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Novel scaffold of natural compound eliciting sweet taste revealed by machine learning

Cédric Bouysset 1 Christine Belloir 2, 3 Serge Antonczak 1 Loïc Briand 2, 3 Sébastien Fiorucci 1
1 ICN - Institut de Chimie de Nice
2 CSGA - Centre des Sciences du Goût et de l'Alimentation [Dijon]
3 UBFC - Université Bourgogne Franche-Comté [COMUE]
Abstract : Sugar replacement is still an active issue in the food industry. The use of structure-taste relationships remains one of the most rational strategy to expand the chemical space associated to sweet taste. A new machine learning model has been setup based on an update of the SweetenersDB and on open-source molecular features. It has been implemented on a freely accessible webserver. Cellular functional assays show that the sweet taste receptor is activated in vitro by a new scaffold of natural compounds identified by the in silico protocol. The newly identified sweetener belongs to the lignan chemical family and opens a new chemical space to explore.
Keywords : sweetener sweet taste receptor machine learning sweet taste natural compounds
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Journal articles
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https://hal.univ-cotedazur.fr/hal-02547525
Contributor : Sébastien Fiorucci <>
Submitted on : Monday, April 20, 2020 - 9:42:34 AM
Last modification on : Monday, October 12, 2020 - 10:28:50 AM

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UNIV-COTEDAZUR | UNIV-BOURGOGNE | CSGA | INC-CNRS | UNICE | CNRS | INRAE

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Cédric Bouysset, Christine Belloir, Serge Antonczak, Loïc Briand, Sébastien Fiorucci. Novel scaffold of natural compound eliciting sweet taste revealed by machine learning. Food Chemistry, Elsevier, 2020, 324, pp.126864. ⟨10.1016/j.foodchem.2020.126864⟩. ⟨hal-02547525⟩

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