Chemically distinct transition states govern rapid dissociation of single L-selectin bonds under force
Bibliographic record
Abstract
Carbohydrate--protein bonds interrupt the rapid flow of leukocytes in the circulation by initiation of rolling and tethering at vessel walls. The cell surface carbohydrate ligands are glycosylated proteins like the mucin P-selectin glycoprotein ligand-1 (PSGL-1), which bind ubiquitously to the family of E-, P-, and L-selectin proteins in membranes of leukocytes and endothelium. The current view is that carbohydrate-selectin bonds dissociate a few times per second, and the unbinding rate increases weakly with force. However, such studies have provided little insight into how numerous hydrogen bonds, a Ca(2+) metal ion bond, and other interactions contribute to the mechanical strength of these attachments. Decorating a force probe with very dilute ligands and controlling touch to achieve rare single-bond events, we have varied the unbinding rates of carbohydrate--selectin bonds by detachment with ramps of force/time from 10 to 100,000 pN/sec. Testing PSGL-1, its outer 19 aa (19FT), and sialyl Lewis(X) (sLe(X)) against L-selectin in vitro on glass microspheres and in situ on neutrophils, we found that the unbinding rates followed the same dependence on force and increased by nearly 1,000-fold as rupture forces rose from a few to approximately 200 pN. Plotted on a logarithmic scale of loading rate, the rupture forces reveal two prominent energy barriers along the unbinding pathway. Strengths above 75 pN arise from rapid detachment (<0.01 sec) impeded by an inner barrier that requires a Ca(2+) bond between a single sLe(X) and the lectin domain. Strengths below 75 pN occur under slow detachment (>0.01 sec) impeded by the outer barrier, which appears to involve an array of weak (putatively hydrogen) bonds.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".