Structural finding of <i>R/S</i>-3,4-dihydro-2,2-dimethyl-6-halo-4-(substituted phenylaminocarbonylamino)-2<i>H</i>-1-benzopyrans as selective pancreatic β-cells K<sub>ATP-pβ</sub> channel openers
Bibliographic record
Abstract
R/S-3,4-Dihydro-2,2-dimethyl-6-halo-4-(substituted phenylaminocarbonyl-amino)-2H-1-benzopyrans are pancreatic β-cells potassium (KATP-pβ) channel openers with inhibitory effect on insulin secretion. To find the more active and effective benzopyrans as selective potassium (KATP-pβ) channel openers towards the pancreatic tissues, quantitative structure–activity relationships (QSAR) study was performed using E-state and R-state indices along with Wang–Ford charges, n-octanol/water partition coefficient, molar refractivity, and indicator parameters. QSAR models were developed by statistical techniques, e.g., multiple linear regression (MLR), principle component regression analysis (PCRA), and partial least squares (PLS) analysis. The generated equations were validated by the leave-one-out cross-validation method. The models show the importance of ETSA indices of atom numbers 16, 17, 18, 19, 21 as well as 22. The positive coefficient of S16, S17, S18, S19, S21, and S22 indicate that with the increase of the value of E-state indices, desired activity decreases. RTSA index is also important for the biological activity, and the atom numbers 16, 17, 18, 19, 20 and 22 are involved in van der Waals interactions. RTSA index also possesses negative impact on the inhibition of residual insulin secretion. Wang–Ford charges of some particular atoms are also important for the inhibition. Increase of n-octanol/water partition coefficients of compounds inhibit insulin secretion, and the presence of chlorine atom at m- and p- positions of the phenyl ring B is necessary for the inhibition of residual insulin secretion.Key words: benzopyran derivatives, potassium channel openers, PCRA, PLS, QSAR.
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 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".