Analysis of Novel Interactions between Components of the Selenocysteine Biosynthesis Pathway, SEPHS1, SEPHS2, SEPSECS, and SECp43
Bibliographic record
Abstract
In mammalian cells, the incorporation of the 21st amino acid, selenocysteine, into proteins is guided by the Sec machinery. The function of this protein complex requires several protein-protein and protein-RNA interactions, leading to the incorporation of selenocysteine at UGA codons. It is guided by stem-loop structures localized in the 3' untranslated regions of the selenoprotein-encoding genes. Here, we conducted a global analysis of interactions between the Sec biosynthesis and incorporation components using a bioluminescence resonance energy transfer assay in mammalian cells that showed that selenocysteine synthase (SEPSECS), SECp43, and selenophosphate synthetases SEPHS1 and SEPHS2 form oligomers in eukaryotic cells. We also showed that SEPHS2 interacts with SEPSECS and SEPHS1; these interactions were confirmed by co-immunoprecipitation. To further analyze the interactions of SECp43, the protein was expressed in Escherichia coli, and small-angle X-ray scattering analysis revealed that it is a globular protein comprising two RNA-binding domains. Using phage display, we identified potential interaction sites and highlighted two residues (K166 and P167) required for its dimerization. The SECp43 structural model presented here constitutes the basis of future exploration of the protein-protein interactions among early components of the selenocysteine biosynthesis and incorporation pathway.
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) | 0.000 | 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) | 0.001 | 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".