ArticleMolecular & cellular proteomics : MCP2024
CLIPPER 2.0: Peptide-Level Annotation and Data Analysis for Positional Proteomics.
Article in Molecular & cellular proteomics : MCP, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Degradomics for large-scale mechanistic insights on proteases and proteolysis in human health.The FEBS journal · 2026Review
- Data Processing and Analysis in Positional Proteomics.Proteomics · 2025Review
- Relaxation of mucosal fibronectin fibers in late gut inflammation following neutrophil infiltration in mice.npj biological physics and mechanics · 2025Article
- Proteomic insights into the extracellular matrix: a focus on proteoforms and their implications in health and disease.Expert review of proteomics · 2024Review
- Substrate O-glycosylation actively regulates extracellular proteolysis.Protein science : a publication of the Protein Society · 2024Article
- Peptidomic analysis of endogenous and bacterial protease activity in human plasma and wound fluids.iScience · 2024Article
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Authors and funding
7 authors.
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Abstract
Positional proteomics methodologies have transformed protease research, and have brought mass spectrometry (MS)-based degradomics studies to the forefront of protease characterization and system-wide interrogation of protease signaling. Considerable advancements in both sensitivity and throughput of liquid chromatography (LC)-MS/MS instrumentation enable the generation of enormous positional proteomics datasets of natural and protein termini and neo-termini of cleaved protease substrates. However, concomitant progress has not been observed to the same extent in data analysis and post-processing steps, arguably constituting the largest bottleneck in positional proteomics workflows. Here, we present a computational tool, CLIPPER 2.0, that builds on prior algorithms developed for MS-based protein termini analysis, facilitating peptide-level annotation and data analysis. CLIPPER 2.0 can be used with several sample preparation workflows and proteomics search algorithms and enables fast and automated database information retrieval, statistical and network analysis, as well as visualization of terminomic datasets. We demonstrate the applicability of our tool by analyzing GluC and MMP9 cleavages in HeLa lysates. CLIPPER 2.0 is available at https://github.com/UadKLab/CLIPPER-2.0.
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