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http://repositorio.ufla.br/jspui/handle/1/49494
Título: | Computer-assisted improvement of Sulfonylureas with antifungal properties and limited herbicidal activity: potential application in forage conservation |
Título(s) alternativo(s): | Computer-assisted improvement of sulfonylureas with antifungal properties and limited herbicidal activity: potential application in forage conservation |
Autores: | Freitas, Matheus Puggina de Ávila, Carla Luiza da Silva Mancini, Daiana Teixeira |
Palavras-chave: | Silagem - Conservação Sulfonilureias Aceto-hidroxiácido sintase Fungicidas Forragem Silage - Conservation Sulfonylureas Acetohydroxyacid synthase Fungicides Forage |
Data do documento: | 15-Mar-2022 |
Editor: | Universidade Federal de Lavras |
Citação: | FARIA, A. C. de. Computer-assisted improvement of Sulfonylureas with antifungal properties and limited herbicidal activity: potential application in forage conservation. 2022. 93 p. Dissertação (Mestrado em Agroquímica) – Universidade Federal de Lavras, Lavras, 2022. |
Resumo: | The conservation of forage for animal feed - silage - requires the use of antifungals as additives to ensure high fermentative efficiency in an anaerobic environment. In this context, new compounds belonging to the class of sulfonylureas have recently been synthesized with the purpose of modifying the chemical structures of analogous and already known substances, improving their antifungal properties and minimizing their herbicidal activities. This work proposes the study at the molecular level of these sulfonylureas, with the objective of finding the chemophoric sites (portions of the molecular structure) responsible for the antifungal activity and for the selectivity (antifungal activity/herbicidal activity) of the molecules to be studied. Accordingly, we employed the computational methodology of molecular modeling MIA-QSAR (Multivariate Image Analysis applied to Quantitative Structure-Activity Relationships), as well as the MIA-Plot tool (to identify the chemophoric sites). The MIAQSAR method was used to find a correlation between the chemical structures of the sulfonylureas with their respective biological properties. As a result, the MIA-QSAR models were reliable, robust, and predictive, i.e. for antifungal activity, the average values for the main validation parameters were r2 = 0.936, q2 = 0.741, and r2 pred = 0.720, whereas for herbicidal activity, the model was predictive (r2 pred = 0.981 and r2 m = 0.944). In this way, and knowing which parts of chemical structures affect the biological properties and how (increasing or decreasing microbiological activity), it was possible to propose 46 new chemical structures with improved properties, from which, 9 presented promising calculated selectivity indexes. Docking studies were carried out in order to validate the QSAR predictions and understanding the mechanisms of action of the compounds under study. |
URI: | http://repositorio.ufla.br/jspui/handle/1/49494 |
Aparece nas coleções: | Agroquímica - Mestrado (Dissertações) |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
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DISSERTAÇÃO_Computer-assisted improvement of Sulfonylureas with antifungal properties and limited herbicidal activity potential application in forage conservation.pdf | 1,33 MB | Adobe PDF | Visualizar/Abrir |
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