Isolation of Monomeric Human VHS by a Phage Selection
Bibliographic record
Abstract
Human V(H) domains are promising molecules in applications involving antibodies, in particular, immunotherapy because of their human origin. However, they are, in general, prone to aggregation. Therefore, various strategies have been employed to acquire monomeric human V(H)s. We had previously discovered that filamentous phages displaying engineered monomeric V(H) domains gave rise to significantly larger plaques on bacterial lawns than phages displaying wild type V(H)s with aggregation tendencies. Using plaque size as the selection criterion and a phage-displayed naïve human V(H) library we identified 15 V(H)s that were monomeric. Additionally, the V(H)s demonstrated good expression yields, good refolding properties following thermal denaturation, resistance to aggregation during long incubation at 37 degrees C, and to trypsin at 37 degrees C. These 15 V(H)s should serve as good scaffolds for developing immunotherapeutics, and the selection method employed here should have general utility for isolating proteins with desirable biophysical properties.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".