Ribosomal Proteins: Their Role in the Assembly, Structure and Function of the Ribosome
Bibliographic record
Abstract
Abstract The ribosome is the macromolecular assembly dedicated to translating the genetic information into proteins. Ribosomes are made of several RNA molecules and between 50 and 80 proteins. The role played by these proteins has been the focus of investigations for over five decades. Initially, proteins were thought to be the only functional component of the ribosome, whereas the rRNA was considered merely a scaffold. This view has evolved and now is clear that both the RNA and protein components of the ribosome are functionally important. The r‐proteins play a role in the assembly process of the ribosome and are also essential for the structure and function of the ribosome. Their importance in the physiology of the ribosome is revealed by the fact that mutations in ribosomal proteins lead to ribosomopathies, a group of diseases that include developmental, haematological, metabolic and cardiovascular disorders, as well as cancers. Key Concepts The ribosome is a large macromolecular assembly dedicated to synthesising all proteins in all cells. The ribosome in all domains of life is made of a small and a large subunit. The small subunit decodes the genetic code and translate it into the sequence of amino acids that form a protein. The large subunit is responsible for the peptide bond formation that links the amino acids in a functional protein. The three core mechanisms of protein synthesis, including decoding and catalysis of peptide bond formation are performed by ribosomal ribonucleic acid (RNA). The ribosome also contains 55–80 proteins. During ribosomal assembly, the ribosomal proteins drive folding of ribosomal ribonucleic acid (rRNA). In the mature ribosome, ribosomal proteins participate in the translation process, binding of translation factors and tuning ribosomal properties including translation fidelity. Ribosomal proteins are also a useful tool to study how cellular proteins acquired their ability to fold over geological timescales.
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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 | 0.001 | 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".