PepPre

PepPre detects peptide precursor ions by decomposing peaks into multiple isotope clusters using linear programming methods, enabling improved peptide and protein identification from tandem mass spectrometry data.

Key Features:

• Precursor Detection: Decomposes peaks into multiple isotope clusters using linear programming methods to detect accurate and comprehensive peptide precursor ions.
• Precursor Scoring and Ranking: Scores and ranks detected precursors, selecting high-scoring precursors for subsequent peptide identification.
• Multiple Precursors per Spectrum: Considers multiple precursors per spectrum to substantially improve both the number of identifications and spectrum explainability.
• Cross-linked Peptide Support: Evaluated and validated on both regular peptide and cross-linked peptide data sets.
• Wide-window Data Acquisition Compatibility: Enables identification of at least 64% more PSMs when the isolation window is widened from 2 to 8 Th.

Scientific Applications:

• Regular Peptide Identification: Increases PSMs by 203% and peptide identifications by 68% compared to instrument software for regular peptides.
• Cross-linked Peptide Identification: Increases PSMs by 99% and peptide pair identifications by 27% for cross-linked peptides compared to instrument software.
• Search Space Reduction: Derives advantages for identification engines through credible and detailed precursors that reduce the search space.
• Wide-window Mass Spectrometry: Demonstrates potential advantages of wide-window data acquisition strategies for proteomics experiments.

Methodology:

PepPre detects precursors by decomposing peaks into multiple isotope clusters using linear programming methods. The detected precursors are scored and ranked, and high-scoring precursors are used for subsequent peptide identification.