Systematic Characterization of the Protein Interaction Network and Protein Complexes in Saccharomyces cerevisiae Using Tandem Affinity Purification and Mass Spectrometry
Bibliographic record
Abstract
Defining protein complexes is a vital aspect of cell biology because cellular processes are often carried out by stable protein complexes and their characterization often provides insights into their function. Accurate identification of the interacting proteins in macromolecular complexes is easiest after purification to near homogeneity. To this end, the tandem affinity purification (TAP) system with subsequent protein identification by high-throughput mass spectrometry was developed (1, 2) to systematically characterize native protein complexes and transient protein interactions under near-physiological conditions. The TAP tag containing two adjacent affinity purification tags (calmodulin-binding peptide and Staphylococcus aureus protein A) separated by a tobacco etch virus (TEV) protease cleavage site is fused with the open reading frame of interest. Using homologous recombination, a fusion library was constructed for the yeast Saccharomyces cerevisiae (3) in which the carboxy-terminal end of each predicted open reading frame is individually tagged in the chromosome so that the resulting fusion proteins are expressed under the control of their natural promoters (3). In this chapter, an optimized protocol for systematic protein purification and subsequent mass spectrometry-based protein identification is described in detail for the protein complexes of S. cerevisiae (4-6).
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".