Molecular modeling and mutagenesis of the ligand‐binding pocket of the mGlu3 subtype of metabotropic glutamate receptor
Bibliographic record
Abstract
A homology model of the extracellular domain of the mGlu3 subtype of metabotropic glutamate (mGlu) receptor was generated and tested using site-directed mutagenesis, a radioligand-binding assay using the Group II selective agonist (2S,2'R,3'R)-2-(2',3'-[3H]dicarboxycyclopropyl) glycine ([3H]DCG-IV), and in a fluorescence-based functional assay in live transiently transfected human embryonic kidney cells. Ten of the 12 mGlu3 mutants (R64A, R68A, Y150A, S151A, T174A, D194A, Y222A, R277A, D301A and K389) showed either no binding or a 90% or greater loss of specific [3H]DCG-IV binding. Several analogous mutations in mGlu2 supported the results obtained with mGlu3. These results demonstrate that the binding of [3H]DCG-IV to mGlu3 is exceptionally sensitive to mutagenesis-induced perturbations. In silico docking of DCG-IV into the agonist binding pocket of mGlu3 facilitated the interpretation the mutagenesis results. Tyrosines 150 and 222, and arginine 277 show close contacts with the third carboxylic acid group in DCG-IV, which is not present in glutamate or (2S,1'S,2'S)-2-(carboxycyclopropyl)glycine (L-CCG-I). Mutation of these three amino acids to alanine resulted in a near complete loss of receptor activation by DCG-IV and retention of near wild-type affinity for L-CCG-I. It is proposed that hydrogen bonding between this carboxylate and tyrosines 150 and 222 and arginine 277 provide a partial explanation for the high affinity and Group II selectivity of DCG-IV. These findings define the essential features of the ligand-binding pocket of mGlu3 and, together with other recent studies on mGlu receptors, provide new opportunities for structure-based drug design.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".