Low-Energy Collision-Induced Dissociation Fragmentation Analysis of Cysteinyl-Modified Peptides
Bibliographic record
Abstract
The development of methods to chemically modify and isolate cysteinyl-residue-containing peptides (Cys-peptides) for LC-MS/MS analysis has generated considerable interest in the field of proteomics. Methods using isotope-coded affinity tags (ICAT) and (+)-biotinyl-iodoacetamidyl-3,6-dioxaoctanediamine (iodoacetyl-PEO-biotin) employ similar Cys-modifying reagents that contain a thiolate-specific biotin group to modify and isolate Cys-containing peptides in conjunction with immobilized avidin. For these strategies to be effective on a proteome-wide level, the presence of the ICAT or acetyl-PEO-biotin tag should not interfere with the efficiency of induced dissociation in MS/MS experiments or with the identification of the modified Cys-peptides by automated database searching algorithms. We have compared the collision-induced dissociation (CID) fragmentation patterns of peptides labeled with iodoacetyl-PEO-biotin and the ICAT reagent to those of the unmodified peptides. CID of Cys-peptides modified with either reagent resulted in the formation of ions attributed to the modified Cys-peptides as well as those unique to the labeling reagent. As demonstrated by analyzing acetyl-PEO-biotin labeled peptides from ribonuclease A and the ICAT-labeled proteome of Deinococcus radiodurans, the presence of these label-specific product ions provides a useful identifier to discern whether a peptide has been modified with the Cys-specific reagent, especially when a number of peptides analyzed using these methods do not contain a modified Cys residue, and to differentiate identical Cys-peptides labeled with either ICAT-d0 or ICAT-d8.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".