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Record W2078515355 · doi:10.1021/jp901921r

Structure and Dynamics of Cold-Adapted Enzymes as Investigated by FT-IR Spectroscopy and MD. The Case of an Esterase from <i>Pseudoalteromonas haloplanktis</i>

2009· article· en· W2078515355 on OpenAlexaff
Vincenzo Aurilia, Jean-François Rioux-Dubé, Anna Marabotti, Michel Pézolet, Sabato D’Auria

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEsteraseSpectroscopyPseudoalteromonasEnzymeDynamics (music)ChemistryBiochemistryPsychologyPhysicsGene

Abstract

fetched live from OpenAlex

Psychrophiles are cold-adapted organisms that produce enzymes that display a high catalytic efficiency at low temperatures. In recent years, these low-temperature working enzymes have attracted the attention of scientists because of their peculiar properties that render them particularly useful in investigating the relationship between enzyme stability and flexibility. Recently, a new esterase was identified and isolated from the cold-adapted organism Pseudoalteromonas haloplanktis. The enzyme, denoted as PhEST, presents a dimeric structure with a molecular mass of 60 kDa. In this work, we used Fourier transform infrared spectroscopy and molecular dynamics simulations to investigate the functional and structural properties of PhEST over a wide range of temperature. The obtained results reveal that the structure of PhEST is quite stable up to 40 degrees C. In fact, the protein starts to denature at about 45 degrees C through the formation of new secondary structural elements such as intermolecular beta-sheets. In addition, our results indicate that the flexibility of protein segment 55-65 (335-345 in subunit B), which corresponds to a loop near the active site of the enzyme, plays a crucial role in the protein function.

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 score0.008
Threshold uncertainty score0.432

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 head0.003
GPT teacher head0.221
Teacher spread0.219 · 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

Citations18
Published2009
Admission routes1
Has abstractyes

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