Investigation of the `switch-epitope' concept with random peptide libraries displayed as thioredoxin loop fusions
Bibliographic record
Abstract
The 'FLITRX' random peptide library, consisting of dodecamer loop peptides displayed on a thioredoxin-flagellin scaffold on Escherichia coli, was used to select peptide sequences with affinity for a monoclonal antibody. These peptides were further screened for pH- and metal-sensitive antibody binding. Several zinc-sensitive peptides were identified, termed 'switch epitopes'. A soluble, monomeric thioredoxin loop ('Trxloop') insertion analog of a FLITRX switch epitope was constructed and its antibody binding properties were characterized by Western blots. Zinc-dependent antibody recognition was maintained in the Trxloop protein although the apparent antibody affinity was lower. This Trxloop protein bound to an immobilized metal affinity chromatography matrix, similar to a 'histidine-patch' thioredoxin variant, and was reversibly precipitated by 1 mM Zn(2+) or Cu(2+) ions. Residues important for zinc and antibody binding were determined by site-directed mutagenesis. The Trxloop antibody affinity was increased by saturation mutagenesis. Biotinylated Trxloop ('Biotrxloop') variants of the original and improved affinity Trxloop proteins were constructed and characterized by surface plasmon resonance measurements. Increased antibody affinity was partially due to a slower antibody desorption rate, although the relative adsorption rates were dependent on the amount of immobilized Biotrxloop protein, indicating an influence of avidity on the apparent affinity.
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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 | 0.000 | 0.000 |
| 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".