Hybrid lactoferrins containing transferrin C1 or C2 subdomains bind asialoglycoprotein receptors
Bibliographic record
Abstract
The Fe‐binding proteins lactoferrin (Lf) and transferrin (Tf) are structurally similar, each Fe‐binding lobe (N, C) composed of two sub‐domains (N1/N2; C1/C2). Lf, but not Tf, binds the major subunit of the asialoglycoprotein receptor (RHL1) in a galactose‐independent manner. To identify C‐lobe regions involved in RHL1 binding, we generated recombinant Lf‐Tf hybrid proteins in which Tf C1 or C2 subdomains were positioned within a Lf background. cDNAs of human Lf and Tf encoding Lf:Tf C1 and Lf:Tf C2 were constructed and expressed in Sf9 insect cells. Binding constants of purified native and recombinant Lfs for RHL1 were determined by surface plasmon resonance. Binding of desialylated ligands and native and recombinant Lf proteins to immobilized RHL1 required Ca 2+ and neutral pH. Tf did not bind RHL1 under any conditions. Average dissociation constants measured for the various proteins were as follows: native Lf: 138 ± 44 nM; r‐Lf: 87 ± 50 nM; Lf:Tf C1 : 31 ± 28 nM; Lf:TfC2: 150 ± 76 nM; and asialofetuin: 21 ± 16 nM. Binding constants for native and recombinant Lfs did not differ statistically. Thus, Tf C1 or C2 sub‐domains in a Lf background showed no loss of RHL1‐binding activity. We conclude that the RHL1 binding determinants on Lf do not reside solely in one of the C‐lobe subdomains. (Support: Research Corporation , NIH DK‐61984).
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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) | 0.001 | 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) | 0.001 | 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".