Quantitative structure-insecticidal activity of essential oils on the human head louse (Pediculus humanus capitis)

• Published in: SAR and QSAR in environmental research Vol. 35; no. 8; pp. 693 - 706
• Main Authors: Duchowicz, P.R., Bennardi, D.O., Fioressi, S.E., Bacelo, D.E.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 02.08.2024; Taylor & Francis Ltd
• Subjects: Biocompatibility; Chemical composition; Composition effects; Essential oils; human head louse; insecticidal activity; Mixtures; molecular descriptors; Oils & fats; Pediculus humanus; Pediculus humanus capitis; Pesticides; Quantitative structure-activity relationships; Regression analysis; Regression models; Structure-activity relationships
• ISSN: 1062-936X; 1029-046X; 1029-046X
• DOI: 10.1080/1062936X.2024.2394497

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 (Pediculus humanus capitis) 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.