New approaches to the design of analgesic medicinal substances
Bibliographic record
Abstract
1.8 channels in the primary sensory neuron membrane. These channels are responsible for the generation of the nociceptive signal; therefore, gamma-pyrones have great therapeutic potential as analgesics, and this effect deserves a deeper understanding. The novelty of our approach to the design of a medicinal substance is based on a combination of the data obtained from living neurons using very sensitive physiological methods and the results of quantum chemical calculations. This approach allows the correlation of the molecular structure of gamma-pyrones with their ability to evoke a physiological response of the neuron. Comenic acid can bind to two calcium cations. One of them is chelated by the carbonyl and hydroxyl functional groups, while the other forms a salt bond with the carboxylate anion. Calcium-bound gamma-pyrones have fundamentally different electrostatic properties from free gamma-pyrone molecules. These two calcium ions are key elements involved in ligand-receptor binding. It is very likely that ion-ionic interactions between these cations and anionic functional groups of the opioid-like receptor activate the latter. The calculated intercationic distance of 9.5 Å is a structural criterion for effective ligand-receptor binding of calcium-bound gamma-pyrones.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".