Structure-Activity-Relationship and Bioactivity of Neurotrophic trans-Banglene
Bibliographic record
Abstract
Neurotrophic small molecule natural products are functional analogs of signaling proteins called neurotrophins, which cause a pro-growth, pro-survival, or pro-differentiation response in neuronal cells. While these phenotypic responses are desirable to combat neurodegenerative disease progression, neurotrophin proteins possess pharmacokinetic properties that present challenges to their administration in living organisms, whether in biomedical studies or as therapeutics. Small molecules such as the cis- and trans-banglenes offer attractive alternatives to activate neurotrophic responses. We describe the synthesis and testing of banglene derivatives to establish a structure-activity response for the banglene family. Notably, during the course of our studies trans-banglene was shown to cause nerve growth factor (NGF)-potentiated neuritogenesis that was markedly stronger than the neuritogenic effects of trans-banglene alone. We demonstrate that only (–) trans-banglene is active, while its (+) enantiomer is not, and further demonstrate that select modifications on the cyclohexene ring of trans-banglene does not impair its bioactivity. Finally, to probe the relationship between (–) trans-banglene’s mechanism of ac-tion and canonical NGF signal transduction pathways, we employed kinase inhibitors targeting Pkc, Akt1/2/3 and Erk1/2, designed to inhibit NGF-induced neurotrophic signaling. Interestingly, (–) trans-banglene potentiation of NGF-induced neuri-togenesis was unaffected by the presence of these kinase inhibitors. Collectively, these results suggest a dual-mode of action for (–) trans-banglene (both neurotrophic alone and strongly potentiating of NGF activity), and an independence of its po-tentiating action on Pkc and Erk1/2 enzymatic activity.
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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 | 0.000 |
| 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".