Glutamate agonists for treating schizophrenia have affinity for dopamine D2<sup>High</sup> and D3 receptors
Bibliographic record
Abstract
Although the glutamate agonist LY 404,039 has been used to treat schizophrenia, its closest congener LY 379,268 has an affinity for both glutamate and dopamine (DA) D2(High) receptors. Considering that all antipsychotics act on dopamine receptors, and considering that another laboratory reported that LY 379,268 did not have any affinity for the D2(High) receptor, it was necessary to examine whether such glutamate agonists have an affinity for D2 and D3 dopamine receptors in vitro. The present data show that 50-200 nM LY 379,268 inhibited the binding of [(3)H]domperidone and [(3)H](+)PHNO to cloned dopamine D2 receptors consistently and reproducibly by 16% with dissociation constants of 2.1 and 2.5 nM at D2(High), respectively. In addition, LY 379,268 inhibited the binding of [(3)H]domperidone and [(3)H](+)PHNO to cloned dopamine D3 receptors with dissociation constants of 130 and 10 nM, respectively. LY 379,268 also inhibited the binding of [(3)H]domperidone to rat striata with a dissociation constant of 22 nM, predicting a clinical antipsychotic dose of 80-100 mg/day. LY 379,268 appears to act as an agonist at D2(High) and as an antagonist at D3, because guanine nucleotide eliminated the competition at D2(High) but had no effect on the competition at D3. The findings indicate that this type of glutamate agonist, LY 379,268, has a significant affinity for D2(High) and D3 receptors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".