A QSTR-based expert system to predict sweetness of molecules

• Autores: Rojas Villa, Cristian Xavier; Todeschini, Roberto; Ballabio, Davide; Mauri, Andrea; Consonni, Viviana; Tripaldi, Piercosimo; Grisoni, Francesca
• Año de publicación: 2017
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Ciencias Exactas; Classification; Expert system; Molecular descriptors; QSAR; Sweetness
• Institución: Universidad Nacional de La Plata

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.
Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas
Facultad de Ciencias Exactas