Two disulfide mutants in domain I of <i>Bacillus thuringiensis</i> Cry3Aa δ-endotoxin increase stability with no effect on toxicity
Bibliographic record
Abstract
To increase protein stability and test protein function, three double-cysteine mutations were individually introduced by protein engineering into the cysteine-free Cry3Aa δ-endotoxin from Bacillus thuringiensis. These mutations were designed to create disulfide bonds between α-helices 2 and 5 (positions 110 - 193), and α-helices 5 and 7 (positions 195 - 276 and 198 - 276). Comparison of the CD spectra of the wild-type and the double-cysteine mutant proteins indicates a tighter helical packing consistent with formation of at least two of the disulfide bonds between the central and the outer helices. Thermal stability analysis indi-cates that potential covalent linkages between the central α-helix 5 and the other helices increase resistance to thermal denaturation by 10?C to 14?C com-pared to the thermal stability of the wild-type protein. Spectroscopic analysis of the disulfide-specific absorbance band indicates that the double mutant proteins are more stable to temperature and denaturant (guanidine hydrochloride) than the wild-type protein, as a result of the formation of two of the disulfide bridges. These results indicate that the double muta-tions M110C/F193C and A198C/V276C successfully established disulfide bonds, resulting in a more stable structure of the entire toxin. Despite the increase in stability and structural changes introduced by the disulfide bonds, no effect on toxicity was observed. A possible mechanism involving the insertion of all of domain I of Cry3Aa toxin into the target membrane accounts for these observations.
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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) | 0.001 | 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 | 0.001 |
| 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".