Informed-Proteomics

Informed-Proteomics performs top-down proteomics analysis of intact proteins from liquid chromatography-tandem mass spectrometry (LC-MS/MS) data to identify and quantify proteoforms while preserving post-translational modifications, isoforms, and proteolytic processing.

Key Features:

• LC-MS feature-finding algorithm: Identifies features within LC-MS/MS data to manage the complexity of top-down mass spectra.
• Database search algorithm: Compares experimental spectra against theoretical models in databases to facilitate proteoform identification.
• Proteoform preservation: Retains information about post-translational modifications, isoforms, and proteolytic processing for proteoform-level characterization.
• Support for complex biological samples: Handles complex LC-MS/MS datasets including human-in-mouse xenograft luminal and basal breast tumor samples.

Scientific Applications:

• Disease biomarker discovery: Enables detailed proteoform characterization, including post-translational modifications and isoforms, for biomarker studies.
• Therapeutic target characterization: Supports identification and quantification of proteoforms relevant to therapeutic target validation.
• Biological pathway elucidation: Facilitates pathway studies by resolving proteoform-level differences.
• Comparative proteomics in xenograft tumors: Applied to human-in-mouse xenograft luminal and basal breast tumor samples to characterize proteoform-level differences and complement bottom-up analysis.

Methodology:

Integrates LC-MS feature-finding and database search algorithms to identify and quantify proteoforms from complex LC-MS/MS datasets.