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Risk assessment of honey bee stressors based on in silico analysis of molecular interactions

A global decline of the honey bee Apis mellifera has been observed in the last decades. This pollinator plays a fundamental role in food production and the economy in Europe. The decline of honey bee colonies is linked to several stressors, including pesticides. The current pesticide risk assessment...

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Autores principales: del Águila Conde, Mónica, Febbraio, Ferdinando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749446/
https://www.ncbi.nlm.nih.gov/pubmed/36531268
http://dx.doi.org/10.2903/j.efsa.2022.e200912
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author del Águila Conde, Mónica
Febbraio, Ferdinando
author_facet del Águila Conde, Mónica
Febbraio, Ferdinando
author_sort del Águila Conde, Mónica
collection PubMed
description A global decline of the honey bee Apis mellifera has been observed in the last decades. This pollinator plays a fundamental role in food production and the economy in Europe. The decline of honey bee colonies is linked to several stressors, including pesticides. The current pesticide risk assessment of honey bees in Europe focuses on lethal effects and lacks reflection on sublethal effects. A better understanding of the consequences that exposure to these chemicals has on honey bees is still needed. In this context, the aim of this European Food Risk Assessment Fellowship Programme fellowship project has been to use in silico methodologies, such as virtual screening, as a first step to identify possible interactions at the molecular level between A. mellifera proteins and pesticide ligands. For this purpose, a docking study of the proteins from A. mellifera and pesticide ligands extracted from online databases has been performed by using the software Autodock Vina. The results obtained were a ranking based on the predicted affinity of the pesticides for specific and non‐specific binding sites on bee macromolecules. These results were compared with data obtained from the literature and linked to potential sublethal effects. Finally, a risk assessment analysis of the identified molecular stressors of honey bees was performed. The results of this study are considered a starting point to identify new sources of possible stress for honey bees and thereby contribute to the overall understanding of the honey bee decline.
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spelling pubmed-97494462022-12-15 Risk assessment of honey bee stressors based on in silico analysis of molecular interactions del Águila Conde, Mónica Febbraio, Ferdinando EFSA J Eu‐fora Series 5 A global decline of the honey bee Apis mellifera has been observed in the last decades. This pollinator plays a fundamental role in food production and the economy in Europe. The decline of honey bee colonies is linked to several stressors, including pesticides. The current pesticide risk assessment of honey bees in Europe focuses on lethal effects and lacks reflection on sublethal effects. A better understanding of the consequences that exposure to these chemicals has on honey bees is still needed. In this context, the aim of this European Food Risk Assessment Fellowship Programme fellowship project has been to use in silico methodologies, such as virtual screening, as a first step to identify possible interactions at the molecular level between A. mellifera proteins and pesticide ligands. For this purpose, a docking study of the proteins from A. mellifera and pesticide ligands extracted from online databases has been performed by using the software Autodock Vina. The results obtained were a ranking based on the predicted affinity of the pesticides for specific and non‐specific binding sites on bee macromolecules. These results were compared with data obtained from the literature and linked to potential sublethal effects. Finally, a risk assessment analysis of the identified molecular stressors of honey bees was performed. The results of this study are considered a starting point to identify new sources of possible stress for honey bees and thereby contribute to the overall understanding of the honey bee decline. John Wiley and Sons Inc. 2022-12-14 /pmc/articles/PMC9749446/ /pubmed/36531268 http://dx.doi.org/10.2903/j.efsa.2022.e200912 Text en © 2022 Wiley‐VCH Verlag GmbH & Co. KgaA on behalf of the European Food Safety Authority. https://creativecommons.org/licenses/by-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nd/4.0/ (https://creativecommons.org/licenses/by-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited and no modifications or adaptations are made.
spellingShingle Eu‐fora Series 5
del Águila Conde, Mónica
Febbraio, Ferdinando
Risk assessment of honey bee stressors based on in silico analysis of molecular interactions
title Risk assessment of honey bee stressors based on in silico analysis of molecular interactions
title_full Risk assessment of honey bee stressors based on in silico analysis of molecular interactions
title_fullStr Risk assessment of honey bee stressors based on in silico analysis of molecular interactions
title_full_unstemmed Risk assessment of honey bee stressors based on in silico analysis of molecular interactions
title_short Risk assessment of honey bee stressors based on in silico analysis of molecular interactions
title_sort risk assessment of honey bee stressors based on in silico analysis of molecular interactions
topic Eu‐fora Series 5
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9749446/
https://www.ncbi.nlm.nih.gov/pubmed/36531268
http://dx.doi.org/10.2903/j.efsa.2022.e200912
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