Method for Identifying Nonspecific Protein−Protein Interactions in Nanoelectrospray Ionization Mass Spectrometry
Bibliographic record
Abstract
The nonspecific self-association of proteins in nanoflow electrospray ionization mass spectrometry (nanoES-MS), and the influence of experimental conditions thereon, are investigated using the protein ubiquitin (Ubq) as a model system. Extents of nonspecific protein association generally increase with protein concentration and, interestingly, with decreasing ES spray potential. The extent of self-association is also sensitive to the duration of the accumulation event in an external rf hexapole. Notably, the relative abundance of metal (Na+ and K+) adducts generally increases with the size of nonspecific Ubq multimer. This result suggests that the gaseous ions of monomeric and nonspecific multimeric Ubq have, on average, different ES droplet histories, with monomer ions originating earlier in the ES process than the nonspecific multimeric complexes. This finding forms the basis for a new method for distinguishing between specific and nonspecific protein complexes in ES-MS. A reporter molecule (Mrep), which does not bind specifically to the proteins and protein complexes of interest, is added to the ES solution at high concentration. The distribution of Mrep bound nonspecifically to gaseous ions of the proteins and protein complexes, as determined from the ES mass spectrum, is used to determine whether a given protein complex originates in solution or whether it forms from nonspecific binding during the ES process. The method is demonstrated in cases where the ions of protein complexes detected by nanoES-MS originate exclusively from nonspecific association, exclusively from specific interactions in solution, or from both specific and nonspecific interactions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".