Development of a robust and validated 2D-QSPR model for sweetness potency of diverse functional organic molecules.

In the present report, we have developed a predictive QSPR model using only easily computable two-dimensional (2D) descriptors from diverse classes of sweetening agents to find out the key structural properties which regulate their sweet potency. The available data set was curated to remove salts, mixtures and compounds without having a definite structure. A k-fold double cross validation technique was employed for variable selection prior to development of the final model. The final model was developed using partial least squares (PLS) regression analysis and selected based on a mean absolute error (MAE) based criteria for the validation sets. The model was validated extensively using different internal and external validation strategies in accordance with the Organization for Economic Co-operation and Development (OECD) guidelines. This work presented development of a validated quantitative structure-property relationship (QSPR) model obtained from k-fold double cross-validation technique in order to find out the key structural information required to enhance the sweet potency of the molecules. Finally, we have designed and proposed 13 new molecules based on the insights obtained from the QSPR model. The designed compounds showed good in silico predicted sweetness potency with acceptable ADMET profile.