Enzymatic properties of rat DNA polymerase beta mutants obtained by randomized mutagenesis
Bibliographic record
Abstract
We have used random sequence mutagenesis to generate mutants of DNA polymerase beta in an effort to identify amino acid residues important for function, catalytic efficiency and fidelity of replication. A library containing 100 000 mutants at residues 274-278 in the N-helix of the thumb subdomain of the polymerase was constructed and screened for polymerase activity by genetic complementation. The genetic screen identified 4000 active pol beta mutants, 146 of which were sequenced. Each of the five positions mutagenized tolerated substitutions, but residues G274 and F278 were only found substituted in combination with mutations at other positions. The least conserved residue, D276, was replaced by a variety of amino acids and, therefore, does not appear to be essential for function. Steady-state kinetic analysis, however, demonstrated that D276 may be important for catalytic efficiency. Mutant D276E exhibited a 25-fold increase in catalytic efficiency over the wild-type enzyme but also a 25-fold increase in G:T misincorporation efficiency. We present a structural model that can account for the observations and we discuss the implications of this study for the question of enzyme optimization by natural selection.
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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 | 0.001 |
| 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 | 0.001 |
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".