Nucleoside Transport as a Potential Target for Chemotherapy in Malaria
Bibliographic record
Abstract
Malaria constitutes an enormous drain on the health and economies of many countries and causes more than a million deaths annually. Moreover, resistance to existing antimalarial drugs is a growing problem, rendering the search for new targets urgent. Protozoan parasites of the genus Plasmodium that cause malaria lack the ability to synthesise the purine ring de novo and so are reliant upon salvage of purines, including hypoxanthine, inosine and adenosine, from the host. The transport systems responsible for uptake of these precursors are therefore promising targets for novel antimalarial drugs. In humans, purine uptake into many cell types is mediated by members of the Equilibrative Nucleoside Transporter (ENT) family, in particular hENT1 and hENT2. Genome sequencing has revealed that P. falciparum and P. vivax, the species responsible for the majority of malaria cases, each also possesses four members of this family, and in P. falciparum transcripts of each are expressed in the erythrocytic stages of the parasite responsible for clinical disease. One of the proteins, PfENT1, is known to be present in the parasite plasma membrane, and the kinetic properties of the heterologously expressed transporter are consistent with its representing the major purine uptake system in the trophozoite. Importantly, its inhibitor specificity and permeant selectivity differ from those of the host. In this review we discuss the possibility of exploiting these differences to develop novel antimalarial drugs that either selectively inhibit purine uptake into the pararasite or are selectively delivered by the transporter to the parasite cytoplasm.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".