Quadrupolar central transition (QCT) and <sup>13</sup>C NMR competition studies of metal ion binding to ovotransferrin
Bibliographic record
Abstract
The transferrins are a family of relatively large bilobal proteins that play a major role in the transport of Fe3+, as well as several other physiological and nonphysiological metal ions. Transferrins can also act as antimicrobial agents, by tightly sequestering iron and making it unavailable for bacterial growth. Using a combination of quadrupolar central transition (QCT) metal ion NMR (27Al, 45Sc, 51V, and 71Ga) and 13C NMR, the binding and displacement of a variety of metal ions to ovotransferrin was studied through direct metal ion competition experiments. The metal ions investigated (Al3+, Co3+, Fe3+, Ga3+, In3+, Sc3+, Y3+, and VO2+) were of differing ionic radius and charge, thus allowing for an assessment of how these factors contribute to metal ion affinity. The competition for the N- and C-terminal metal ion binding sites on ovotransferrin was directly followed by metal ion QCT NMR. Moreover, 13C NMR was used to study the two protein-bound synergistic anions (13C-labeled carbonate), whose chemical shifts are distinct and dependent on the bound metal ion that is present in the binding sites. The observed order of decreasing affinity for the metal ions studied was Fe3+ ≈ In3+ ≥ Sc3+ ≥ Ga3+ > Al3+ > VO2+ > Y3+ ≥ Co3+. These results illustrate how a combination of multinuclear solution NMR methods can provide unique insights into the ligand binding properties of larger metalloproteins.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".