Synthesis, characterization, alkaline phosphatase inhibition assay and molecular modeling studies of 1-benzylidene-2-(4-tert- butylthiazol-2-yl) hydrazines
Bibliographic record
Abstract
Alkaline phosphatases are homodimeric protein enzymes which removes phosphates from several types of molecules. These catalyze the hydrolysis of monoesters in phosphoric acid which in turn catalyze a transphosphorylation reaction. Thiazoles are a privileged class of heterocyclic compounds which may potentially serve as effective phosphatase inhibitors. In this regard, the present research paper reports the facile synthesis and characterization of substituted 1-benzylidene-2-(4-tert-butylthiazol-2-yl) hydrazines with excellent yields. The synthesized compounds were tested for inhibitory potential against alkaline phosphatases. The compound 1-(4-Hydroxy, 3-methoxybenzylidene)-2-(4-tert-butylthiazol-2-yl) hydrazine (5e) was found to be the most potent inhibitor of human tissue non-alkaline phosphatase in this group of molecules with an IC50 value of 1.09 ± 0.18 µM. The compound 1-(3,4-dimethoxybenzylidene)-2-(4-tert-butylthiazol-2-yl) hydrazine (5d) exhibited selectivity and potency for human intestinal alkaline phosphatase with an IC50 value of 0.71 ± 0.02 µM. In addition, structure activity relationship and molecular docking studies were performed to evaluate their binding modes with the target site of alkaline phosphatase. The docking analysis revealed that the most active inhibitors showed the important interactions within the binding pockets of human intestinal alkaline phosphatase and human tissue non-alkaline phosphatase and may be responsible for the inhibitory activity of the compound towards the enzymes. Therefore, the screened thiazole derivatives provided an outstanding platform for further development of alkaline phosphatase inhibitors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".