6533b7cffe1ef96bd1258e94
RESEARCH PRODUCT
Novel scaffold of natural compound eliciting sweet taste revealed by machine learning
Serge AntonczakLoïc BriandChristine BelloirCédric BouyssetSébastien Fioruccisubject
ScaffoldsweetenerComputer scienceIn silicoMachine learningcomputer.software_genre01 natural sciencesAnalytical ChemistryReceptors G-Protein-Coupled0404 agricultural biotechnologysweet tastenatural compoundsHumans[CHIM]Chemical Sciences[SDV.BBM]Life Sciences [q-bio]/Biochemistry Molecular Biologysweet taste receptor2. Zero hungerbusiness.industryNatural compound010401 analytical chemistrydigestive oral and skin physiologySweet taste04 agricultural and veterinary sciencesGeneral Medicine040401 food scienceChemical space0104 chemical sciences[CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistrymachine learningSweetening AgentsTasteArtificial intelligencebusinesscomputer[CHIM.CHEM]Chemical Sciences/CheminformaticsFood Sciencedescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-09-15 |