Metal–Organocatalyst for Detoxification of Phosphorothioate Pesticides: Demonstration of Acetylcholine Esterase Activity
Bibliographic record
Abstract
In recent years, transition metal complexes have been developed for catalytical degradation of a phosphate ester bond, particularly in RNA and DNA; however, less consideration has been given for development of complexes for the degradation of a phosphorothioate bond, as they are the foremost used pesticides in the environment and are toxic to human beings. In this context, we have developed copper complexes of benzimidazolium based ligands for catalytical degradation of a series of organophosphates (parathion, paraoxon, methyl-parathion) at ambient conditions. The copper complexes (assigned as N1–N3) were characterized using single X-ray crystallography which revealed that all three complexes are mononuclear and distorted square planner in geometry. Further, the solution state studies of the prepared complexes were carried out using UV–visible absorption, fluorescence spectroscopy, and cyclic voltametry. The complexes N1 and N2 have benzimidazolium ionic liquid as base attached with two 2-mercapto-benzimidazole pods, whereas complex N3 contains a nonionic ligand. The synthesized copper complexes were evaluated for their catalytic activity for degradation of organophosphates. It is interesting that the complex containing the ionic ligand efficiently degrades phosphorothioate pesticides, whereas complex N3 was not found to be appropriate for degradation due to a weaker conversion rate. The organophosphate degradation studies were monitored by recording absorbance spectra of parathion in the presence of catalyst, i.e., copper complexes with respect to time. The parathion was hydrolyzed into para-nitrophenol and diethyl thiophosphate. Moreover, to analyze the inhibition activity of the pesticides toward acetylcholine esterase enzyme in the presence of prepared metal complexes, Ellman’s assay was performed and revealed that, within 20 min, the inhibition of acetylcholine esterase enzyme decreases by up to 13%.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".