Computational Screening of Filamin Mechanical Binding Proteins using AlphaFold2
Bibliographic record
Abstract
Abstract Filamins are dimeric actin binding protein that play a critical role in mechanical signaling. They contain a mechanosensory region (MSR) that naturally folds into a globular closed conformation. Under mechanical stress, the MSR unfolds into an open conformation, exposing binding sites for numerous proteins. Filamins are involved in diverse cellular functions, and their mechanical binding targets are highly context dependent. In this study, we employed AlphaFold2 modeling for screening proteins that specifically recognize the open conformation of filamins. We focused on the Drosophila melanogaster filamin, Cheerio, and conducted a biased screen to identify mechanical binding proteins. We selected the top 132 hits from the initial screening for further characterization. All identified binding proteins specifically recognize the open conformation of the MSR and not the closed conformation. Interestingly, the binding regions of these proteins lack obvious sequence similarity. While some false positives were identified, they could be effectively filtered out based on the secondary structure formed at the binding interface. This study provides a framework for identifying specifically filamin interactions in mechanosignaling.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".