Miransertib (ARQ 092), an orally-available, selective Akt inhibitor is effective against Leishmania
Bibliographic record
Abstract
Leishmaniasis is amongst the most important neglected diseases, afflicting more than 12 million people in 88 countries. There is an urgent need for safe orally bioavailable and cost-effective drugs for the treatment of leishmaniasis. It has recently been shown that Leishmania activates host macrophage serine/threonine kinase Akt, to promote survival of both parasites and infected cells. Here, we sought to evaluate a compound, Miransertib (ARQ 092), an orally bioavailable and selective allosteric Akt inhibitor currently in clinical trials for patients with PI3K/Akt-driven tumors or Proteus syndrome. Miransertib was tested against Leishmania donovani and Leishmania amazonensis, causative agents of visceral and cutaneous leishmaniasis, respectively. Cultured promastigotes were susceptible to Miransertib. In addition, Miransertib was markedly effective against intracellular amastigotes of L. donovani or L. amazonensis-infected macrophages. Miransertib also enhanced mTOR dependent autophagy in Leishmania-infected macrophages, which may represent one mechanism of Miransertib-mediated killing of intracellular Leishmania. Whereas parasite clearance in the spleen of mice infected with L. donovani and treated with Miransertib was comparable to that when treated with miltefosine, Miransertib caused a greater reduction in the parasite load in the liver. In the cutaneous leishmaniasis infection model, lesions were reduced by 40% as compared to mock treated mice. Together, these results provide direct evidence to support the conclusion that Miransertib is an excellent lead compound for the development of a new oral drug therapy for visceral and cutaneous leishmaniasis.
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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) | 0.003 | 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".