Epitope mapping in cell surface proteins by site-directed masking: defining the structural elements of NTPDase3 inhibition by a monoclonal antibody
Bibliographic record
Abstract
We adapted the method of epitope mapping by site-directed masking, which was described for purified soluble antigens [Paus,D. and Winter,G. (2006) Proc. Natl Acad. Sci. USA, 103, 9172-9177.], to map the binding site of an inhibitory monoclonal antibody on the cell surface protein ecto-nucleotidase NTPDase3. Using homology modeling, we built a 3D structure of NTPDase3 and designed 21 single cysteine mutations distributed over the surface of the enzyme. The mutant proteins were expressed in cells, biotinylated with a cysteine-specific reagent, and then extracted with detergent and immobilized on streptavidin-coated plates. Tethering NTPDase3 via cysteine residues located in a surface patch near the active site cleft masked the epitope and blocked antibody binding, as evaluated by enzyme inhibition assay and by ELISA. We then constructed 18 single alanine substitution mutations within the defined patch and found that W403A, D414A, E415A and R419A decreased the inhibitory effect of the antibody, whereas the double mutation W403A/R419A abolished both antibody binding and enzyme inhibition, suggesting the critical role of these residues for interaction with the antibody. Lack of competition between the antibody and a non-hydrolyzable substrate analog AMPPCP, as well as location of the epitope adjacent to the active site, suggest a noncompetitive mechanism of inhibition by steric hindrance. The described technique should be useful for systematic epitope mapping in cell membrane proteins for which either a 3D structure is available, or a sufficiently accurate 3D model can be obtained by homology modeling.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".