PatchMAN
PatchMAN maps receptor surfaces with structural motifs to perform receptor-centric blind peptide docking and model near-native peptide–protein complexes from free receptor structures.
Key Features:
- Receptor-centric docking: Shifts from peptide-centered methods to a global, receptor-focused peptide-docking approach that samples peptide binding based on receptor structure.
- Backbone-scaffold motif mapping: Maps the receptor surface using backbone scaffolds extracted from protein structures to identify candidate peptide-binding motifs.
- Sequence-independent conformation sampling: Samples bound peptide conformations based solely on the receptor's structural context without relying on peptide sequence information.
- Motif sourcing from monomers and interfaces: Identifies structural units of peptides within both interfaces and monomeric proteins to expand the motif search space.
- High-resolution near-native identification: On a nonredundant set of protein–peptide complexes starting from free receptor structures, identifies near-native complexes within 2.5 Å/5 Å interface backbone RMSD in 58%/84% of cases and achieves corresponding sampling in 81%/100% of instances.
- Patch-Motif AligNments: Leverages motif alignments (Patch-Motif AligNments) to match receptor surface patches to peptide backbone scaffolds.
Scientific Applications:
- Peptide–protein interaction modeling: Enables modeling of bound peptide conformations and orientations at high resolution.
- Peptide binder design: Provides structural templates and binding modes to inform design of novel peptide binders.
- Mechanistic studies: Facilitates analysis of the principles underlying peptide recognition and peptide–protein associations.
Methodology:
Implements a global, receptor-centric docking approach that maps receptor surfaces using structural motifs and backbone scaffolds extracted from protein structures, samples peptide conformations based on receptor structural context, and identifies near-native complexes assessed by interface backbone RMSD (2.5 Å and 5 Å) starting from free receptor structures.
Topics
Details
- Cost:
- Free of charge
- Tool Type:
- web application
- Operating Systems:
- Mac, Linux, Windows
- Added:
- 7/26/2022
- Last Updated:
- 11/24/2024
Operations
Data Inputs & Outputs
Backbone modelling
Inputs
Outputs
Publications
Khramushin A, Ben-Aharon Z, Tsaban T, Varga JK, Avraham O, Schueler-Furman O. Matching protein surface structural patches for high-resolution blind peptide docking. Proceedings of the National Academy of Sciences. 2022;119(18). doi:10.1073/pnas.2121153119. PMID:35482919. PMCID:PMC9170164.