Kinetics and thermodynamics of thermal inactivation for recombinant <i>Escherichia coli</i> cellulases, cel12B, cel8C, and polygalacturonase, peh28; biocatalysts for biofuel precursor production
Bibliographic record
Abstract
Lignocellulosic biomass conversion using cellulases/polygalacturonases is a process that can be progressively influenced by several determinants involved in cellulose microfibril degradation. This article focuses on the kinetics and thermodynamics of thermal inactivation of recombinant Escherichia coli cellulases, cel12B, cel8C and a polygalacturonase, peh 28, derived from Pectobacterium carotovorum sub sp. carotovorum. Several consensus motifs conferring the enzymes' thermal stability in both cel12B and peh28 model structures have been detailed earlier, which were confirmed for the three enzymes through the current study of their thermal inactivation profiles over the 20-80°C range using the respective activities on carboxymethylcellulose and polygalacturonic acid. Kinetic constants and half-lives of thermal inactivation, inactivation energy, plus inactivation entropies, enthalpies and Gibbs free energies, revealed high stability, less conformational change and protein unfolding for cel12B and peh28 due to thermal denaturation compared to cel8C. The apparent thermal stability of peh28 and cel12B, along with their hydrolytic efficiency on a lignocellulosic biomass conversion as reported previously, makes these enzymes candidates for various industrial applications. Analysis of the Gibbs free energy values suggests that the thermal stabilities of cel12B and peh28 are entropy-controlled over the tested temperature range.
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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 | 0.000 |
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".