Identification of Inositol Phosphate or Phosphoinositide Interacting Proteins by Affinity Chromatography Coupled to Western Blot or Mass Spectrometry
Bibliographic record
Abstract
Inositol phosphates and phosphoinositides regulate several cellular processes in eukaryotes, including gene expression, vesicle trafficking, signal transduction, metabolism, and development. These metabolites perform this regulatory activity by binding to proteins, thereby changing protein conformation, catalytic activity, and/or interactions. The method described here uses affinity chromatography coupled to mass spectrometry or Western blotting to identify proteins that interact with inositol phosphates or phosphoinositides. Inositol phosphates or phosphoinositides are chemically tagged with biotin, which is then captured via streptavidin conjugated to agarose or magnetic beads. Proteins are isolated by their affinity of binding to the metabolite, then eluted and identified by mass spectrometry or Western blotting. The method has a simple workflow that is sensitive, non-radioactive, liposome-free, and customizable, supporting the analysis of protein and metabolite interaction with precision. This approach can be used in label-free or in amino acid-labelled quantitative mass spectrometry methods to identify protein-metabolite interactions in complex biological samples or using purified proteins. This protocol is optimized for the analysis of proteins from Trypanosoma brucei, but it can be adapted to related protozoan parasites, yeast or mammalian cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".