A QSTR-Based Expert System to Predict Sweetness of Molecules

Frontiers in Chemistry

Andrea Mauri²  Roberto Todeschini³  Davide Ballabio³  Viviana Consonni³  Francesca Grisoni³  Cristian Rojas⁴  Piercosimo Tripaldi⁴ 

[1] Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas, CONICET, Universidad Nacional de La PlataLa Plata, Argentina;Kode s.r.l.Pisa, Italy;Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-BicoccaMilan, Italy;Vicerrectorado de Investigaciones, Universidad del AzuayCuenca, Ecuador;

关键词: sweetness;    QSAR;    molecular descriptors;    classification;    expert system;   

DOI  :  10.3389/fchem.2017.00053

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown