Mechanism of Formin-Induced Nucleation of Actin Filaments
Bibliographic record
Abstract
A fragment of the yeast formin Bni1 containing the FH1FH2 domains increases the rate of filament nucleation from pure G-actin [Pruyne et al. (2002) Science 297, 612-615]. To determine the mechanism of nucleation, we compared the G-actin dependence of Bni1FH1FH2-induced polymerization with theoretical models. The data best fit a model suggesting that Bni1FH1FH2 stabilizes an actin dimer. We also show that nucleation increases with the square root of the Bni1FH1FH2 concentration. We demonstrate that this relationship is expected for any such nucleator, independent of nucleus size. The proline-rich FH1 domain binds profilin, and deletion of this domain decreases the contribution of profilin-actin to the nucleation. A role for profilin binding to the FH1 domain in filament nucleation was supported by the inability of Bni1FH1FH2 to utilize a mutant profilin, H133S profilin, with defective binding to polyproline. Bni1FH1FH2 partially inhibits barbed-end elongation, and we find that the rate constants for both polymerization and depolymerization are decreased by approximately 50%. Bni1FH1FH2 has no effect on pointed-end kinetics or on the critical concentration. To investigate the domains of Bni1 required for these activities, the experiments were all duplicated with the FH2 domain alone. The FH2 domain is as effective as the FH1FH2 domains together in inhibiting barbed-end kinetics; it is less effective as a nucleator but the mechanism is again best fit by dimer stabilization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".