In silico analysis of coevolution among ERMES proteins, Pex11, and Lam6
Bibliographic record
Abstract
In eukaryotic cells, communication and dynamic interactions among different organelles are important for maintaining cellular homeostasis. The endoplasmic reticulum (ER) mitochondria encounter structure (ERMES) complex establishes membrane contact sites between ER and mitochondria and is essential for phospholipid transport, protein import, and mitochondrial dynamics and inheritance. In this work, in silico analyses were used to probe the intramolecular interactions in ERMES proteins and the interactions that support the ERMES complex. Based on mutual information (MI), sites of intramolecular coevolution are predicted in the core proteins Mmm1, Mdm10, Mdm12, Mdm34, the peroxisomal protein Pex11, and cytoplasmic Lam6; these sites are linked to structural features of the proteins. Intermolecular coevolution is predicted among the synaptotagmin-like mitochondrial lipid-binding protein (SMP) domains of Mmm1, Mdm12, and Mdm34. Segments of Pex11 and Lam6 also share MI with the SMP domains of Mmm1 and Mdm12 and with the N terminus of Mdm34, implicating Mdm34 as part of a hub for interactions between ERMES and other complexes. In contrast, evidence of limited intermolecular coevolution involving the outer membrane protein Mdm10 was detected only with Mmm1 and Pex11. The results support models for the organization of these interacting proteins and suggest roles for Pex11 and Lam6 in regulating complex formation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".