Development and Characterization of a Fluorinated MS-Cleavable Cross-Linker for Structural Proteomics
Bibliographic record
Abstract
Cross-linking mass spectrometry (XL-MS) is an important method for studying three-dimensional protein structures and mapping protein-protein interactions. Some limitations of XL-MS still consist of its use for in-cell and in vivo applications. To date, cross-linking reagents are urgently needed that can efficiently penetrate the cell membrane to comprehensively map protein-protein interaction networks in intact cells. In this study, the fluorinated MS-cleavable cross-linker bis(pentafluorophenyl) ureido-4,4'-dibutyrate (DPFU) is described. DPFU is based on the MS-cleavable cross-linker disuccinimidyl dibutyric urea (DSBU) with the aim of balancing the hydrophobicity and solubility to improve membrane permeability. DPFU was evaluated for its solubility behavior in different detergent solutions to optimize conditions for its potential application in live cells. Using bovine serum albumin (BSA) as a model protein, XL-MS experiments were conducted across different temperatures and cross-linker concentrations. Solubility assays identified sodium dodecyl sulfate (SDS) as effective for enhancing DPFU solubility in an aqueous environment. DPFU yielded fewer cross-links for BSA than DSBU, highlighting limitations regarding its cross-linking efficiency under similar experimental conditions. This study provides the first insights into fluorinated cross-linkers, suggesting that further optimization is needed for a broader application of DPFU for future in-cell XL-MS studies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".