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.
Rojas, C., Todeschini, R., Ballabio, D., Mauri, A., Consonni, V., Tripaldi, P., et al. (2017). A QSTR-based expert system to predict sweetness of molecules. FRONTIERS IN CHEMISTRY, 5(JUL).
|Citazione:||Rojas, C., Todeschini, R., Ballabio, D., Mauri, A., Consonni, V., Tripaldi, P., et al. (2017). A QSTR-based expert system to predict sweetness of molecules. FRONTIERS IN CHEMISTRY, 5(JUL).|
|Tipo:||Articolo in rivista - Articolo scientifico|
|Carattere della pubblicazione:||Scientifica|
|Presenza di un coautore afferente ad Istituzioni straniere:||Si|
|Titolo:||A QSTR-based expert system to predict sweetness of molecules|
|Autori:||Rojas, C; Todeschini, R; Ballabio, D; Mauri, A; Consonni, V; Tripaldi, P; Grisoni, F|
TODESCHINI, ROBERTO (Secondo)
GRISONI, FRANCESCA (Ultimo)
|Data di pubblicazione:||2017|
|Rivista:||FRONTIERS IN CHEMISTRY|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.3389/fchem.2017.00053|
|Appare nelle tipologie:||01 - Articolo su rivista|