Linear and non-linear QSAR modelling of juvenile hormone esterase inhibitors

Abstract

A tight control of juvenile hormone (JH) titre is crucial during the life cycle of a holometabolous insect. JH metabolism is made through the action of enzymes, particularly the juvenile hormone esterase (JHE). Trifluoromethylketones (TFKs) are able to inhibit this enzyme to disrupt the endocrine function of the targeted insect. In this context, a set of 96 TFKs, tested on Trichoplusia ni for their JHE inhibition, was split into a training set (n = 77) and a test set (n = 19) to derive a QSAR model. TFKs were initially described by 42 CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) descriptors, but a feature selection process allowed us to consider only five descriptors encoding the structural characteristics of the TFKs and their reactivity. A classical and spline regression analysis, a three-layer perceptron, a radial basis function network and a support vector regression were experienced as statistical tools. The best results were obtained with the support vector regression (r ² and  = 0.91). The model provides information on the structural features and properties responsible for the high JHE inhibition activity of TFKs.

Keywords:

• juvenile hormone esterase
• trifluoromethylketones
• spline regression analysis
• artificial neural network
• support vector regression

Acknowledgements

The financial support from the French Ministry of Ecology and Sustainable Development is gratefully acknowledged (PNRPE program).