Departamento de Química, Instituto de Ciências Naturais, Universidade Federal de Lavras, Lavras, Minas Gerais 37200-900, Brazil.
J Agric Food Chem. 2022 Mar 16;70(10):3321-3330. doi: 10.1021/acs.jafc.1c07352. Epub 2022 Mar 1.
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 = 0.936, = 0.741, and = 0.720, and for herbicidal activity, the model was very predictive ( = 0.981 and = 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.
本工作在分子水平上对一系列修饰的磺酰脲类化合物进行了研究,以确定其抗真菌和除草活性的化学基团。对于饲料保存,需要高抗真菌活性和低植物毒性。应用于定量构效关系(MIA-QSAR)的基于多元图像分析的分子建模研究用于对这些性质进行建模,并指导新的农用化学品候选物的设计。结果表明,MIA-QSAR 模型可靠、稳健且具有预测性;对于抗真菌活性,主要验证参数的平均值分别为 = 0.936、 = 0.741 和 = 0.720,对于除草活性,该模型具有很好的预测性( = 0.981 和 = 0.944)。通过 MIA-图的解释,提出了 46 种具有潜在改进性能的新型磺酰脲类化合物,其中 9 种具有有希望的计算选择指数。进行对接研究以验证 QSAR 预测,并了解所提出的配体与乙酰羟酸合酶的相互作用模式。