Selective modulation of orexinergic receptors by neem-derived phytochemicals: Computational analysis of structure-activity relationships
Bibliographic record
Abstract
Orexinergic system dysfunction is the fundamental basis for several neurological illnesses like narcolepsy, insomnia, and drug dependency, yet none of the existing medications are subtype receptor specific. This study examines 124 chemicals from neem to determine if they can be utilised as specific orexinergic receptor modulators using advanced computational methods. The methodology includes detailed clustering, pharmacophoric interaction, pharmacokinetic, statistical, and clustering analyses. Molecular property profiling indicated the majority of the compounds exhibit excellent drug-like qualities (MW 350-450 Da, LogP 0-2), while principal component analysis captured 100% structural variability between two components (92.5% and 7.5%, respectively). Molecular docking simulations indicated selective binding to the 6V9S receptor (-11.3 to -4 kcal/mol) over 4S0V (-9.7 to -4 kcal/mol). Lead compounds Neem_PDB_10257 (Tirucallol) (-11.3 kcal/mol) and Neem_PDB_12072821 ([(5 R,7 R,8 R,9 R,10 R,13S,17 R) -17-(2-methoxy-5-oxo-4,4,8,10,13-pentamethyl-3-oxo-5,6,7,9,11,12,16,17-octahydrocyclopenta[a]phenanthren-7-yl] acetate) were particularly 6V9S selective (>2 kcal/mol difference), whereas Neem_PDB_10160319 ((4S,4aS,5S,10S,13S,14S,17-4,4,10,13,14-pentam -1, 2, 3, 5, 6, 7, 11, 12, 15, 17-decahydrocyclopenta[a]phenanthren-16-one) was most sensitive towards 4S0V. Two top-ranked compound families were discovered by hierarchical cluster analysis with a distance requirement of 35 units, and receptor-specific dendrograms revealed distinctive subcluster branching patterns (4S0V: 5.5 and 6.7 unit subclusters; 6V9S: 7.1 and 7.2 unit subclusters). Interaction pattern (heatmap analysis) identified major interaction hotspots, including TYR348, TRP120, PHE227, and HIS350. Neem_PDB_163184214 (Meliatetraolenone) specifically targeted ASN318 in 6V9S, while Neem_PDB_54580354 (7-Benzoylnimbocinol) favored interaction with GLN134 in 4S0V (>90 interactions). These findings dispute the "one-pharmacophore" theory for orexinergic modulators, showing that intentional functionalization of NEM templates can deliver subtype-selective treatments with maximal sleep-wake modulation and low off-target effects.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".