Exploring Cyclodextrin Glycosyltransferase's Thermostability through Molecular Dynamics Simulation
Bibliographic record
Abstract
Cyclodextrin glycosyltransferase (EC 2.4.1.19, CGTase) is an important industrial enzyme in the production of cyclodextrins. However, the working conditions are extreme, which often restrict the usage of CGTase. Thermal stability is of great importance for this enzyme. Besides to screen microorganism for CGTase that fit the requirement of biotechnology, it is also hoped that protein engineering can tailor CGTase to meet demands of industry. In this work, molecular dynamics simulations were performed to study thermal stabilization of CGTase C-terminal structured region. Dynamic motions of salt bridges in thermal unstable regions were monitored during the simulations. In the C-terminal region, salt bridge Arg591-Asp640 and Lys652-Glu664 were proposed to be more important for stability than the others. Sheet1 and Sheet3 through the Arg591-Asp640 salt-bridge formation renders the C-terminal stable. The salt bridge Lys652-Glu664 linking sheet4 and sheet5 terminal also contributes to the structural stability of C-terminal. This study is attempt to observe the dynamic behavior of CGTase C-terminal at high temperatures and to understand the factors conferring thermostability of this protein. The results provide specific knowledge about thermal stability in CGTase C-terminal and may help to design biotechnologically improved thermostable proteins.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".