Mechanically Tightening a Protein Slipknot into a Trefoil Knot
Bibliographic record
Abstract
The knotted/slipknotted polypeptide chain is one of the most surprising topological features found in certain proteins. Understanding how knotted/slipknotted proteins overcome the topological difficulty during the folding process has become a challenging problem. By stretching a knotted/slipknotted protein, it is possible to untie or tighten a knotted polypeptide and even convert a slipknot to a true knot. Here, we use single molecule force spectroscopy as well as steered molecular dynamics (SMD) simulations to investigate how the slipknotted protein AFV3-109 is transformed into a tightened trefoil knot by applied pulling force. Our results show that by pulling the N-terminus and the threaded loop of AFV3-109, the protein can be unfolded via multiple pathways and the slipknot can be transformed into a tightened trefoil knot involving ∼13 amino acid residues as the polypeptide chain is apparently shortened by ∼4.7 nm. The SMD simulation results are largely consistent with our experimental findings, providing a plausible and detailed molecular mechanism of mechanical unfolding and knot tightening of AFV3-109. These simulations reveal that interactions between shearing β-strands on the threaded and knotting loops provide high mechanical resistance during mechanical unfolding.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".