Quantitative structure–activity relationships to predict sweet and non-sweet tastes

  • Cristian Rojas
  • Davide Ballabio
  • Viviana Consonni
  • Piercosimo Tripaldi
  • Andrea Mauri
  • Roberto Todeschini
Regular Article
Part of the following topical collections:
  1. CHITEL 2015 - Torino - Italy

Abstract

The aim of this work was the calibration and validation of mathematical models based on a quantitative structure–activity relationship approach to discriminate sweet, tasteless and bitter molecules. The sweet-tasteless and the sweet-bitter datasets included 566 and 508 compounds, respectively. A total of 3763 conformation-independent Dragon molecular descriptors were calculated and subsequently reduced through both unsupervised reduction and supervised selection coupled with the k-nearest neighbors classification technique. A model based on nine descriptors was retained as the optimal one for sweet and tasteless molecules, while a model based on four descriptors was calibrated for the sweetness-bitterness dataset. Models were properly validated through cross-validation and external test sets. The applicability domain of models was investigated, and the interpretation of the role of the molecular descriptors in classifying sweet and non-sweet tastes was evaluated. The classification and the performance of the models presented in this paper are simple but accurate. They are based on a relatively small number of descriptors and a straightforward classification approach. The results presented here indicate that the proposed models can be used to accurately select new compounds as potential sweetener candidates.

Keywords

QSAR k-Nearest neighbors Classification Sweetness 

Supplementary material

214_2016_1812_MOESM1_ESM.xlsx (64 kb)
Supplementary material 1 (XLSX 63 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Cristian Rojas
    • 1
    • 2
  • Davide Ballabio
    • 3
  • Viviana Consonni
    • 3
  • Piercosimo Tripaldi
    • 4
  • Andrea Mauri
    • 3
  • Roberto Todeschini
    • 3
  1. 1.Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas INIFTA (CCT La Plata-CONICET, UNLP)La PlataArgentina
  2. 2.Decanato General de InvestigacionesUniversidad del AzuayCuencaEcuador
  3. 3.Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental SciencesUniversity of Milano-BicoccaMilanItaly
  4. 4.Laboratorio de Química-Física de Alimentos, Facultad de Ciencia y TecnologíaUniversidad del AzuayCuencaEcuador

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