SwarmDock
SwarmDock performs flexible protein-protein docking to generate three-dimensional models of protein complexes and characterize binding interfaces using normal modes to account for conformational changes.
Key Features:
- Flexible Protein-Protein Docking: Models protein complexes with flexibility, accommodating conformational changes that occur during binding.
- Normal Modes Analysis: Integrates normal modes analysis to simulate protein dynamics and flexibility within the docking algorithm.
- PDB Input Processing: Processes uploaded PDB files of the binding partners as input for docking calculations.
- Low-Energy Conformation Generation: Generates low-energy conformations and corresponding structural models of docked complexes.
- Clustering and Ranking of Docking Poses: Produces a ranked list of clustered docking poses and their corresponding structures.
- Focused Docking Options: Supports full global docking or focused docking concentrated on specified residues implicated in binding.
Scientific Applications:
- Structural modeling of protein-protein interactions: Produces atomic-level models to elucidate interaction mechanisms between proteins.
- Binding site characterization: Identifies and refines binding residues and interaction interfaces for downstream analysis.
- Drug discovery and therapeutic development: Provides structural insights into protein complexes that can inform drug design and therapeutic targeting.
Methodology:
Uses the SwarmDock flexible docking algorithm integrating normal modes analysis; processes PDB input to generate low-energy conformations, clusters docking poses, and returns a ranked list of poses and corresponding structures.
Topics
Details
- Tool Type:
- command-line tool
- Operating Systems:
- Linux, Windows, Mac
- Added:
- 12/18/2017
- Last Updated:
- 4/19/2023
Operations
Data Inputs & Outputs
Protein docking
Publications
Torchala M, Moal IH, Chaleil RAG, Fernandez-Recio J, Bates PA. SwarmDock: a server for flexible protein–protein docking. Bioinformatics. 2013;29(6):807-809. doi:10.1093/bioinformatics/btt038.