Cysteine engineering of actin self-assembly interfaces
Bibliographic record
Abstract
The Holmes model of filamentous actin (F-actin) and recent structural studies suggest specific atomic interactions between F-actin subunits. We tested these interactions through a cysteine-engineering approach with the goal of inhibiting filament formation by introducing chemical groups at sites important for polymerization. We substituted surface amino acids on the actin molecule with cysteine residues and tested the effect of producing these actin mutant proteins in a yeast expression system. The intrinsic folding and polymerization characteristics of the cysteine-engineered actin proteins were measured. The effect of chemical modification of the introduced cysteine residues on the polymerization of the actin mutant proteins was also examined. Modification of cysteine residues with large hydrophobic reagents resulted in polymerization inhibition. We examined the finding that the D288C actin protein does not polymerize under oxidizing conditions and forms protein aggregates when magnesium and EGTA are present. Chemical crosslinking experiments revealed the presence of a lower dimer when only D288C actin was present. When both D288C and A204C actin were present, crosslinking experiments support the proximity of Asp288 on the barbed end of one subunit to Ala204 on the pointed end of a neighboring subunit in the Holmes model of F-actin.
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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) | 0.000 | 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".