Probing Receptor Binding Activity of Interleukin-8 Dimer Using a Disulfide Trap
Bibliographic record
Abstract
Interleukin-8 (IL-8), a member of the chemokine superfamily, exists as both monomers and dimers, and mediates its function by binding to neutrophil CXCR1 and CXCR2 receptors that belong to the G protein-coupled receptor class. It is now well established that the monomer functions as a high-affinity ligand, but the binding affinity of the dimer remains controversial. The approximately 1000-fold difference between monomer-dimer equilibrium constant (microM) and receptor binding constant (nM) of IL-8 does not allow receptor-binding affinity measurements of the native IL-8 dimer. In this study, we overcame this roadblock by creating a "trapped" nondissociating dimer that contains a disulfide bond across the dimer interface at the 2-fold symmetry point. The NMR studies show that the structure of this trapped dimer is indistinguishable from the native dimer. The trapped dimer, compared to a trapped monomer, bound CXCR1 with approximately 70-fold and CXCR2 with approximately 20-fold lower affinities. Receptor binding involves two interactions, between the IL-8 N-loop and receptor N-domain residues, and between IL-8 N-terminal and receptor extracellular loop residues. In contrast to a trapped monomer that bound an isolated CXCR1 N-domain peptide with microM affinity, the trapped dimer failed to show any binding, indicating that dimerization predominantly perturbs the binding of only the N-loop residues. These results demonstrate that only the monomer is a high-affinity ligand for both receptors, and also provide a structural basis for the lower binding affinity of the dimer.
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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 | 0.000 |
| 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".