Sequence tolerance of immunoglobulin variable domain framework regions to noncanonical intradomain disulfide linkages
Bibliographic record
Abstract
Most immunoglobulin (Ig) domains bear only a single highly conserved canonical intradomain, inter-β-sheet disulfide linkage formed between Cys23-Cys104, and incorporation of rare noncanonical disulfide linkages at other locations can enhance Ig domain stability. Here, we exhaustively surveyed the sequence tolerance of Ig variable (V) domain framework regions (FRs) to noncanonical disulfide linkages. Starting from a destabilized V H domain lacking a Cys23-Cys104 disulfide linkage, we generated and screened phage-displayed libraries of engineered V H s, bearing all possible pairwise combinations of Cys residues in neighboring β-strands of the Ig fold FRs. This approach identified seven novel Cys pairs in V H FRs (Cys4-Cys25, Cys4-Cys118, Cys5-Cys120, Cys6-Cys119, Cys22-Cys88, Cys24-Cys86, and Cys45-Cys100; the international ImMunoGeneTics information system numbering), whose presence rescued domain folding and stability. Introduction of a subset of these noncanonical disulfide linkages (three intra-β-sheet: Cys4-Cys25, Cys22-Cys88, and Cys24-Cys86, and one inter-β-sheet: Cys6-Cys119) into a diverse panel of V H , V L , and V H H domains enhanced their thermostability and protease resistance without significantly impacting expression, solubility, or binding to cognate antigens. None of the noncanonical disulfide linkages identified were present in the natural human V H repertoire. These data reveal an unexpected permissiveness of Ig V domains to noncanonical disulfide linkages at diverse locations in FRs, absent in the human repertoire, whose presence is compatible with antigen recognition and improves domain stability. Our work represents the most complete assessment to date of the role of engineered noncanonical disulfide bonding within FRs in Ig V domain structure and function.
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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".