Disrupting the LC3 Interaction Region (LIR) Binding of Selective Autophagy Receptors Sensitizes AML Cell Lines to Cytarabine
Bibliographic record
Abstract
Short linear motifs (SLiMs) located in disordered regions of multidomain proteins are important for the organization of protein-protein interaction networks. By dynamic association with their binding partners, SLiMs enable assembly of multiprotein complexes, pivotal for the regulation of various aspects of cell biology in higher organisms. Despite their importance, there is a paucity of molecular tools to study SLiMs of endogenous proteins in live cells. LC3 interacting regions (LIRs), being quintessential for orchestrating diverse stages of autophagy, are a prominent example of SLiMs and mediate binding to the ubiquitin-like LC3 / GABARAP family of proteins. The role of LIRs ranges from the posttranslational processing of their binding partners at early stages of autophagy to the binding of selective autophagy receptors (SARs) to the autophagosome. In order to generate tools to study LIRs in cells, we engineered high affinity binders of LIR motifs of three archetypical SARs: OPTN, p62 and NDP52. In an array of in vitro and cellular assays, the engineered binders were shown to have greatly improved affinity and specificity when compared with the endogenous LC3 / GABARAP family of proteins, thus providing a unique possibility for modulating LIR interactions in living systems. We exploited these novel tools to study the impact of LIR inhibition on the fitness and the responsiveness to cytarabine treatment of THP-1 cells – a model for studying acute myeloid leukemia (AML). Our results demonstrate that inhibition of LIR of a single autophagy receptor is insufficient to sensitize the cells to cytarabine, while simultaneous inhibition of three LIR motifs in three distinct SARs reduces the IC50 of the chemotherapeutic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".