Aedes aegypti is the primary vector of several infectious viruses that cause yellow, dengue, chikungunya, and Zika fevers. Recently, plant-derived products have been tested as safe and eco-friendly larvicides against Ae. aegypti. The present study aimed to improve QSAR models for 62 larvicidal phytocompounds against Ae. aegypti via the Monte Carlo method based on the index of the ideality of correlation (IIC) criterion. The representation of structures was done with SMILES. Three splits were prepared randomly and three QSAR models were constructed using IIC target function. The molecular descriptors were selected from SMILES descriptors and the hydrogen-filled molecular graphs. The predictability of three models was evaluated on the validation sets, the r ² of which was 0.9770, 0.8660, and 0.8565 for models 1 to 3, respectively. The statistical results of three randomized splits indicated that robust, simple, predictive, and reliable models were obtained for different sets. From the modelling results, important descriptors were identified to enhance and reduce the larvicidal activity of compounds. Based on the identified important descriptors, some new structures of larvicidal compounds were proposed. The larvicidal activity of novel molecules designed further was supported by docking studies. Using the simple QSAR model, one can predict pLC₅₀ of new similarity larvicidal phytocompounds.

埃及伊蚊是引起黄热病，登革热，基孔肯雅热和寨卡热的几种传染性病毒的主要载体。最近，已经对源自植物的产品进行了针对Ae的安全，环保的杀幼虫剂测试。伊蚊。本研究旨在改善针对Ae的62种杀幼虫植物化合物的QSAR模型。通过基于理想相关性（IIC）准则的索引的蒙特卡罗方法的埃及。结构的表示是使用SMILES完成的。随机准备了三个部分，并使用IIC目标函数构建了三个QSAR模型。分子描述符选自SMILES描述符和充氢分子图。三种模式的可预测性的验证组进行了评价，在[R 模型1至3的²个分别为0.9770、0.8660和0.8565。三个随机分组的统计结果表明，针对不同的集合获得了健壮，简单，可预测和可靠的模型。从建模结果中，确定了重要的描述符，以增强和减少化合物的杀幼虫活性。基于已鉴定的重要描述符，提出了一些杀幼虫化合物的新结构。对接研究支持了进一步设计的新型分子的杀幼虫活性。使用简单的QSAR模型，可以预测新的相似性幼虫植物化合物的pLC ₅₀。