Reliable repurposing of antibody interactome inside the cell
Bibliographic record
Abstract
Abstract In biology proximity is paramount and eighty-five percent of the human proteome has at least one documented interacting monoclonal antibody. These molecules penetrate the cytoplasm poorly and are very often non-functional within the cell. Sequence analysis of 10 6 antibody variable domains alongside the cytoplasmic human proteome shows charge and isoelectric point are characteristics ill adapted to intracellular monodispersity. Characterisation of forty-five single-chain variable fragment (scFv) intrabodies expressed in human cells confirmed charge to have the greatest impact on solubility. We created new interdomain linkers, optimised scFv domain orientation and found variable heavy domain framework sites to be generally positively charged, and promote insolubility, but be amenable to optimisation. This is applied in combination to reduce the search space and refine the products of AI-led inverse folding to create highly soluble, abundant and thermally stable intrabodies that maintain parent antibody epitope recognition. Over six hundred intrabody sequences are described targeting sixty cytoplasmic proteins with linear, conformational, post-translational modification or oligomeric state specificity. Interactions were validated for p53, α-synuclein, SOD1, polyQ, FUS/TLS, UCHL1 and GFP. This approach removes obstacles hindering intracellular repurposing of the vast sequenced antibody interactome with applications relevant to many human disease states.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".