Molecular Identification of d-Ribulokinase in Budding Yeast and Mammals
Bibliographic record
Abstract
Proteomes of even well characterized organisms still contain a high percentage of proteins with unknown or uncertain molecular and/or biological function. A significant fraction of those proteins is predicted to have catalytic properties. Here we aimed at identifying the function of the Saccharomyces cerevisiae Ydr109c protein and its human homolog FGGY, both of which belong to the broadly conserved FGGY family of carbohydrate kinases. Functionally identified members of this family phosphorylate 3- to 7-carbon sugars or sugar derivatives, but the endogenous substrate of S. cerevisiae Ydr109c and human FGGY has remained unknown. Untargeted metabolomics analysis of an S. cerevisiae deletion mutant of YDR109C revealed ribulose as one of the metabolites with the most significantly changed intracellular concentration as compared with a wild-type strain. In human HEK293 cells, ribulose could only be detected when ribitol was added to the cultivation medium, and under this condition, FGGY silencing led to ribulose accumulation. Biochemical characterization of the recombinant purified Ydr109c and FGGY proteins showed a clear substrate preference of both kinases for d-ribulose over a range of other sugars and sugar derivatives tested, including l-ribulose. Detailed sequence and structural analyses of Ydr109c and FGGY as well as homologs thereof furthermore allowed the definition of a 5-residue d-ribulokinase signature motif (TCSLV). The physiological role of the herein identified eukaryotic d-ribulokinase remains unclear, but we speculate that S. cerevisiae Ydr109c and human FGGY could act as metabolite repair enzymes, serving to re-phosphorylate free d-ribulose generated by promiscuous phosphatases from d-ribulose 5-phosphate. In human cells, FGGY can additionally participate in ribitol metabolism.
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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 | 0.001 |
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".