ProteaseGuru

ProteaseGuru performs in silico protease digestion and comparative peptide analysis to guide protease selection for bottom-up proteomics, informing peptide profiles for LC-MS-based peptide identification and post-translational modification assessment.

Key Features:

• In Silico Digestion: Performs in silico digestion of protein sequences for candidate proteases to evaluate expected peptide products for targeted proteins and complex proteomes.
• Comprehensive Peptide Information: Generates theoretical peptide sequences and computes biophysical properties relevant to LC-MS analysis.
• Data Visualization and Comparison: Produces histograms and sequence coverage maps and supports comparison of shared and unique peptides across proteases.
• Results Summaries: Provides summaries of key metrics including counts of shared and unique peptides per protease.
• Application Examples: Applicable to analyses of variant-containing proteins, multi-database studies such as human:mouse xenograft models, and microbiome metaproteomics.

Scientific Applications:

• Targeted Protein Studies: Evaluates protease choices for single or small sets of proteins to optimize peptide generation for LC-MS detection.
• Proteome-wide Analyses: Assesses protease performance across complex proteomes to optimize sequence coverage and peptide observability.
• Variant-containing Protein Analysis: Predicts proteolytic peptides that include sequence variants to support analysis of variant-containing proteins in the human proteome.
• Human:Mouse Xenograft Proteomics: Enables comparison across proteomic databases for human:mouse xenograft model analyses.
• Microbiome Metaproteomics: Supports protease selection for metaproteomic analyses of microbiome samples.

Methodology:

Performs in silico digestion of input protein sequences, generates theoretical peptide sequences with biophysical properties, creates histograms and sequence coverage maps, and compares peptide sets across candidate proteases to identify shared and unique peptides for LC-MS-based bottom-up proteomics.