MODPROPEP

MODPROPEP models protein-peptide complexes using knowledge-based templates to analyze peptide binding to major histocompatibility complex (MHC) proteins and protein kinases.

Key Features:

• Template-Based Modeling: Uses Protein Data Bank (PDB) crystal structures of protein-peptide complexes as templates to position peptide backbones within MHC and kinase substrate-binding pockets.
• Side-Chain Conformation Prediction: Predicts peptide side-chain conformations using SCWRL.
• Contact Analysis: Calculates inter-molecular contacts between peptide ligands and binding pockets to provide insights into substrate specificity.
• Predictive Scoring: Identifies potential MHC-binding peptides in antigen sequences and predicts kinase phosphorylation sites by scoring inter-molecular contacts using residue-based statistical pair potentials.

Scientific Applications:

• Structural Biology: Elucidates the structural basis of substrate specificity for MHCs and kinases by modeling protein-peptide interactions.
• Immunology: Supports identification of antigenic peptides that bind to MHC molecules for vaccine development and immunotherapy research.
• Signal Transduction Research: Predicts phosphorylation sites on substrates to inform studies of kinase-mediated signaling pathways.

Methodology:

Uses known protein-peptide complex structures as templates, models peptide backbones to match template conformations, predicts side-chain conformations with SCWRL, and scores inter-molecular contacts using residue-based statistical pair potentials.