Structural analysis of the lncRNA SChLAP1 reveals protein binding interfaces and a conformationally heterogenous retroviral insertion
Bibliographic record
Abstract
The lncRNA second chromosome locus associated with prostate 1 (SChLAP1) was previously identified as a predictive biomarker and potential driver of aggressive prostate cancer. Recent work suggested that SChLAP1 may bind the SWI/SNF chromatin remodeling complex to promote prostate cancer metastasis, though the exact role of SWI/SNF recognition is debated. To date, there are no detailed biochemical studies of apo SChLAP1 or SChLAP1:protein complexes. Herein, we report the first secondary structure model of SChLAP1 using SHAPE-MaP in vitro, in cellulo, and ex cellulo (protein-free). Comparison of the ex cellulo and in cellulo data via ΔSHAPE identified putative protein binding regions within SChLAP1. In addition, phylogenetic analysis revealed that SChLAP1 is a primate-conserved lncRNA, with two exons significantly derived from primate-specific retroviral insertions. In particular, we characterized a complex structural landscape in a protein binding region at the 3′-end of SChLAP1 derived from a THE1B-type retroviral insertion, suggesting a role for an exapted RNA structure in SChLAP1:protein recognition and prostate cancer progression. Lastly, pulldowns of SChLAP1 substructures enabled identification of previously unestablished SChLAP1-interacting proteins. This work lays the foundation for future efforts to selectively target and disrupt SChLAP1 structures and/or protein interfaces and to develop new therapeutic avenues in prostate cancer treatment.
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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".