Heuristic molecular lipophilicity potential (HMLP): A 2D‐QSAR study to LADH of molecular family pyrazole and derivatives
Bibliographic record
Abstract
The quantum chemical and structure-based technique heuristic molecular lipophilicity potential (HMLP) is used in the liver alcohol dehydrogenase (LADH) study of molecular family pyrazole and derivatives. The molecular lipophilic index LM, molecular hydrophilic index HM, lipophilic indices lss, and hydrophilic indices hss of the substitutes (fragments), and atomic lipophilicity indices las are constructed and used in QSAR study. The HMLP indices are correlated with bioactivities of 18 pyrazole derivatives according to the 2D QSAR procedure. The multiple linear regression equation between the bioactivities of pyrazole derivatives and HMLP indices are built using partial least square (PLS) with the optimal statistical quantity (r=0.987, s=0.479, F=47.19). The inhibition mechanism of LADH of the pyrazole derivatives is explained according to the physical meaning of HMLP indices. During the HMLP calculations for the 2D QSAR, the only input parameters are the atomic van der Waals radius without the need to resort to any empirical parameters. Accordingly, HMLP can provide a rigorous theoretical approach with a crystal clear physical meaning for the 2D QSAR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".