Molecular docking and comparative molecular similarity indices analysis of estrogenicity of polybrominated diphenyl ethers and their analogues
Bibliographic record
Abstract
Molecular docking and three-dimensional quantitative structure-activity relationships (3D-QSAR) were used to develop models to predict estrogenicity of polybrominated diphenyl ethers (PBDEs), para-hydroxylated polybrominated diphenyl ethers (para-HO-PBDEs), and brominated bisphenol A compounds to the human estrogen receptor alpha (hERalpha). Based on the molecular conformations developed from the molecular docking, predictive comparative molecular similarity indices analysis (CoMSIA) models were developed. The results of CoMSIA modeling with region focusing included were: leave-one-out (LOO) cross-validated coefficient q(2)(LOO) = 0.722 (all 26 compounds), q(2)(LOO) = 0.633 (the training set, 20 compounds), q(2)(LMO, two groups) = 0.520 +/- 0.155 (26 compounds), q(2)(LMO, five groups) = 0.665 +/- 0.068 (26 compounds), predictive r(2), r(2)(pred) = 0.686 (the test set, 6 compounds), and Q(2)(EXT) = 0.678. The 3D-QSAR can be used to infer the activities of compounds with similar structural characteristics. The interaction mechanism between compounds and the hERalpha was explored. Hydrogen bonding of the compound with Glu353 in the hERalpha is an important determinant of the estrogenic activity of para-HO-PBDEs and brominated bisphenol A.
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 | 0.001 |
| 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".