Inhibition of Plasmodium falciparum plasmepsins by drugs targeting HIV-1 protease: A way forward for antimalarial drug discovery
Bibliographic record
Abstract
Plasmodium species are causative agents of malaria, a disease that is a serious global health concern. FDA-approved HIV-1 protease inhibitors (HIV-1 PIs) have been reported to be effective in reducing the infection by Plasmodium parasites in the population co-infected with both HIV-1 and malaria. However, the mechanism of HIV-1 PIs in mitigating Plasmodium pathogenesis during malaria/HIV-1 co-infection is not fully understood. In this study we demonstrate that HIV-1 drugs ritonavir (RTV) and lopinavir (LPV) exhibit the highest inhibition activity against plasmepsin II (PMII) and plasmepsin X (PMX) of P. falciparum. Crystal structures of the complexes of PMII with both drugs have been determined. The inhibitors interact with PMII via multiple hydrogen bonding and hydrophobic interactions. The P4 moiety of RTV forms additional interactions compared to LPV and exhibits conformational flexibility in a large S4 pocket of PMII. Our study is also the first to report inhibition of P. falciparum PMX by RTV and the mode of binding of the drug to the PMX active site. Analysis of the crystal structures implies that PMs can accommodate bulkier groups of these inhibitors in their S4 binding pockets. Structurally similar active sites of different vacuolar and non-vacuolar PMs suggest the potential of HIV-1 PIs in targeting these enzymes with differential affinities. Our structural investigations and biochemical data emphasize PMs as crucial targets for repurposing HIV-1 PIs as antimalarial drugs.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".