Characterization of Single-Domain Antibodies with an Engineered Disulfide Bond
Bibliographic record
Abstract
Camelidae single-domain antibodies (VHHs) represent a unique class of emerging therapeutics. Similar to other recombinant antibody fragments (e.g., Fabs, scFvs), VHHs are amenable to library screening and selection, but benefit from superior intrinsic biophysical properties such as high refolding efficiency, high solubility, no tendency for aggregation, resistance to proteases and chemical denaturants, and high expression, making them ideal agents for antibody-based drug design. Despite these favorable biophysical characteristics, further improvements to VHH stability are desirable when considering applications in adverse environments like high heat, low humidity, pH extremes, and the acidic, protease-rich gastrointestinal tract. Recently, the introduction of a disulfide bond into the hydrophobic core of camelid VHHs increased antibody thermal and conformational stability. Here, we present additional protocols for characterizing the effects of the introduced disulfide bond on a panel of llama VHHs. Specifically, we employ mass spectrometry fingerprinting analysis of VHH peptides to confirm the presence of the introduced disulfide bond, size exclusion chromatography, and surface plasmon resonance to examine the effects on aggregation state and target affinity, and circular dichroism spectroscopy and protease digestion assays to assess the effects on thermal and proteolytic stability. The disulfide bond stabilization strategy can be incorporated into antibody library design and should lead to hyperstabilized single-domain antibodies (VHHs, VHs), and possibly Fabs and scFvs, if selection pressures such as denaturants or proteases are introduced during antibody selection.
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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) | 0.000 | 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".