Characterization of the sorbitol dehydrogenase SmoS from <i>Sinorhizobium meliloti</i> 1021
Bibliographic record
Abstract
Sinorhizobium meliloti 1021 is a Gram-negative alphaproteobacterium with a robust capacity for carbohydrate metabolism. The enzymes that facilitate these reactions assist in the survival of the bacterium across a range of environmental niches, and they may also be suitable for use in industrial processes. SmoS is a dehydrogenase that catalyzes the oxidation of the commonly occurring sugar alcohols sorbitol and galactitol to fructose and tagatose, respectively, using NAD + as a cofactor. The main objective of this study was to evaluate SmoS using biochemical techniques. The nucleotide sequence was codon-optimized for heterologous expression in Escherichia coli BL21 (DE3) Gold cells and the protein was subsequently overexpressed and purified. Size-exclusion chromatography and X-ray diffraction experiments suggest that SmoS is a tetramer. SmoS was crystallized, and crystals obtained in the absence of substrate diffracted to 2.1 Å resolution and those of a complex with sorbitol diffracted to 2.0 Å resolution. SmoS was characterized kinetically and shown to have a preference for sorbitol despite having a higher affinity for galactitol. Computational ligand-docking experiments suggest that tagatose binds the protein in a more energetically favourable complex than fructose, which is retained in the active site over a longer time frame following oxidation and reduces the rate of the reaction. These results supplement the inventory of biomolecules with potential for industrial applications and enhance the understanding of metabolism in the model organism S. meliloti .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".