Prediction of the Molecular Lipophilicity of an Alkylphenol Family Using Quantum Chemistry and QSPR Methods

Abstract

This study examined the relationship between the water/octanol partition coefficient of eighteen alkylphenols and molecular descriptors derived from quantum-chemical calculations using a quantitative structure-property relationship (QSPR) approach. The experimental database was divided into a training set of fourteen compounds and a test set of four compounds. Three descriptors, the electronic energy (ET), the energy of the Lowest Unoccupied Molecular Orbital (ELUMO) and the energy gap (ΔEgap) were used to develop a multiple linear regression model. The model showed a strong association between the experimental lipophilicity values and the selected descriptors, with R = 0.9850, R² = 0.9703, a standard deviation of 0.0853, and F = 108.9532. Internal validation using leave-one-out cross-validation and property randomisation, together with external validation using the test set and the Tropsha criteria, was applied to assess model stability and predictive performance. The applicability domain was evaluated using a Williams plot. Within the studied dataset and the defined applicability domain, the model showed close agreement between experimental and predicted water/octanol partition coefficients. The reported validation results indicate that the selected quantum-chemical descriptors can be used to model lipophilicity within this alkylphenol series. Predictions for additional alkylphenols should, however, remain restricted to compounds that fall within the model’s defined applicability domain.