Nonspecific interactions between proteins and charged biomolecules in electrospray ionization mass spectrometry
Bibliographic record
Abstract
An investigation of the nonspecific association of small charged biomolecules and proteins in electrospray ionization mass spectrometry (ES-MS) is described. Aqueous solutions containing pairs of proteins and a small acidic or basic biomolecule that does not interact specifically with either of the proteins were analyzed by ES-MS and the distributions of the biomolecules bound nonspecifically to each pair of proteins compared. For the basic amino acid arginine and the peptide RGVFRR, nonequivalent distributions were measured in positive ion mode, but equivalent distributions were measured in negative ion mode. In the case of uridine 5'-diphosphate, nonequivalent distributions were measured in negative ion mode, but equivalent distributions observed in positive ion mode. The results of dissociation experiments performed on the gaseous ions of the nonspecific complexes suggest that the nonequivalent distributions result from differences in the extent to which the nonspecific complexes undergo in-source dissociation. To test this hypothesis, the distributions of nonspecifically bound basic molecules measured in the presence of imidazole, which protects complexes from in-source dissociation, were compared. In all cases, equivalent distributions were obtained. The results indicate that nonspecific binding of charged molecules to proteins during ES is a statistical process, independent of protein structure and size. However, the kinetic stabilities of the nonspecific interactions are sensitive to the nature of the protein ions. It is concluded that the reference protein method for correcting ES mass spectra for nonspecific ligand-protein binding can be applied to the analysis of ionic ligands, provided that in-source dissociation of the nonspecific interactions is minimized.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".