“Click” Dendrimers as Anti-inflammatory Agents: With Insights into Their Binding from Molecular Modeling Studies
Bibliographic record
Abstract
These studies explore the relationship between the inhibitory actions of low generation dendrimers in stimulated microglia and dendrimer-enzyme interactions using in silico molecular modeling. Low generation (DG0 and DG1) dendrimers with acetylene and hydroxyl terminal groups were tested for their anti-inflammatory activity in microglia stimulated by lipopolysaccharides (LPS), and the results were compared with those from the established anti-inflammatory agents, ibuprofen and celecoxib. We hypothesized that hydroxyl terminal groups of DG0 and DG1 dendrimers could interact with the active sites of the inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) enzymes due to their small size and favorable electrochemical properties. The enzymatic activity of iNOS and COX-2 was determined in the presence of low generation dendrimers using biochemical assays and their values related to dendrimer docking confirmations from in silico molecular modeling. We found that results from the molecular modeling studies correlated well with the in vitro biological data, suggesting that, indeed, hydroxyl terminal groups of low generation dendrimers enable multivalent macromolecular interactions, resulting in the inhibition of both iNOS and COX-2 enzymes.
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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 | 0.001 |
| 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".