Structural Comparison of MTA Phosphorylase and MTA/AdoHcy Nucleosidase Explains Substrate Preferences and Identifies Regions Exploitable for Inhibitor Design
Bibliographic record
Abstract
The development of new and effective antiprotozoal drugs has been a difficult challenge because of the close similarity of the metabolic pathways between microbial and mammalian systems. 5'-Methylthioadenosine/S-adenosylhomocysteine (MTA/AdoHcy) nucleosidase is thought to be an ideal target for therapeutic drug design as the enzyme is present in many microbes but not in mammals. MTA/AdoHcy nucleosidase (MTAN) irreversibly depurinates MTA or AdoHcy to form adenine and the corresponding thioribose. The inhibition of MTAN leads to a buildup of toxic byproducts that affect various microbial pathways such as quorum sensing, biological methylation, polyamine biosynthesis, and methionine recycling. The design of nucleosidase-specific inhibitors is complicated by its structural similarity to the human MTA phosphorylase (MTAP). The crystal structures of human MTAP complexed with formycin A and 5'-methylthiotubercidin have been solved to 2.0 and 2.1 A resolution, respectively. Comparisons of the MTAP and MTAN inhibitor complexes reveal size and electrostatic potential differences in the purine, ribose, and 5'-alkylthio binding sites, which account for the substrate specificity and reactions catalyzed. In addition, the differences between the two enzymes have allowed the identification of exploitable regions that can be targeted for the development of high-affinity nucleosidase-specific inhibitors. Sequence alignments of Escherichia coli MTAN, human MTAP, and plant MTA nucleosidases also reveal potential structural changes to the 5'-alkylthio binding site that account for the substrate preference of plant MTA nucleosidases.
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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 | 0.001 |
| 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".