Purification, characterization and studies of a novel cysteine protease inhibitor from Juglans regia: Implications as a potential biopesticide
Bibliographic record
Abstract
To isolate and characterize a novel phytocystatin from walnut and investigate it for biopesticide development. A battery of methodology was employed. Initially, phytocystatin was extracted and purified from walnut using ammonium sulfate saturation (60–80%), followed by gel filtration chromatography on the Sephacryl S-100 HR column. Further characterization studies including pH and temperature stability, molecular weight, secondary structure, protease inhibitory assay and antimicrobial activity were carried using various techniques viz: spectroscopy, electrophoresis, and circular dichroism (CD) techniques. Thiol protease inhibitor from walnut (WCPI) was isolated and purified with high (71.4%) yield and 184-fold purification. The molecular weight of the purified inhibitor was found to be around 11.2 kDa. Kinetic tests revealed that the inhibitor competitively inhibited papain and other cysteine proteases such as ficin and bromelain. It also exhibited significant antimicrobial activity against bacterial species. Walnut cysteine protease inhibitor (WCPI) from Juglans regia (Kashmiri walnut) was isolated to homogeneity and had features of other members of the phytocystatin family. It demonstrated potential antimicrobial activity and may serve as an initial step towards developing enhanced pest control methods based on natural molecules.
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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) | 0.000 | 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 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".