An Isotopically Coded CID-cleavable Biotinylated Cross-linker for Structural Proteomics
Bibliographic record
Abstract
Successful application of cross-linking combined with mass spectrometry for structural proteomics demands specifically designed cross-linking reagents to address challenges in the detection and assignment of cross-links. A combination of affinity enrichment, isotopic coding, and cleavage of the cross-linker is beneficial for detection and identification of the peptide cross-links. Here we describe a novel cross-linker, cyanurbiotindipropionylsuccinimide (CBDPS), that allows affinity enrichment of cross-linker-containing peptides with avidin. Affinity enrichment eliminates interfering non-cross-linked peptides and allows the researcher to focus on the analysis of the cross-linked peptides. CBDPS is also isotopically coded and CID-cleavable. The cleaved fragments still contain a portion of the isotopic label and can therefore be distinguished from unlabeled fragments by their distinct isotopic signatures in the MS/MS spectra. This cleavage information has been incorporated into a program for the automatic analysis of the MS/MS spectra of the cross-links. This allows rapid determination of cross-link type in addition to facilitating identification of the individual peptides constituting the interpeptide cross-links. Thus, affinity enrichment combined with isotopic coding and CID cleavage allows in-depth mass spectrometric analysis of the peptide cross-links. We have characterized the performance of CBDPS on the 120-kDa protein heterodimer of HIV reverse transcriptase.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".