Antioxidative Peptides from Proteolytic Hydrolysates of False Abalone (Volutharpa ampullacea perryi): Characterization, Identification, and Molecular Docking
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Antioxidative peptides were produced from false abalone (Volutharpa ampullacea perryi) using enzymatic hydrolysis. Trypsin produced the most bioactive hydrolysates with the highest scavenging ABTS+• free radicals compared to pepsin, alcalase, neutrase, and flavourzyme. The response surface methodology studies on trypsin hydrolysis indicated that the hydrolysis temperature, time, and pH were interacted with each other (p < 0.05), and the optimal conditions were hydrolysis at 51.8 °C for 4.1 h, pH 7.7 and the maximum predicted hydrolysis degree was 13.18% and ABTS+• scavenging activity of 79.42%. The optimized hydrolysate was subjected to ultrafiltration fractionation, and the fraction with MW < 3 kDa showed the highest ABTS+• scavenging activity. There were 193 peptide sequences identified from this peptide fraction and 133 of them were successfully docked onto human myeloperoxidase (MPO), an enzyme involved in forming reactive oxidants in vivo. The highest scored peptide, no. 39, consists of DTETGVPT. Its structure and molecular interactions with MPO active site were compared with previously characterized peptide hLF1-11. The interactions between peptide no. 39 and MPO include electrostatic charge, hydrogen bonds, and covalent bonds. The antioxidative peptide produced in this research may exert antioxidant activity in vivo due to its potential inhibition effect on MPO.
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.
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 it