PeSA

PeSA analyzes peptide arrays, permutation arrays, and One-Probe Arrays with Labeled peptides (OPALs) to generate motifs and position-specific scoring matrices (PSSMs) for peptide specificity studies, supporting interpretation of protein-protein interactions, enzyme-substrate specificity, and epigenetic modification sites.

Key Features:

• Motif generation (PSSMs): Generates position-specific scoring matrices that represent candidate interaction motifs from peptide data.
• Array type support: Processes data from peptide arrays, permutation arrays, and One-Probe Arrays with Labeled peptides (OPALs).
• Frequency-based model: Identifies residue patterns by analyzing residue occurrence across a provided list of peptides using frequency criteria.
• Weight-based model: Constructs motifs from quantified matrices by assigning positional weights to residues.
• Threshold-based filtering: Populates lists of peptides that match predefined thresholds derived from quantified matrices.

Scientific Applications:

• Protein-protein interaction analysis: Identifies candidate interaction motifs relevant to PPIs from peptide array experiments.
• Enzyme-substrate specificity: Characterizes positional residue preferences that inform enzyme substrate recognition and specificity.
• Epigenetic modification site analysis: Aids detection of motifs associated with epigenetic modification sites.
• Peptide specificity studies: Supports discovery of candidate motifs and specificity determinants from peptide array datasets.

Methodology:

Generates PSSMs; applies a frequency-based model that analyzes residue occurrence across peptide lists; applies a weight-based model that uses quantified matrices to compute positional weights; and performs threshold-based filtering to select peptides meeting predefined criteria.