Strategic Template Filtering Accelerates Fragment-Based Peptide Docking

Peptide–protein interactions are often transient and structurally elusive, necessitating computational approaches to identify both binding sites and peptide conformations. PatchMAN, one of the leading but computationally expensive biophysic-based global peptide-docking protocols, addresses this challenge by treating peptide docking as a protein-folding problem, using structural motifs from solved monomer structures as templates that are subsequently refined using Rosetta FlexPepDock. Here we present PatchMAN2, which introduces (1) strategic fragment filtering and (2) local docking modes that focus sampling on relevant surfaces or known binding regions, thereby reducing the high computational cost of the original implementation due to extensive refinement of many nonproductive low-quality fragments. Benchmarking shows that PatchMAN2 removes ∼30–70% of unnecessary fragments while preserving accuracy, substantially reducing runtime and improving the practical efficiency of peptide–protein docking.