Epitope mapping of a blood–brain barrier crossing antibody targeting the cysteine-rich region of IGF1R using hydrogen-exchange mass spectrometry enabled by electrochemical reduction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pathologies of the central nervous system impact a significant portion of our population, and the delivery of therapeutics for effective treatment is challenging. The insulin-like growth factor-1 receptor (IGF1R) has emerged as a target for receptor-mediated transcytosis, a process by which antibodies are shuttled across the blood-brain barrier (BBB). Here, we describe the biophysical characterization of VHH-IR4, a BBB-crossing single-domain antibody (sdAb). Binding was confirmed by isothermal titration calorimetry and an epitope was highlighted by surface plasmon resonance that does not overlap with the IGF-1 binding site or other known BBB-crossing sdAbs. The epitope was mapped with a combination of linear peptide scanning and hydrogen-deuterium exchange mass spectrometry (HDX-MS). IGF1R is large and heavily disulphide bonded, and comprehensive HDX analysis was achieved only through the use of online electrochemical reduction coupled with a multiprotease approach, which identified an epitope for VHH-IR4 within the cysteine-rich region (CRR) of IGF1R spanning residues W244-G265. This is the first report of an sdAb binding the CRR. We show that VHH-IR4 inhibits ligand induced auto-phosphorylation of IGF1R and that this effect is mediated by downstream conformational effects. Our results will guide the selection of antibodies with improved trafficking and optimized IGF1R binding characteristics.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it