In silico modeling and experimental validation of 2-oxoimidazolidin-4-sulfonamides as low-toxicity fungicides against Phytophthora infestans

Vasyl Kovalishyn, Diana Hodyna, Ivan Semenyuta, Volodymyr Brovarets, Oleh Shablykin, Svitlana Chumachenko, Larysa Metelytsia
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Abstract

Phytophthora infestans control is a long-standing problem that has caused ongoing difficulties and brought limited success for over a century. Traditional methods, such as fungicides, have drawbacks including high cost, restrictions on organic farming, potential risks to the environment and human health, and the development of resistant strains. In this study, we employed cutting-edge computer-based techniques, including Quantitative Structure-Activity Relationship (QSAR) modeling and molecular docking simulations, to uncover new fungicidal compounds and gain insights into their specific mechanisms of action against P. infestans. QSAR modeling on the number of compounds tested as P. infestans inhibitors was performed using an interactive OCHEM web platform. The predictive ability of the developed classification models had a balanced accuracy (BA) of 77–85 % for the training set and BA = 89–93 % for the validation external test set. During the in vitro testing against P. infestans, thirteen synthesized 2-oxoimidazolidine-4-sulfonamides demonstrated inhibition rates, ranging from 23.6 % to 87.4 %. The fungicidal potential of six of these fungicides ranged from 79.3 % to 87.4 %, which is comparable to the activity of known fungicides. Acute toxicity results using the well-known aquatic marker Daphnia magna showed that the most active sulfonamides 3d, 3f, 3h, 3j, 3k, and 3l, with LC50 values ranging from 13.7 to 52.9 mg/L, are low-toxicity compounds. The molecular docking results demonstrated a potential mechanism of the antifungal action of the studied 2-oxoimidazolidin-4-sulfonamide derivatives via the inhibition of fungal CYP51, a sterol biosynthesis enzyme.

Abstract Image

2-氧咪唑烷-4-磺酰胺作为抗疫霉菌的低毒杀菌剂的计算机模拟和实验验证
一个多世纪以来,控制疫霉是一个长期存在的问题,造成了持续的困难,取得了有限的成功。传统的方法,如杀菌剂,有一些缺点,包括成本高,对有机农业的限制,对环境和人类健康的潜在风险,以及抗性菌株的发展。在这项研究中,我们采用了尖端的基于计算机的技术,包括定量结构-活性关系(QSAR)建模和分子对接模拟,以发现新的杀真菌化合物,并深入了解它们对病原菌的具体作用机制。使用交互式OCHEM网络平台对检测为病原菌抑制剂的化合物数量进行QSAR建模。所建立的分类模型在训练集的预测能力为77 ~ 85%,在验证外部测试集的预测能力为89 ~ 93%。在体外抑菌试验中,13种合成的2-氧咪唑烷-4-磺胺类药物的抑菌率为23.6% ~ 87.4%。其中6种杀菌剂的杀菌力在79.3% ~ 87.4%之间,与已知杀菌剂的活性相当。水蚤的急性毒性实验结果表明,活性最强的磺胺类化合物3d、3f、3h、3j、3k和3l的LC50值在13.7 ~ 52.9 mg/L之间,为低毒化合物。分子对接结果表明,所研究的2-氧咪唑烷-4-磺酰胺衍生物的抗真菌作用可能是通过抑制真菌固醇生物合成酶CYP51来实现的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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