Allovalency observed by transferred NOE: interactions of sulfated tyrosine residues in the N‐terminal segment of CCR5 with the CCL5 chemokine
Bibliographic record
Abstract
The N-terminal segment of the chemokine receptor Human CC chemokine receptor 5 (CCR5), Nt-CCR5, contains four tyrosine residues, Y3, Y10, Y14, and Y15. Sulfation of at least two of these tyrosine residues was found to be essential for high-affinity binding of CCR5 to its chemokine ligands. Here, we show that among the monosulfated Nt-CCR5(8-20) peptide surrogates (sNt-CCR5) those sulfated at Y15 and Y14 have the highest affinity for the CC chemokine ligand 5 (CCL5) chemokine in comparison with monosulfation at position Y10. Sulfation at Y3 was not investigated. A peptide sulfated at both Y14 and Y15 has the highest affinity for CCL5 by up to a factor of 3, in comparison with the other disulfated (sNt-CCR5) peptides. Chemical shift perturbation analysis and transferred nuclear Overhauser effect measurements indicate that the sulfated tyrosine residues interact with the same CCL5-binding pocket and that each of the sulfated tyrosines at positions 10, 14, and 15 can occupy individually the binding site on CCL5 in a similar manner, although with somewhat different affinity, suggesting the possibility of allovalency in sulfated Nt-CCR5 peptides. The affinity of the disulfated peptides to CCL5 could be increased by this allovalency and by stronger electrostatic interactions.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".