RNA aptamers to initiation factor 4A helicase hinder cap-dependent translation by blocking ATP hydrolysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The mammalian translation initiation factor 4A (eIF4A) is a prototype member of the DEAD-box RNA helicase family that couples ATPase activity to RNA binding and unwinding. In the crystal form, eIF4A has a distended "dumbbell" structure consisting of two domains, which probably undergo a conformational change, on binding ATP, to form a compact, functional structure via the juxtaposition of the two domains. Moreover, additional conformational changes between two domains may be involved in the ATPase and helicase activity of eIF4A. The molecular basis of these conformational changes, however, is not understood. Here, we generated RNA aptamers with high affinity for eIF4A by in vitro RNA selection-amplification. On binding, the RNAs inhibit ATP hydrolysis. One class of RNAs contains members that exhibit dissociation constant of 27 nM for eIF4A and severely inhibit cap-dependent in vitro translation. The binding affinity was increased on Arg substitution in the conserved motif Ia of eIF4A, which probably improves a predicted arginine network to bind RNA substrates. Selected RNAs, however, failed to bind either domain of eIF4A that had been split at the linker site. These findings suggest that the selected RNAs interact cooperatively with both domains of eIF4A, either in the dumbbell or the compact form, and entrap it into a dead-end conformation, probably by blocking the conformational change of eIF4A. The selected RNAs, therefore, represent a new class of specific inhibitors that are suitable for the analysis of eukaryotic initiation, and which pose a potential therapeutic against malignancies that are caused by aberrant translational control.
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.
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 it