Riboswitches that sense <i>S</i>-adenosylmethionine and <i>S</i>-adenosylhomocysteineThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Systems and Chemical Biology, and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
Numerous riboswitches have been discovered that specifically recognize metabolites and modulate gene expression. Each riboswitch class is defined either by the consensus sequence and structural features of its metabolite-binding aptamer domain, or by the distinct metabolite that the aptamer recognizes. Several distinct classes of riboswitches that respond to S-adenosylmethionine (SAM or AdoMet) have been discovered. Representatives of these classes have been shown to strongly discriminate against S-adenosylhomocystenine (SAH or AdoHcy), which is the metabolic byproduct produced when SAM is used as a cofactor for methylation reactions. However, a distinct class of riboswitches that selectively binds SAH, and strongly discriminates against SAM, also has been discovered. Herein we compare the features of SAM and SAH riboswitches, which help showcase the enormous structural diversity that RNA can harness to form precision genetic switches for compounds that are critical for fundamental metabolic processes.
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".