Screening structure-activity relationships of cannabinoid receptor antagonists derived from British Columbian marine actinobacteria extracts
Bibliographic record
Abstract
The cold, nutrient-rich waters off British Columbia's coast harbor actinobacteria whose secondary metabolites remain largely unscreened for cannabinoid receptor activity a gap this research addressed. Sediment samples collected from three sites along the Strait of Georgia (depths 30-120 m) yielded 47 actinobacteria isolates, of which 12 produced ethyl acetate extracts with CB1 receptor antagonist activity in a cell-based reporter assay (IC₅₀ < 20 µM). Bioassay-guided fractionation of the three most active isolates produced 24 semi-purified fractions, from which structure-activity relationship (SAR) trends were mapped using calculated physicochemical descriptors (LogP, polar surface area, molecular weight, H-bond donors/acceptors). Fraction F3 from Streptomyces sp. BCM-14 gave the lowest IC₅₀ of 1.83 µM against CB1 with a selectivity index of 8.4 over CB2. SAR analysis showed that moderate lipophilicity (LogP 2.5-3.5) and the presence of an indole-type pharmacophore correlated most strongly with CB1 antagonist potency (Pearson r = −0.74, p<0.001). These marine-derived scaffolds offer starting points for developing selective CB1 antagonists with potential applications in appetite regulation and neuropathic pain management.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".