The Molecular Signature of Umami Palatability in Dogs Based on Amino Acid Interactions with Canine Taste Receptors.
Brewer, M.; Kumar, A. H.
Show abstract
Canine feeding behaviour is strongly influenced by taste perception, yet the molecular determinants of palatability, particularly umami taste is unclear. Dogs typically consume food rapidly with minimal mastication, relying on a limited number of taste buds to detect sour, bitter, salty, sweet, and umami flavours. Amino acids are known to play a central role in canine taste, especially in diets rich in animal proteins. In this study, we aimed to identify the specific amino acids that optimally stimulate umami perception in dogs using a receptor-ligand docking approach. A total of 27 canine-specific taste receptors were identified from the UniProt database, comprising three umami, two sweet, five uncharacterized, and seventeen bitter receptors. All 20 naturally occurring amino acids were docked against these receptors using the CB-Dock tool, and binding affinities were systematically analysed. Heat maps of binding energies revealed that tyrosine, tryptophan, arginine, histidine, phenylalanine, glutamine, glutamic acid, and lysine exhibited the strongest interactions with umami and sweet receptors, whereas bitter and unknown receptors showed comparatively weaker affinities. Binding energy ratio analyses further confirmed that amino acids preferentially stimulated umami and sweet receptors, with lysine, histidine, glutamine, glutamic acid, and arginine emerging as key co-stimulators. Functional enrichment analyses indicated that the receptors belong to Class C/3 GPCRs, with membrane-bound sweet receptor complexes and strong associations with sensory perception of umami, sweet, and bitter tastes. These findings provide a molecular basis for enhancing palatability in canine diets, offering practical implications for the formulation of dry dog food and the design of oral veterinary medicines. The study highlights the importance of specific amino acids, potentially in combination with salts, in modulating taste responses and improving food acceptance in dogs.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Savor the flavor — a randomized double-blind study on taste-enhanced placebo analgesia in healthy volunteers 90%
- A long-acting GDF15 analog causes robust, sustained weight loss and reduction of food intake in an obese non-human primate model 88%
- An untargeted metabolomics analysis of exogenous chemicals in human milk and transfer to the infant 88%
Similar papers in this journal
- Intense bitterness of molecules: machine learning for expediting drug discovery 91%
- Machine learning driven acceleration of biopharmaceutical formulation development using Excipient Prediction Software (ExPreSo) 89%
- Mechanistic insights into zearalenone-accelerated colorectal cancer in mice using integrative multi-omics approaches 88%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.