Mapping the Active Site−Ligand Interactions of Orotidine 5‘-Monophosphate Decarboxylase by Crystallography<sup>,</sup>
Bibliographic record
Abstract
The crystal structures of orotidine 5'-monophosphate decarboxylases from four different sources have been published recently. However, the detailed mechanism of catalysis of the most proficient enzyme known to date remains elusive. As the ligand-protein interactions at the orotate binding site are crucial to the understanding of this enzyme, we mutated several of the residues surrounding the aromatic part of the substrate, individually and in combination. The ensuing effects on enzyme structure and stability were characterized by X-ray crystallography of inhibitor, product, or substrate complexes and by chemical denaturation with guanidine hydrochloride, respectively. The results are consistent with the residues K42D70K72D75B being charged and forming an 'alternate charge network' around the reactive part of the substrate. In addition to exerting charge-charge repulsion on the orotate carboxylate, Asp70 also makes a crucial contribution to enzyme stability. Consequently, orotidine 5'-monophosphate decarboxylases seem to require the presence of a negative charge at this position for catalysis as well as for correct and stable folding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".