Characterization of Sorbitol Dehydrogenase SmoS from <i>Sinorhizobium meliloti</i> 1021
Bibliographic record
Abstract
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 into fructose and tagatose respectively using NAD + as a cofactor. The main objective of this study is to evaluate SmoS using biochemical techniques. The nucleotide sequence was codon optimized for heterologous expression in E. coli BL21 (DE3) GOLD cells, the protein was subsequently overexpressed and purified. Size exclusion chromatography and X-ray diffraction experiments suggest that SmoS is a tetrameric peptide. SmoS was crystallized to 2.1 Å in the absence of substrate and 2.0 Å in complex with sorbitol. SmoS was characterized kinetically and shown to have a preference for sorbitol despite a higher affinity for galactitol. Computational ligand docking experiments suggest that galactitol oxidation proceeds slowly because tagatose binds the protein in a more energetically favorable complex than fructose, and is retained in the active site for a longer time frame following oxidation which reduces the rate of the reaction. These results supplement the inventory of biomolecules with the potential for industrial applications and enhance our understanding of metabolism in the model organism S. meliloti .
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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 | 0.000 |
| 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) | 0.000 | 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 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".