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bioRxiv · 10.1101/2022.01.13.476205

BitterMatch: Recommendation systems for matching molecules with bitter taste receptors

Margulis, E.·Slavutsky, Y.·Lang, T.·Behrens, M.·Benjamini, Y.·Niv, M. Y.
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Abstract

Bitterness is an aversive cue elicited by thousands of chemically diverse compounds. Bitter taste may prevent consumption of foods and jeopardize drug compliance. The G protein-coupled receptors for bitter taste, TAS2Rs, have species-dependent number of subtypes and varying expression levels in extraoral tissues. Molecular recognition by TAS2R subtypes is physiologically important, and presents a challenging case study for ligand-receptor matchmaking. Inspired by hybrid recommendation systems, we developed a new set of similarity features, and created the BitterMatch algorithm that predicts associations of ligands to receptors with ~80% precision at ~50% recall. Associations for several compounds were tested in-vitro, resulting in 80% precision and 42% recall. The encouraging performance was achieved by including receptor properties and integrating experimentally determined ligand-receptor associations with chemical ligand-to-ligand similarities. BitterMatch can predict off-targets for bitter drugs, identify novel ligands and guide flavor design. Inclusion of neighbor-informed similarities improves as experimental data mounts, and provides a generalizable framework for molecule-biotarget matching.

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Margulis, E., Slavutsky, Y., Lang, T., Behrens, M., Benjamini, Y., Niv, M. Y.. 2022-01-15. BitterMatch: Recommendation systems for matching molecules with bitter taste receptors. https://doi.org/10.1101/2022.01.13.476205

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