QSAR models for the Fumigant Activity Prediction of Essential Oils

DUCHOWICZ, PABLO ROMAN; COMELLI, NIEVES C.; BENNARDI, DANIEL O.; ORTIZ, ERLINDA DEL V.

JOURNAL OF MOLECULAR GRAPHICS & MODELLING.

ELSEVIER SCIENCE INC

Lugar: Amsterdam; Año: 2020 vol. 101

1093-3263

The Quantitative Structure-Activity Relationships (QSAR) theory, which allows predicting the insecticidal activity of chemical compounds through calculations from the molecular structure, is applied on 23 essential oils composed of 402 structurally diverse compounds at different chemical compositions. A large number of 114,871 conformation-independent molecular descriptors are computed through different types of freely available open-source programs. Mixture descriptors are calculated based on molecular descriptors of the essential oil components and their composition. The best resulting threedescriptor linear regression models are established through the Replacement Method variable subset selection approach. The results obtained in the present work are interesting for predicting the fumigant activity of these essential oil complex mixtures, by means of simple non-conformational QSAR models.