Literature DB >> 32344344

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

Cédric Bouysset1, Christine Belloir2, Serge Antonczak1, Loïc Briand2, Sébastien Fiorucci3.   

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.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Keywords:  Machine learning; Natural compounds; Sweet taste; Sweet taste receptor; Sweetener

Year:  2020        PMID: 32344344     DOI: 10.1016/j.foodchem.2020.126864

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  2 in total

1.  Pharmacology of TAS1R2/TAS1R3 Receptors and Sweet Taste.

Authors:  Maik Behrens
Journal:  Handb Exp Pharmacol       Date:  2022

2.  ChemTastesDB: A curated database of molecular tastants.

Authors:  Cristian Rojas; Davide Ballabio; Karen Pacheco Sarmiento; Elisa Pacheco Jaramillo; Mateo Mendoza; Fernando García
Journal:  Food Chem (Oxf)       Date:  2022-02-21
  2 in total

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