New nitric oxide-releasing indomethacin derivatives with 1,3-thiazolidine-4-one scaffold: Design, synthesis, in silico and in vitro studies
Bibliographic record
Abstract
In this study we present design and synthesis of nineteen new nitric oxide-releasing indomethacin derivatives with 1,3-thiazolidine-4-one scaffold (NO-IND-TZDs) (6a-s), as a new safer and efficient multi-targets strategy for inflammatory diseases. The chemical structure of all synthesized derivatives (intermediaries and finals) was proved by NMR and mass spectroscopic analysis. In order to study the selectivity of NO-IND-TZDs for COX isoenzymes (COX-1 and COX-2) a molecular docking study was performed using AutoDock 4.2.6 software. Based on docking results, COX-2 inhibitors were designed and 6o appears as the most selective derivative which showed an improved selective index compared with indomethacin (IND) and diclofenac (DCF), used as reference drugs. The biological evaluation of 6a-s, using in vitro assays has included the anti-inflammatory and antioxidant effects as well as the nitric oxide (NO) release. Referring to the anti-inflammatory effects, the most active compound was 6i, which was more active than IND and aspirin (ASP) in term of denaturation effect, on bovine serum albumin (BSA), as indirect assay to predict the anti-inflammatory effect. An appreciable anti-inflammatory effect, in reference with IND and ASP, was also showed by 6k, 6c, 6q, 6o, 6j, 6d. The antioxidant assay revealed the compound 6n as the most active, being 100 times more active than IND. The compound 6n showed also the most increase capacity to release NO, which means is safer in terms of gastro-intestinal side effects. The ADME-Tox study revealed also that the NO-IND-TZDs are generally proper for oral administration, having optimal physico-chemical and ADME properties. We can conclude that the compounds 6i and 6n are promising agents and could be included in further investigations to study in more detail their pharmaco-toxicological profile.
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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) | 0.001 | 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".