The importance of adding EDTA for the nanopore analysis of proteins
Bibliographic record
Abstract
Nanopore analysis is a promising technique for studying the conformation of proteins and protein/protein interactions. Two proteins (bacterial thioredoxin and maltose binding protein) were subjected to nanopore analysis with α-hemolysin. Two types of events were observed; bumping events with a blockade current less than -40 pA and intercalation events with blockade currents between -40 pA and -100 pA. In potassium phosphate buffer, pH 7.8, both proteins gave intercalation events but the frequency of these events was significantly reduced in TRIS or HEPES buffers especially in the presence of 0.01 mM divalent metal ions. The frequency of events was restored by the addition of EDTA. For maltose binding protein, the frequency of intercalation events was also decreased in the presence of maltose but not lactose to which it does not bind. It is proposed that the events with large blockade currents represent transient intercalation of a loop or end of the protein into the pore and that divalent metal ions inhibit this process. The results demonstrate that the choice of buffer and the effects of metal ion contamination are important considerations in nanopore analysis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".