IsobaricQuant

IsobaricQuant quantifies peptides labeled with isobaric mass tags (iTRAQ and TMT) to improve accuracy of MS-based quantitative proteomics by addressing precursor interference from co-isolation of co-eluting precursors with similar mass-to-charge ratios.

Key Features:

• Isobaric tag support: Supports quantification of peptides labeled with iTRAQ and TMT isobaric mass tags.
• Acquisition strategies: Supports both MS2 and MS3 acquisition strategies for reporter-ion–based quantification.
• Visualization of interference: Provides a viewer for visual assessment of precursor interference caused by co-isolated or co-eluting precursors.
• Quality-control scoring: Implements several QC scores to detect scans affected by compression and other factors that reduce quantitative accuracy.
• Scan filtering: Applies QC-based filtering at MS2 and MS3 levels to remove unreliable scans prior to quantification.
• Quantitative accuracy: Demonstrated to reduce protein coefficient of variation (CV) and produce accurate quantifications relative to commonly used software.
• Improved sensitivity: QC-score filtering has been shown to increase sensitivity for identifying protein targets of kinase inhibitors in a PISA dataset.

Scientific Applications:

• High-throughput quantitative proteomics: Enables reporter-ion–based quantification in complex biological samples requiring accurate peptide and protein-level measurements.
• Drug target identification: Enhances detection of protein targets of kinase inhibitors, as demonstrated with a PISA dataset.
• Biomarker discovery and interaction studies: Supports applications in drug discovery, biomarker identification, and characterization of protein interactions that depend on precise isobaric quantification.

Methodology:

Performs reporter-ion quantification of iTRAQ and TMT-labeled peptides using MS2 and MS3 data, enables visual assessment of precursor interference, computes QC scores to identify scans affected by compression, and filters scans at MS2/MS3 levels to reduce protein CVs; performance has been compared against commonly used software.