Quantifying Protein-Fatty Acid Interactions Using Electrospray Ionization Mass Spectrometry
Bibliographic record
Abstract
The application of the direct electrospray ionization mass spectrometry (ESI-MS) assay to quantify interactions between bovine β-lactoglobulin (Lg) and a series of fatty acids (FA), CH(3)(CH(2))(x)COOH, where x=6 (caprylic acid, CpA), 8 (capric acid, CA), 10 (lauric acid, LA), 12 (myristic acid, MA), 14 (palmitic acid, PA) and 16 (stearic acid, SA), is described. Control ESI-MS binding measurements performed on the Lg-PA interaction revealed that both the protonated and deprotonated gas phase ions of the (Lg + PA) complex are prone to dissociate in the ion source, which leads to artificially small association constants (K (a)). The addition of imidazole, a stabilizing solution additive, at high concentration (10 mM) increased the relative abundance of (Lg + PA) complex measured by ESI-MS in both positive and negative ion modes. The K(a) value measured in negative ion mode and using sampling conditions that minimize in-source dissociation is in good agreement with a value determined using a competitive fluorescence assay. The K (a) values measured by ESI-MS for the Lg interactions with MA and SA are also consistent with values expected based on the fluorescence measurements. However, the K (a) values measured using optimal sampling conditions in positive ion mode are significantly lower than those measured in negative ion mode for all of the FAs investigated. It is concluded that the protonated gaseous ions of the (Lg + FA) complexes are kinetically less stable than the deprotonated ions. In-source dissociation was significant for the complexes of Lg with the shorter FAs (CpA, CA, and LA) in both modes and, in the case of CpA, no binding could be detected by ESI-MS. The affinities of Lg for CpA, CA, and LA determined using the reference ligand ESI-MS assay, a method for quantifying labile protein-ligand complexes that are prone to in-source dissociation, were found to be in good agreement with reported values.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".