Investigation of the relationship between ergocristinine and vascular receptors
Bibliographic record
Abstract
Ergot alkaloids are secondary metabolites that exist in two configurations, the C-8-R-isomer (R-epimer), and the C-8-S-isomer (S-epimer). Toxic effects of ergot, such as vasoconstriction, have been primarily attributed to the R-epimer bioactivity, as compared to the S-epimer. Recent studies demonstrated potential bioactivity of S-epimers. Therefore, further cost-effective investigations of the S-epimers are needed. The present study investigated the S-epimer - vascular receptor binding relationship. An in silico molecular docking approach, utilizing AutoDock Vina and DockThor, was used to determine if the S-epimer (ergocristinine) binds to vascular receptors and to compare the binding affinity and interactions to the corresponding R-epimer (ergocristine) and a structural analogue (lysergic acid amide). The binding energy (kcal/mol) of ergocristinine was − 9.7 or − 11.0 to the serotonin (5-HT) 2 A receptor and − 8.7 or − 11.4 to the alpha 2 A adrenergic receptor, depending on the software used. A hydrogen bond was formed between ergocristinine and amino acid residues of the 5-HT 2 A and alpha 2 A adrenergic receptor binding sites, with bond lengths of 3.10 Å and 3.28 Å, respectively. Binding affinities and molecular interactions among the ligands to each receptor differed. Different affinities and interactions may relate to differences in the chemical structures. The binding affinities and strong molecular interactions of the S-epimer to vascular receptors may contribute to the observed physiological manifestations that occur after ergot alkaloid exposure. The results of the present study suggest further investigation on the receptor binding of the S-epimers of ergot alkaloids.
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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) | 0.000 | 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) | 0.001 | 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 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".