Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA), CONICET, UNLP, Diag. 113 y 64, C.C. 16, Sucursal 4, 1900 La Plata, Argentina.
Centro de Investigación y Desarrollo en Ciencias Aplicadas "Dr. J.J. Ronco" (CINDECA), Departamento de Química, Facultad de Ciencias Exactas, CONICET, UNLP, Calle 47 No. 257, B1900AJK La Plata, Argentina; Cátedra de Química Orgánica, Centro de Investigación en Sanidad Vegetal (CISaV), Facultad de Ciencias Agrarias y Forestales, Universidad Nacional de La Plata, Calles 60 y 119 s/n, B1904AAN La Plata, Argentina.
Sci Total Environ. 2018 Jan 1;610-611:937-943. doi: 10.1016/j.scitotenv.2017.08.119. Epub 2017 Aug 19.
The insecticidal activity of a series of 62 plant derived molecules against the chikungunya, dengue and zika vector, the Aedes aegypti (Diptera:Culicidae) mosquito, is subjected to a Quantitative Structure-Activity Relationships (QSAR) analysis. The Replacement Method (RM) variable subset selection technique based on Multivariable Linear Regression (MLR) proves to be successful for exploring 4885 molecular descriptors calculated with Dragon 6. The predictive capability of the obtained models is confirmed through an external test set of compounds, Leave-One-Out (LOO) cross-validation and Y-Randomization. The present study constitutes a first necessary computational step for designing less toxic insecticides.
对一系列 62 种植物源分子对基孔肯雅热、登革热和寨卡病毒载体埃及伊蚊（双翅目：蚊科）的杀虫活性进行了定量构效关系（QSAR）分析。基于多元线性回归（MLR）的替换法（RM）变量子集选择技术被证明是成功的，用于探索用 Dragon 6 计算的 4885 个分子描述符。通过化合物的外部测试集、留一法（LOO）交叉验证和 Y-随机化来确认所得到模型的预测能力。本研究构成了设计毒性更低的杀虫剂的第一个必要计算步骤。
