Structural and functional analysis of lignostilbene dioxygenases from Sphingobium sp. SYK-6
Bibliographic record
Abstract
Lignostilbene-α,β-dioxygenases (LSDs) are iron-dependent oxygenases involved in the catabolism of lignin-derived stilbenes. Sphingobium sp. SYK-6 contains eight LSD homologs with undetermined physiological roles. To investigate which homologs are involved in the catabolism of dehydrodiconiferyl alcohol (DCA), derived from β-5 linked lignin subunits, we heterologously produced the enzymes and screened their activities in lysates. The seven soluble enzymes all cleaved lignostilbene, but only LSD2, LSD3, and LSD4 exhibited high specific activity for 3-(4-hydroxy-3-(4-hydroxy-3-methoxystyryl)-5-methoxyphenyl) acrylate (DCA-S) relative to lignostilbene. LSD4 catalyzed the cleavage of DCA-S to 5-formylferulate and vanillin and cleaved lignostilbene and DCA-S (∼10 6 M −1 s −1 ) with tenfold greater specificity than pterostilbene and resveratrol. X-ray crystal structures of native LSD4 and the catalytically inactive cobalt-substituted Co-LSD4 at 1.45 Å resolution revealed the same fold, metal ion coordination, and edge-to-edge dimeric structure as observed in related enzymes. Key catalytic residues, Phe-59, Tyr-101, and Lys-134, were also conserved. Structures of Co-LSD4·vanillin, Co-LSD4·lignostilbene, and Co-LSD4·DCA-S complexes revealed that Ser-283 forms a hydrogen bond with the hydroxyl group of the ferulyl portion of DCA-S. This residue is conserved in LSD2 and LSD4 but is alanine in LSD3. Substitution of Ser-283 with Ala minimally affected the specificity of LSD4 for either lignostilbene or DCA-S. By contrast, substitution with phenylalanine, as occurs in LSD5 and LSD6, reduced the specificity of the enzyme for both substrates by an order of magnitude. This study expands our understanding of an LSD critical to DCA catabolism as well as the physiological roles of other LSDs and their determinants of substrate specificity.
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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) | 0.001 | 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".