbi.nlm.nih.gov/pubmed/34451817 http://dx.doi.org/10.3390/ph14080720 |
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author | Catalani, Valeria Botha, Michelle Corkery, John Martin Guirguis, Amira Vento, Alessandro Scherbaum, Norbert Schifano, Fabrizio |
author_facet | Catalani, Valeria Botha, Michelle Corkery, John Martin Guirguis, Amira Vento, Alessandro Scherbaum, Norbert Schifano, Fabrizio |
author_sort | Catalani, Valeria |
collection | PubMed |
description | Designer benzodiazepines (DBZDs) represent a serious health concern and are increasingly reported in polydrug consumption-related fatalities. When new DBZDs are identified, very limited information is available on their pharmacodynamics. Here, computational models (i.e., quantitative structure-activity relationship/QSAR and Molecular Docking) were used to analyse DBZDs identified online by an automated web crawler (NPSfinder(®)) and to predict their possible activity/affinity on the gamma-aminobutyric acid A receptors (GABA-ARs). The computational software MOE was used to calculate 2D QSAR models, perform docking studies on crystallised GABA-A receptors (6HUO, 6HUP) and generate pharmacophore queries from the docking conformational results. 101 DBZDs were identified online by NPSfinder(®). The validated QSAR model predicted high biological activity values for 41% of these DBDZs. These predictions were supported by the docking studies (good binding affinity) and the pharmacophore modelling confirmed the importance of the presence and location of hydrophobic and polar functions identified by QSAR. This study confirms once again the importance of web-based analysis in the assessment of drug scenarios (DBZDs), and how computational models could be used to acquire fast and reliable information on biological activity for index novel DBZDs, as preliminary data for further investigations. |
format | Online Article Text |
id | pubmed-8398354 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83983542021-08-29 The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity Catalani, Valeria Botha, Michelle Corkery, John Martin Guirguis, Amira Vento, Alessandro Scherbaum, Norbert Schifano, Fabrizio Pharmaceuticals (Basel) Article Designer benzodiazepines (DBZDs) represent a serious health concern and are increasingly reported in polydrug consumption-related fatalities. When new DBZDs are identified, very limited information is available on their pharmacodynamics. Here, computational models (i.e., quantitative structure-activity relationship/QSAR and Molecular Docking) were used to analyse DBZDs identified online by an automated web crawler (NPSfinder(®)) and to predict their possible activity/affinity on the gamma-aminobutyric acid A receptors (GABA-ARs). The computational software MOE was used to calculate 2D QSAR models, perform docking studies on crystallised GABA-A receptors (6HUO, 6HUP) and generate pharmacophore queries from the docking conformational results. 101 DBZDs were identified online by NPSfinder(®). The validated QSAR model predicted high biological activity values for 41% of these DBDZs. These predictions were supported by the docking studies (good binding affinity) and the pharmacophore modelling confirmed the importance of the presence and location of hydrophobic and polar functions identified by QSAR. This study confirms once again the importance of web-based analysis in the assessment of drug scenarios (DBZDs), and how computational models could be used to acquire fast and reliable information on biological activity for index novel DBZDs, as preliminary data for further investigations. MDPI 2021-07-26 /pmc/articles/PMC8398354/ /pubmed/34451817 http://dx.doi.org/10.3390/ph14080720 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 Catalani, Valeria Botha, Michelle Corkery, John Martin Guirguis, Amira Vento, Alessandro Scherbaum, Norbert Schifano, Fabrizio The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity |
title | The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity |
title_full | The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity |
title_fullStr | The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity |
title_full_unstemmed | The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity |
title_short | The Psychonauts’ Benzodiazepines; Quantitative Structure-Activity Relationship (QSAR) Analysis and Docking Prediction of Their Biological Activity |
title_sort | psychonauts’ benzodiazepines; quantitative structure-activity relationship (qsar) analysis and docking prediction of their biological activity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8398354/ https://www.ncbi.nlm.nih.gov/pubmed/34451817 http://dx.doi.org/10.3390/ph14080720 |
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