The optimal pH of AID is skewed from that of its catalytic pocket by DNA-binding residues and surface charge
Bibliographic record
Abstract
Activation-induced cytidine deaminase (AID) is a member of the apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like (APOBEC) family of cytidine deaminases. AID mutates immunoglobulin loci to initiate secondary antibody diversification. The APOBEC3 (A3) sub-branch mutates viral pathogens in the cytosol and acidic endosomal compartments. Accordingly, AID functions optimally near-neutral pH, while most A3s are acid-adapted (optimal pH 5.5-6.5). To gain a structural understanding for this pH disparity, we constructed high-resolution maps of AID catalytic activity vs pH. We found AID's optimal pH was 7.3 but it retained most (>70%) of the activity at pH 8. Probing of ssDNA-binding residues near the catalytic pocket, key for bending ssDNA into the pocket (e.g. R25) yielded mutants with altered pH preference, corroborating previous findings that the equivalent residue in APOBEC3G (H216) underlies its acidic pH preference. AID from bony fish exhibited more basic optimal pH (pH 7.5-8.1) and several R25-equivalent mutants altered pH preference. Comparison of pH optima across the AID/APOBEC3 family revealed an inverse correlation between positive surface charge and overall catalysis. The paralogue with the most robust catalytic activity (APOBEC3A) has the lowest surface charge and most acidic pH preference, while the paralogue with the most lethargic catalytic rate (AID) has the most positive surface charge and highest optimal pH. We suggest one possible mechanism is through surface charge dictating an overall optimal pH that is different from the optimal pH of the catalytic pocket microenvironment. These findings illuminate an additional structural mechanism that regulates AID/APOBEC3 mutagenesis.
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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) | 0.001 | 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".