The chloride effect is related to anion binding in determining the rate of iron release from the human transferrin N-lobe
Bibliographic record
Abstract
The major function of human transferrin is to deliver iron from the bloodstream to actively dividing cells. Upon iron release, the protein changes its conformation from 'closed' to 'open'. Extensive studies in vitro indicate that iron release from transferrin is very complex and involves many factors, including pH, the chelator used, an anion effect, temperature, receptor binding and intra-lobe interactions. Our earlier work [He, Mason and Woodworth (1997) Biochem. J. 328, 439-445] using the isolated transferrin N-lobe (recombinant N-lobe of human transferrin comprising residues 1-337; hTF/2N) has shown that anions and pH modulate iron release from hTF/2N in an interdependent manner: chloride retards iron release at neutral pH, but accelerates the reaction at acidic pH. The present study supports this idea and further details the nature of the dual effect of chloride: the anion effect on iron release is closely related to the strength of anion binding to the apoprotein. The negative effect seems to originate from competition between chloride and the chelator for an anion-binding site(s) near the metal centre. With decreasing pH, the strength of anion binding to hTF/2N increases linearly, decreasing the contribution of competition with the chelator. In the meantime, the 'open' or 'loose' conformation of hTF/2N, induced by the protonation of critical residues such as the Lys-206/Lys-296 pair at low pH, enables chloride to enter the cleft and bind to exposed side chains, thereby promoting cleft opening and synergistically allowing removal of iron by the chelator, leading to a positive anion effect. Disabling one or more of the primary anion-binding residues, namely Arg-124, Lys-206 and Lys-296, substantially decreases the anion-binding ability of the resulting mutant proteins. In these cases, the competition for the remaining binding residue(s) is increased, leading to a negative chloride effect or, at most, a very small positive effect, even at low pH.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".