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Modeling and docking of antibody structures with Rosetta.
Brian D Weitzner1, Jeliazko R Jeliazkov2, Sergey Lyskov1
1Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
Nature Protocols
|January 27, 2017
Summary
Computational protocols predict antibody 3D structures and antigen docking. RosettaAntibody and SnugDock offer automated or manual options for antibody modeling and antigen complex prediction, aiding drug discovery.
Area of Science:
- Structural Biology
- Computational Biology
- Immunology
Background:
- Accurate prediction of antibody structure and antigen binding is crucial for therapeutic antibody development.
- Computational methods are essential for modeling antibody-antigen interactions due to experimental limitations.
Purpose of the Study:
- To present Rosetta-based computational protocols for antibody 3D structure prediction (RosettaAntibody) and antibody-antigen docking (SnugDock).
- To provide tools for refining antibody models, including loop minimization and CDR H3 loop prediction.
- To enable automated and manual execution of these protocols for broader accessibility.
Main Methods:
- RosettaAntibody utilizes canonical loop conformations and energetic calculations for antibody modeling.
- SnugDock refines antibody-antigen docking by resampling loop conformations and considering conformational ensembles.
- Protocols are available via the ROSIE web server or for local execution.
Main Results:
- The protocols enable prediction of antibody 3D structures from sequence.
- Antibody-antigen docking is achieved by integrating antibody models with antigen structures.
- Model uncertainty is addressed by resampling loop conformations and using multiple models.
Conclusions:
- Rosetta-based protocols offer a robust framework for antibody structure prediction and docking.
- These computational tools can accelerate the design and development of antibody-based therapeutics.
- Automated execution via the ROSIE web server enhances accessibility for researchers.
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