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Exploring Cyclodextrin Glycosyltransferase's Thermostability through Molecular Dynamics Simulation

2013· article· en· W2095583121 on OpenAlexaff
Yi Fu, Qi Fang Gu

Bibliographic record

VenueAdvanced materials research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsLa Cité Collégiale
Fundersnot available
KeywordsThermostabilitySalt bridgeMolecular dynamicsThermal stabilityProtein engineeringChemistryCyclodextrinEnzymeBiochemistryOrganic chemistryComputational chemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.097
GPT teacher head0.358
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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