Computer-Assisted Improvement of Sulfonylureas with Antifungal Properties and Limited Herbicidal Activity: Potential Application in Forage Conservation.
Adriana C de FariaJoyce K DaréElaine F F da CunhaMatheus P FreitasPublished in: Journal of agricultural and food chemistry (2022)
This work reports studies at the molecular level of a series of modified sulfonylureas to determine the chemophoric sites responsible for their antifungal and herbicidal activities. For forage conservation, high antifungal potency and low phytotoxicity are required. A molecular modeling study based on multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR) was performed to model these properties, as well as to guide the design of new agrochemical candidates. As a result, the MIA-QSAR models were reliable, robust, and predictive; for antifungal activity, the averages of the main validation parameters were r 2 = 0.936, q 2 = 0.741, and r 2 pred = 0.720, and for herbicidal activity, the model was very predictive ( r 2 pred = 0.981 and r 2 m = 0.944). From the interpretation of the MIA-plots, 46 novel sulfonylureas with likely improved performance were proposed, from which 9 presented promising calculated selectivity indexes. Docking studies were performed to validate the QSAR predictions and to understand the interaction mode of the proposed ligands with the acetohydroxyacid synthase enzyme.