An In Silico QSAR Model Study Using Electrophilicity as a Possible Descriptor Against T. Brucei
Bibliographic record
Abstract
Human African trypanosomiasis (HAT) is a vector-borne sleeping sickness parasitic disease spread through the bite of infected tsetse flies (Glossina genus), which is highly populated in rural Africa. The present study constructed quantitative structure-activity relationship (QSAR) models based on quantum chemical electronic descriptors to bring out the extent to which the electronic factor of the selected compounds affects the HAT activity. Theoretical prediction of toxicity (pIC50) of the series of heterocyclic scaffolds consisting 32 pyridyl benzamide derivatives towards HAT is investigated by considering all possible combinations of electrophilicity index (ω) and the square of electrophilicity index (ω2) as descriptors in the studied models along with other descriptors previously used by Masand et al. A multiple linear regression (MLR) analysis is conducted to develop the models. Further, in order to obtain the variable selection on the overall data set having diverse functional groups, the analysis using sum of ranking differences methodology with ties is carried out.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".