Aggregation-resistant VHs selected by in vitro evolution tend to have disulfide-bonded loops and acidic isoelectric points
Bibliographic record
Abstract
When panned with a transient heat denaturation approach against target enzymes, a human V(H) (antibody heavy chain variable domain) phage display library yielded V(H)s with composite characteristics of binding, non-aggregation and reversible thermal unfolding. Moreover, selection was characterized by enrichment for V(H)s with (i) an even number of disulfide forming Cys residues in complementarity-determining region (CDR) 1 and CDR3 and (ii) acidic isoelectric points. This parallels naturally occurring camelid and shark single-domain antibodies (sdAbs) which are also characterized by (i) solubility and reversible unfolding, (ii) a high occurrence of disulfide forming Cys in their CDRs, particularly, in CDR1 and CDR3 and (iii) acidic V(H)s as inferred here by a pI distribution analysis, reported here, of pools of human and camelid V(H) and V(H)H (camelid heavy chain antibody V(H)) sequences. Our results, reinforced by previous observations by others, suggest that protein acidification may yet be another mechanism nature has devised to create functional sdAbs and that this concept along with the inclusion of inter-CDR disulfide linkages may be applied to human V(H) domains/libraries for non-aggregation optimization. In addition, calculation of theoretical pIs of V(H)s selected by panning may be used for rapid and precise identification of non-aggregating V(H)s.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".