Discovery and Characterization of Cell-Permeable Inhibitors of <i>Leishmania mexicana</i> CLK1 Using an In-Cell Target Engagement Assay
Bibliographic record
Abstract
Leishmaniasis is a neglected tropical disease with limited treatment options and significant unmet medical need. Here, we report the development of a bioluminescence resonance energy transfer (BRET)-based target engagement assay in live cells to identify and validate cell-permeable, ATP-competitive inhibitors of Leishmania mexicana (Lmx)CLK1. LmxCLK2, a closely related paralog with an identical protein kinase domain, is also considered in our analysis. Genetic and pharmacological evidence indicates that simultaneous deletion or inhibition of both LmxCLK1/2 is lethal to the parasite. Using our newly developed assay, we screened a library of human kinase inhibitors and identified WZ8040, a third-generation EGFR inhibitor, as a potent LmxCLK1 ligand. WZ8040 demonstrated robust target engagement in both promastigotes and macrophage-internalized amastigotes, with an EC 50 value of 2.1 μM for amastigote killing and minimal toxicity to host macrophages. Biochemical assays confirmed that WZ8040 covalently binds and inhibits LmxCLK1, with mass spectrometry identifying Cys172 as the primary site of modification. Genetic validation using overexpression and knockout lines supports LmxCLK1 as the primary target of WZ8040. However, the retained activity of WZ8040 in mutant lines with the Cys172Ala substitution suggests that covalent binding is not essential for compound efficacy. Our findings highlight the utility of BRET-based assays for target validation in kinetoplastid parasites and underscore the potential of CLK1/2 as druggable kinases in Leishmania . This integrated approach provides a framework for accelerating the discovery of novel antileishmanial agents through target engagement-guided strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
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".