Identification of Ni2+-binding peptides in sunflower meal protein hydrolysate for deeper understanding of peptide-metal interactions
Bibliographic record
Abstract
Sunflower ( Helianthus annus L.) is one of the most important oil crops in the world. Once oil extracted, sunflower meal by-product could offer a potential alternative for various food applications due to its high protein content. Derived from food protein hydrolysates, metal-binding peptides have attracted attention as bioactive compounds to prevent metal-induced oxidation and diseases. This study aimed to investigate the Ni 2+ -binding ability of sunflower meal protein hydrolysates and ten peptides theoretically present in sunflower proteins using IMAC, switchSENSE®, UV–vis and CD techniques. Single and sequential enzymatic treatments were applied to produce hydrolysates using Protamex® (Prot) and Protamex followed by Flavourzyme® (Prot+Flav), respectively. MS/MS analysis of enriched Ni 2+ -binding peptides fractions revealed different composition of His-containing peptides among hydrolysates; however, similar to the His-containing pure peptides, the Ni 2+ -binding ability of all the hydrolysates was almost identical in IMAC. On the contrary, switchSENSE® studies indicated that the Ni 2+ -binding ability of sunflower peptides does not depend only on the presence of His residues, but also on their position along the polypeptide chain and the presence of proline, suggesting that Prot hydrolysates exhibited the highest Ni 2+ -binding ability. UV–vis and CD data confirmed that sunflower peptides bound onto Ni 2+ through nitrogen atoms from imidazole sidechain of His residues, deprotonated amide bonds and N-terminal amino group, indicating square-planar and also octahedral geometries in the formed complexes. Finally, His-containing peptides without proline could offer a suitable strategy to design metal-binding peptides from sunflower meal by-product, with the most promising motifs being LL H VT and WL H. Derived from food protein hydrolysates, metal-binding peptides have attracted attention as bioactive compounds to prevent metal-induced oxidation and diseases. This study aimed to investigate the Ni 2+ -binding ability of sunflower meal protein hydrolysates and ten peptides theoretically present in sunflower proteins using IMAC, switchSENSE®, UV–vis and CD techniques. • IMAC and switchSENSE® unveiled the chelating profile of peptides and hydrolysates. • Sunflower meal-derived peptides complexed Ni 2+ with 3 N and 4 N coordination modes. • Single hydrolysate possessed the strongest ability to complex Ni 2+ with ATCUN motif. • WLH and LLHVT ATCUN peptides identified as the most interesting Ni 2+ chelator. • 26 metal-chelating peptides with His identified from sunflower meal hydrolysates.
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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 | 0.001 | 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".