An Engineered ClyA Nanopore Detects Folded Target Proteins by Selective External Association and Pore Entry
Bibliographic record
Abstract
Nanopores have been used in label-free single-molecule studies, including investigations of chemical reactions, nucleic acid analysis, and applications in sensing. Biological nanopores generally perform better than artificial nanopores as sensors, but they have disadvantages including a fixed diameter. Here we introduce a biological nanopore ClyA that is wide enough to sample and distinguish large analyte proteins, which enter the pore lumen. Remarkably, human and bovine thrombins, despite 86% sequence identity, elicit characteristic ionic current blockades, which at -50 mV differ in their main current levels by 26 ± 1 pA. The use of DNA aptamers or hirudin as ligands further distinguished the protein analytes. Finally, we constructed ClyA nanopores decorated with covalently attached aptamers. These nanopores selectively captured and internalized cognate protein analytes but excluded noncognate analytes, in a process that resembles transport by nuclear pores.
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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 | 0.001 | 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".