@ARTICLE{10.3389/fchem.2017.00053, AUTHOR={Rojas, Cristian and Todeschini, Roberto and Ballabio, Davide and Mauri, Andrea and Consonni, Viviana and Tripaldi, Piercosimo and Grisoni, Francesca}, TITLE={A QSTR-Based Expert System to Predict Sweetness of Molecules}, JOURNAL={Frontiers in Chemistry}, VOLUME={5}, YEAR={2017}, URL={https://www.frontiersin.org/articles/10.3389/fchem.2017.00053}, DOI={10.3389/fchem.2017.00053}, ISSN={2296-2646}, ABSTRACT={This work describes a novel approach based on advanced molecular similarity to predict the sweetness of chemicals. The proposed Quantitative Structure-Taste Relationship (QSTR) model is an expert system developed keeping in mind the five principles defined by the Organization for Economic Co-operation and Development (OECD) for the validation of (Q)SARs. The 649 sweet and non-sweet molecules were described by both conformation-independent extended-connectivity fingerprints (ECFPs) and molecular descriptors. In particular, the molecular similarity in the ECFPs space showed a clear association with molecular taste and it was exploited for model development. Molecules laying in the subspaces where the taste assignation was more difficult were modeled trough a consensus between linear and local approaches (Partial Least Squares-Discriminant Analysis and N-nearest-neighbor classifier). The expert system, which was thoroughly validated through a Monte Carlo procedure and an external set, gave satisfactory results in comparison with the state-of-the-art models. Moreover, the QSTR model can be leveraged into a greater understanding of the relationship between molecular structure and sweetness, and into the design of novel sweeteners.} }