MOLECULAR DOCKING ANALYSIS OF Azadirachta indica CONSTITUENTS AS INHIBITORS OF AFLATOXIN POLYKETIDE SYNTHASE (APKS)
Bibliographic record
Abstract
In the present study, 18 selected Azadirachta indica constituents, which includes azadiractin, azadiron, epicatechin, epoxyazadiradione, gallic acid, gedunin, isomargolonone, kaempferol, mahmoodin, margolone, margolonone, myristinin A, nimbolide, nimocinolide, quercetin, quercitrin, rutin and sugiol were assessed on the docking behaviour of Aflatoxin polyketide synthase (APKS) by utilizing PatchDock method.Furthermore, Molecular physico-chemical, Bioactivity scores and Absorption, Distribution, Metabolism and Excretion (ADME) analyses were also carried out using Molinspiration and Swiss ADME respectively.The molecular Physico-chemical analysis predicted that rutin has shown three violations for Lipinski's rule of five.And whereas, ADME analysis also showed to have high gastro-intestinal (GI) absorption effect for all the ligands (except for azadiractin, quercetin, quercitin and rutin).The docking studies revealed that myristinin A showed the best binding energy (-350.92kcal/mol) for the target enzyme Aflatoxin polyketide synthase (APKS).Thus the present findings provide new insights in understanding 18 Azadirachta indica constituents as a possible inhibitor against PKS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".