SPECTRUM

SPECTRUM analyzes Top-Down Proteomics (TDP) high-resolution mass spectrometry data to identify, characterize, and quantify intact proteins and their post-translational modifications.

Key Features:

• MS2-based Intact Protein Mass Tuning: Calibrates intact protein masses using MS2 spectra to improve mass measurement accuracy.
• De Novo Peptide Sequence Tag Analysis: Generates and analyzes de novo peptide sequence tags for identification without prior database sequences.
• Propensity-driven PTM Characterization: Applies a propensity-based approach to characterize post-translational modifications (PTMs).
• Blind PTM Search: Performs blind searches to discover previously unidentified PTMs in spectra.
• Spectral Comparison: Compares MS/MS spectra to support validation and refinement of identifications.
• Identification of Truncated Proteins: Detects truncated proteoforms from TDP spectra.
• Multifactorial Coefficient-weighted Scoring: Integrates multiple factors into a coefficient-weighted scoring scheme to rank identifications.

Scientific Applications:

• Proteoform Identification and Characterization: Identifies intact proteoforms and characterizes sequence and modification states from TDP MS data.
• PTM Discovery and Localization: Discovers and localizes post-translational modifications, including unknown PTMs via blind search and propensity modeling.
• Quantitation of Intact Proteins: Supports quantitation of intact proteins using high-resolution mass spectrometry measurements.
• Detection of Truncated Proteins: Identifies truncated proteins and proteoforms in complex samples.

Methodology:

Implemented in MATLAB and using MS2-based intact protein mass tuning, de novo peptide sequence tag analysis, propensity-driven PTM characterization, blind PTM search, spectral comparison, identification of truncated proteins, and a multifactorial coefficient-weighted scoring system.