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

Food Chem. 2020 Sep 15:324:126864. doi: 10.1016/j.foodchem.2020.126864. Epub 2020 Apr 18.

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

MeSH terms

  • Humans
  • Machine Learning*
  • Receptors, G-Protein-Coupled / agonists
  • Receptors, G-Protein-Coupled / metabolism
  • Sweetening Agents / analysis*
  • Taste / physiology*

Substances

  • Receptors, G-Protein-Coupled
  • Sweetening Agents