Human mitochondrial import receptor Tom70 functions as a monomer
Bibliographic record
Abstract
The mitochondrial import receptor Tom70 (translocase of the mitochondrial outer membrane 70) interacts with chaperone-preprotein complexes through two domains: one that binds Hsp70 (heat-shock protein 70)/Hsc70 (heat-shock cognate 70) and Hsp90, and a second that binds preproteins. The oligomeric state of Tom70 has been controversial, with evidence for both monomeric and homodimeric forms. In the present paper, we report that the functional state of human Tom70 appears to be a monomer with mechanistic implications for its function in mitochondrial protein import. Based on analytical ultracentrifugation, cross-linking, size-exclusion chromatography and multi-angle light scattering, we found that the soluble cytosolic fragment of human Tom70 exists in equilibrium between monomer and dimer. A point mutation introduced at the predicted dimer interface increased the percentage of monomeric Tom70. Although chaperone docking to the mutant was the same as to the wild-type, the mutant was significantly more active in preprotein targeting. Cross-linking also demonstrated that the mutant formed stronger contacts with preprotein. However, cross-linking of full-length wild-type Tom70 on the mitochondrial membrane showed little evidence of homodimers. These results indicate that the Tom70 monomers are the functional form of the receptor, whereas the homodimers appear to be a minor population, and may represent an inactive state.
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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 | 0.000 |
| 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 | 0.001 |
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".