Sweetness prediction of natural compounds

Food Chemistry

Volumn 221, Issue , 2017, Pages 1421-1425

  Chéron, Jean Baptiste ^a   Casciuc, Iuri ^a   Golebiowski, Jérôme ^a   Antonczak, Serge ^a   Fiorucci, Sébastien ^a  

^a UNIVERSITÉ CÔTE D'AZUR   (France)

Author keywords

Chemical space; Natural compounds; Structure activity relationship; Sweeteners

Indexed keywords

CHEMICAL ANALYSIS; CHEMICAL COMPOUNDS; DATABASE SYSTEMS; FOOD ADDITIVES; FORECASTING; HYDROGEN BONDS; SCAFFOLDS; STRUCTURES (BUILT OBJECTS);

CHEMICAL SPACE; HYDROGEN BOND DONORS; NATURAL COMPOUNDS; PHYSICOCHEMICAL PROPERTY; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP MODELING; STRUCTURE ACTIVITY RELATIONSHIPS; SWEETENERS; TOXICITY PROPERTIES;

COMPLEXATION;

NATURAL PRODUCT; SAPONIN; STEVIOSIDE; SWEETENING AGENT; BIOLOGICAL PRODUCT;

ARTICLE; BITTER TASTE; COMPUTER MODEL; CONTROLLED STUDY; HYDROGEN BOND; HYDROPHOBICITY; LOW CALORY DIET; MACHINE LEARNING; MOLECULAR WEIGHT; PROTON TRANSPORT; QUANTITATIVE STRUCTURE ACTIVITY RELATION; SUPERVISED MACHINE LEARNING; SWEETNESS; CHEMISTRY; HUMAN; STRUCTURE ACTIVITY RELATION;

BIOLOGICAL PRODUCTS; HUMANS; STRUCTURE-ACTIVITY RELATIONSHIP; SWEETENING AGENTS;

EID: 85006247369     PISSN: 03088146     EISSN: 18737072     Source Type: Journal    
DOI: 10.1016/j.foodchem.2016.10.145     Document Type: Article

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