Interdomain twists of human thymidine phosphorylase and its active–inactive conformations: Binding of 5‐FU and its analogues to human thymidine phosphorylase versus dihydropyrimidine dehydrogenase
Bibliographic record
Abstract
5-fluorouracil (5-FU) is an anticancer drug, which inhibits human thymidine phosphorylase (hTP) and plays a key role in maintaining the process of DNA replication and repair. It is involved in regulating pyrimidine nucleotide production, by which it inhibits the mechanism of cell proliferation and cancerous tumor growth. However, up to 80% of the administered drug is metabolized by dihydropyrimidine dehydrogenase (DPD). This work compares binding of 5-FU and its analogues to hTP and DPD, and suggests strategies to reduce drug binding to DPD to decrease the required dose of 5-FU. An important feature between the proteins studied here was the difference of charge distribution in their binding sites, which can be exploited for designing drugs to selectively bind to the hTP. The 5-FU presence was thought to be required for a closed conformation. Comparison of the calculation results pertaining to unliganded and liganded protein showed that hTP could still undergo open-closed conformations in the absence of the ligand; however, the presence of a positively charged ligand better stabilizes the closed conformation and rigidifies the core region of the protein more than unliganded or neutral liganded system. The study has also shown that one of the three hinge segments linking the two major α and α/β domains of the hTP is an important contributing factor to the enzyme's open-close conformational twist during its inactivation-activation process. In addition, the angle between the α/β-domain and the α-domain has shown to undergo wide rotations over the course of MD simulation in the absence of a phosphate, suggesting that it contributes to the stabilization of the closed conformation of the hTP.
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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 | 0.000 |
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".