Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA), CONICET, UNLP, La Plata, Argentina.
Cátedra de Química Orgánica, Facultad de Ciencias Agrarias y Forestales, UNLP, La Plata, Argentina.
SAR QSAR Environ Res. 2024 Aug;35(8):693-706. doi: 10.1080/1062936X.2024.2394497. Epub 2024 Aug 30.
In the search for natural and non-toxic products alternatives to synthetic pesticides, the fumigant and repellent activities of 35 essential oils are predicted in the human head louse () through the Quantitative Structure-Activity Relationships (QSAR) theory. The number of constituents of essential oils with weight percentage composition greater than 1% varies from 1 to 15, encompassing up to 213 structurally diverse compounds in the entire dataset. The 27,976 structural descriptors used to characterizing these complex mixtures are calculated as linear combinations of non-conformational descriptors for the components. This approach is considered simple enough to evaluate the effects that changes in the composition of each component could have on the studied bioactivities. The best linear regression models found, obtained through the Replacement Method variable subset selection method, are applied to predict 13 essential oils from a previous study with unknown property data. The results show that the simple methodology applied here could be useful for predicting properties of interest in complex mixtures such as essential oils.
在寻找天然、无毒的产品替代合成农药的过程中,通过定量构效关系(QSAR)理论预测了 35 种精油在人头虱()中的熏蒸和驱避活性。精油的组成成分的数量(以重量百分比计)大于 1%的从 1 到 15 不等,整个数据集共包含多达 213 种结构不同的化合物。用于描述这些复杂混合物的 27976 个结构描述符是通过对各成分的非构象描述符进行线性组合计算得到的。这种方法被认为足够简单,可以评估每个成分的组成变化对所研究的生物活性可能产生的影响。通过替换法变量子集选择方法找到的最佳线性回归模型,被应用于预测来自先前研究的 13 种精油,这些精油具有未知的特性数据。结果表明,这里应用的简单方法可能有助于预测复杂混合物(如精油)中的感兴趣性质。