Structural basis of 3′-end poly(A) RNA recognition by LARP1
Bibliographic record
Abstract
La-related proteins (LARPs) comprise a family of RNA-binding proteins involved in a wide range of posttranscriptional regulatory activities. LARPs share a unique tandem of two RNA-binding domains, La motif (LaM) and RNA recognition motif (RRM), together referred to as a La-module, but vary in member-specific regions. Prior structural studies of La-modules reveal they are pliable platforms for RNA recognition in diverse contexts. Here, we characterize the La-module of LARP1, which plays an important role in regulating synthesis of ribosomal proteins in response to mTOR signaling and mRNA stabilization. LARP1 has been well characterized functionally but no structural information exists for its La-module. We show that unlike other LARPs, the La-module in LARP1 does not contain an RRM domain. The LaM alone is sufficient for binding poly(A) RNA with submicromolar affinity and specificity. Multiple high-resolution crystal structures of the LARP1 LaM domain in complex with poly(A) show that it is highly specific for the RNA 3'-end, and identify LaM residues Q333, Y336 and F348 as the most critical for binding. Use of a quantitative mRNA stabilization assay and poly(A) tail-sequencing demonstrate functional relevance of LARP1 RNA binding in cells and provide novel insight into its poly(A) 3' protection activity.
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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 | 0.000 |
| 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".