Isolation, characterization and pentamerization of alpha-cobrotoxin specific single-domain antibodies from a naive phage display library: preliminary findings for antivenom development
Bibliographic record
Abstract
Conventional antivenoms to snakebite generated from the serum of immunized animals, often elicit adverse reactions and have mismatched pharmacokinetic profiles with their target toxins due to antibody/toxin size discrepancies which results in poor neutralization. Furthermore, animal immunization protocols are often lengthy and have batch to batch variability. Recombinant V(H)H-based antivenoms may help overcome these problems. Three V(H)H fragments with specificity to alpha-cobrotoxin, a snake neurotoxin from Naja kaouthia venom, were isolated from a naive llama V(H)H phage-display library. Alpha-cobrotoxin-binding specificity was determined using a phage-displayed V(H)H ELISA format. Sequence analysis shows two of the three clones differ by only two amino acid substitutions, while the third is unique. Surface plasmon resonance analysis determined the K(D) values of the interactions to be 2, 3 and 3 microM. These affinities are too low for alpha-cobrotoxin detection in a standard ELISA format, or for practical use as therapeutic agents. However, improved functional affinity was obtained via antibody pentamerization and alpha-cobrotoxin detection was possible using a pentabody-based ELISA. Development of antivenoms composed of a mixture of antibody fragments, such as V(H)Hs and V(H)H multimers, may help match the pharmacokinetic profiles of complex venoms, improving antivenom biodistribution, and toxin neutralization while reducing adverse effects in humans
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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".