Interactions between the Cell Membrane Repair Protein S100A10 and Phospholipid Monolayers and Bilayers
Bibliographic record
Abstract
Protein S100A10 participates in different cellular mechanisms and has different functions, especially at the membrane. Among those, it forms a ternary complex with annexin A2 and the C-terminal of AHNAK and then joins the dysferlin membrane repair complex. Together, they act as a platform enabling membrane repair. Both AHNAK and annexin A2 have been shown to have membrane binding properties. However, the membrane binding abilities of S100A10 are not clear. In this paper, we aimed to study the membrane binding of S100A10 in order to better understand its role in the cell membrane repair process. S100A10 was overexpressed by E. coli and purified by affinity chromatography. Using a Langmuir monolayer as a model membrane, the binding parameters and ellipsometric angles of the purified S100A10 were measured using surface tensiometry and ellipsometry, respectively. Phosphorus-31 solid-state nuclear magnetic resonance spectroscopy was also used to study the interaction of S100A10 with lipid bilayers. In the presence of a lipid monolayer, S100A10 preferentially interacts with unsaturated phospholipids. In addition, its behavior in the presence of a bilayer model suggests that S100A10 interacts more with the negatively charged polar head groups than the zwitterionic ones. This work offers new insights on the binding of S100A10 to different phospholipids and advances our understanding of the parameters influencing its membrane behavior.
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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".