Amino Acid Derivatives as Bitter Taste Receptor (T2R) Blockers
Bibliographic record
Abstract
In humans, the 25 bitter taste receptors (T2Rs) are activated by hundreds of structurally diverse bitter compounds. However, only five antagonists or bitter blockers are known. In this study, using molecular modeling guided site-directed mutagenesis, we elucidated the ligand-binding pocket of T2R4. We found seven amino acids located in the extracellular side of transmembrane 3 (TM3), TM4, extracellular loop 2 (ECL2), and ECL3 to be involved in T2R4 binding to its agonist quinine. ECL2 residues Asn-173 and Thr-174 are essential for quinine binding. Guided by a molecular model of T2R4, a number of amino acid derivatives were screened for their ability to bind to T2R4. These predictions were tested by calcium imaging assays that led to identification of γ-aminobutryic acid (GABA) and Nα,Nα-bis(carboxymethyl)-L-lysine (BCML) as competitive inhibitors of quinine-activated T2R4 with an IC50 of 3.2 ± 0.3 μM and 59 ± 18 nM, respectively. Interestingly, pharmacological characterization using a constitutively active mutant of T2R4 reveals that GABA acts as an antagonist, whereas BCML acts as an inverse agonist on T2R4. Site-directed mutagenesis confirms that the two novel bitter blockers share the same orthosteric site as the agonist quinine. The signature residues Ala-90 and Lys-270 play important roles in interacting with BCML and GABA, respectively. This is the first report to characterize a T2R endogenous antagonist and an inverse agonist. The novel bitter blockers will facilitate physiological studies focused on understanding the roles of T2Rs in extraoral tissues.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".