Broad Coverage Identification of Multiple Proteolytic Cleavage Site Sequences in Complex High Molecular Weight Proteins Using Quantitative Proteomics as a Complement to Edman Sequencing
Bibliographic record
Abstract
Proteolytic processing modifies the pleiotropic functions of many large, complex, and modular proteins and can generate cleavage products with new biological activity. The identification of exact proteolytic cleavage sites in the extracellular matrix laminins, fibronectin, and other extracellular matrix proteins is not only important for understanding protein turnover but is needed for the identification of new bioactive cleavage products. Several such products have recently been recognized that are suggested to play important cellular regulatory roles in processes, including angiogenesis. However, identifying multiple cleavage sites in extracellular matrix proteins and other large proteins is challenging as N-terminal Edman sequencing of multiple and often closely spaced cleavage fragments on SDS-PAGE gels is difficult, thus limiting throughput and coverage. We developed a new liquid chromatography-mass spectrometry approach we call amino-terminal oriented mass spectrometry of substrates (ATOMS) for the N-terminal identification of protein cleavage fragments in solution. ATOMS utilizes efficient and low cost dimethylation isotopic labeling of original N-terminal and proteolytically generated N termini of protein cleavage fragments followed by quantitative tandem mass spectrometry analysis. Being a peptide-centric approach, ATOMS is not dependent on the SDS-PAGE resolution limits for protein fragments of similar mass. We demonstrate that ATOMS reliably identifies multiple proteolytic sites per reaction in complex proteins. Fifty-five neutrophil elastase cleavage sites were identified in laminin-1 and fibronectin-1 with 34 more identified by matrix metalloproteinase cleavage. Hence, our degradomics approach offers a complimentary alternative to Edman sequencing with broad applicability in identifying N termini such as cleavage sites in complex high molecular weight extracellular matrix proteins after in vitro cleavage assays. ATOMS can therefore be useful in identifying new cleavage products of extracellular matrix proteins cleaved by proteases in pathology for bioactivity screening.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".