Mass Spectrometric Based Mapping of the Disulfide Bonding Patterns of Integrin α Chains
Bibliographic record
Abstract
Integrins are one of the major mediators of cellular adherence. Structurally the component alpha and beta chains are characterized by extensive intrachain disulfide bonding. The assignment of these bonds is currently based on homology with the chains of the integrin alphaIIbbeta3. However, recent crystallographic analysis of the soluble alphaVbeta3 construct indicates that the alphaV chain displays bonding patterns different from those predicted for alphaIIb. In an effort to define the disulfide bonding patterns in integrins, we have used mass spectrometric based approaches to map the human alpha3, alpha5, alphaV, and alphaIIb. The results indicate that there are differences in the disulfide patterns of the alpha chains. These do not correlate with the integrin capacity to bind ligands as all integrins used in the present study displayed functional activity. The differences were observed in the bonding patterns linking the heavy (H) and light (L) components of the of the alpha chains. It was also possible to assign the location in alpha5 of an additional disulfide bond involving a pair of cysteines not present in alphaV or alphaIIb. This second bond between the H and L chains of alpha5 has not been previously described. These results indicate that not all integrin species display the same disulfide bonding patterns. They also highlight the need for caution in the use of assignments based on sequence homology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".