Assessing Specific Oligonucleotides and Small Molecule Antibiotics for the Ability to Inhibit the CRD-BP-CD44 RNA Interaction
Bibliographic record
Abstract
Studies on Coding Region Determinant-Binding Protein (CRD-BP) and its orthologs have confirmed their functional role in mRNA stability and localization. CRD-BP is present in extremely low levels in normal adult tissues, but it is over-expressed in many types of aggressive human cancers and in neonatal tissues. Although the exact role of CRD-BP in tumour progression is unclear, cumulative evidence suggests that its ability to physically associate with target mRNAs is an important criterion for its oncogenic role. CRD-BP has high affinity for the 3'UTR of the oncogenic CD44 mRNA and depletion of CRD-BP in cells led to destabilization of CD44 mRNA, decreased CD44 expression, reduced adhesion and disruption of invadopodia formation. Here, we further characterize the CRD-BP-CD44 RNA interaction and assess specific antisense oligonucleotides and small molecule antibiotics for their ability to inhibit the CRD-BP-CD44 RNA interaction. CRD-BP has a high affinity for binding to CD44 RNA nts 2862-3055 with a Kd of 645 nM. Out of ten antisense oligonucleotides spanning nts 2862-3055, only three antisense oligonucleotides (DD4, DD7 and DD10) were effective in competing with CRD-BP for binding to 32P-labeled CD44 RNA. The potency of DD4, DD7 and DD10 in inhibiting the CRD-BP-CD44 RNA interaction in vitro correlated with their ability to specifically reduce the steady-state level of CD44 mRNA in cells. The aminoglycoside antibiotics neomycin, paramomycin, kanamycin and streptomycin effectively inhibited the CRD-BP-CD44 RNA interaction in vitro. Assessing the potential inhibitory effect of aminoglycoside antibiotics including neomycin on the CRD-BP-CD44 mRNA interaction in cells proved difficult, likely due to their propensity to non-specifically bind nucleic acids. Our results have important implications for future studies in finding small molecules and nucleic acid-based inhibitors that interfere with protein-RNA interactions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".