Identification of Novel Interacting Protein Partners of SMN Using Tandem Affinity Purification
Bibliographic record
Abstract
Mutations in the survival motor neuron (SMN) gene cause spinal muscular atrophy (SMA), a neuromuscular disease associated with muscle weakness that progresses to paralysis, respiratory distress, and ultimately death. Both neurons and muscle are severely affected in this disease. Tandem affinity purification (TAP) has emerged as a useful tool for studying protein complexes in vitro. We have used this purification system to discover novel SMN interacting partners in C2C12 muscle and PC12 neuronal cells. To do so, we fused a TAP-tag, consisting of a HIS hexamer and FLAG epitope separated by the tobacco etch virus (TEV) protease cleavage site, to either the N- or C-terminal region of SMN. Interestingly, the profile of SMN interacting proteins varies depending on the cell type and stage. We have identified a number of novel SMN interacting proteins in both C2C12 and PC12 cells, and from among these we have validated Annexin II and myosin regulatory light chain (MRLC). The discovery of these proteins will lead to a better understanding of the mechanisms underlying the pathophysiology of SMA.
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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".