Magnesium, Essential for Base Excision Repair Enzymes, Inhibits Substrate Binding of N-Methylpurine-DNA Glycosylase
Bibliographic record
Abstract
N-Methylpurine-DNA glycosylase (MPG) initiates base excision repair in DNA by removing a wide variety of alkylated, deaminated, and lipid peroxidation-induced purine adducts. MPG activity and other DNA glycosylases do not have an absolute requirement for a cofactor. In contrast, all downstream activities of major base excision repair proteins, such as apurinic/apyrimidinic endonuclease, DNA polymerase beta, and ligases, require Mg(2+). Here we have demonstrated that Mg(2+) can be significantly inhibitory toward MPG activity depending on its concentration but independent of substrate type. The pre-steady-state kinetics suggests that Mg(2+) at high but physiologic concentrations decreases the amount of active enzyme concentrations. Steady-state inhibition kinetics showed that Mg(2+) affected K(m), but not V(max), and the inhibition could be reversed by EDTA but not by DNA. At low concentration, Mg(2+) stimulated the enzyme activity only with hypoxanthine but not ethenoadenine. Real-time binding experiments using surface plasmon resonance spectroscopy showed that the pronounced inhibition of activity was due to inhibition in substrate binding. Nonetheless, the glycosidic bond cleavage step was not affected. These results altogether suggest that Mg(2+) inhibits MPG activity by abrogating substrate binding. Because Mg(2+) is an absolute requirement for the downstream activities of the major base excision repair enzymes, it may act as a regulator for the base excision repair pathway for efficient and balanced repair of damaged bases, which are often less toxic and/or mutagenic than their subsequent repair product intermediates.
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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) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".