Protein–peptide interactions, in which one partner is a globular protein and the other is a flexible linear peptide, are important for understanding cellular processes and regulatory pathways, and are therefore targets for drug discovery. In this study, I combined rigid-body protein-protein docking software (MEGADOCK) and global flexible protein–peptide docking software (CABS-dock) to establish a re-ranking method with amino acid contact profiles using rigid-body sampling decoys. I demonstrate that the correct complex structure cannot be predicted (< 10 Å peptide RMSD) using the current version of CABS-dock alone. However, my newly proposed re-ranking method based on the amino acid contact profile using rigid-body search results (designated the decoy profile) demonstrated the possibility of improvement of predictions. Adoption of my proposed method along with continuous efforts for effective computational modeling of protein–peptide interactions can provide useful information to understand complex biological processes in molecular detail and modulate protein-protein interactions in disease treatment.