The Lid Domain of the MCP Hydrolase DxnB2 Contributes to the Reactivity toward Recalcitrant PCB Metabolites
Bibliographic record
Abstract
DxnB2 and BphD are meta-cleavage product (MCP) hydrolases that catalyze C-C bond hydrolysis of the biphenyl metabolite 2-hydroxy-6-oxo-6-phenylhexa-2,4-dienoic acid (HOPDA). BphD is a bottleneck in the bacterial degradation of polychlorinated biphenyls (PCBs) by the Bph catabolic pathway due in part to inhibition by 3-Cl HOPDAs. By contrast, DxnB2 from Sphingomonas wittichii RW1 catalyzes the hydrolysis of 3-Cl HOPDAs more efficiently. X-ray crystallographic studies of the catalytically inactive S105A variant of DxnB2 complexed with 3-Cl HOPDA revealed a binding mode in which C1 through C6 of the dienoate are coplanar. The chlorine substituent is accommodated by a hydrophobic pocket that is larger than the homologous site in BphDLB400 from Burkholderia xenovorans LB400. The planar binding mode observed in the crystalline complex was consistent with the hyper- and hypsochromically shifted absorption spectra of 3-Cl and 3,9,11-triCl HOPDA, respectively, bound to S105A in solution. Moreover, ES(red), an intermediate possessing a bathochromically shifted spectrum observed in the turnover of HOPDA, was not detected, suggesting that substrate destabilization was rate-limiting in the turnover of these PCB metabolites. Interestingly, electron density for the first α-helix of the lid domain was poorly defined in the dimeric DxnB2 structures, unlike in the tetrameric BphDLB400. Structural comparison of MCP hydrolases identified the NC-loop, connecting the lid to the α/β-hydrolase core domain, as a determinant in the oligomeric state and suggests its involvement in catalysis. Finally, an increased mobility of the DxnB2 lid may contribute to the enzyme's ability to hydrolyze PCB metabolites, highlighting how lid architecture contributes to substrate specificity in α/β-hydrolases.
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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) | 0.002 | 0.001 |
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".