A QSAR analysis of toxicity of <i>Aconitum</i> alkaloids
Bibliographic record
Abstract
Biological activity of Aconitum alkaloids may be related to their toxicity rather than to a specific pharmacological action. A Quantitative structure-activity relationships (QSAR) analysis was performed on the following two groups of alkaloids: compounds with an aroyl/aroyloxy group at R(14) position (yunaconitine, bulleyaconitine, aconitine, beiwutine, nagarine, 3-acetyl aconitine, and penduline), and compounds with the aroyloxy group at R(4) position (N-deacetyllappaconitine, lappaconitine, ranaconitine, N-deacetylfinaconitine, N-deacetylranaconitine). The LD(50) (micromol/kg) of the 12 alkaloids were obtained from the literature. LD(50) was significantly lower in group 1 than in group 2. The steric and core-core repulsion energies were significantly higher in group 1. The total energy and heat of formation and electronic energies were significantly lower in group 1. The reactivity index of N, C1', C4' and C6' were similar between groups. The reactivity index of C2' was significantly higher and the reactivity index of C3' and C5' were significantly lower in group 1. Log P and pKa were similar between groups. Molecular weight was significantly higher in group 1. A significant linear relationship was observed between log LD(50) and either analgesic log ED(50) or local anesthetic log ED(50). The LD(50)/analgesic ED(50) obtained from average values was 5.9 for group 1 and 5.0 for group 2. However, the LD(50)/local anesthetic ED(50) was 40.4 and 318, respectively. The study supports that the analgesic effects of these alkaloids are secondary to their toxic effects whereas alkaloids from group 2 are susceptible to be further studied as local anesthetic agents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".