Practically useful: what the Rosetta protein modeling suite can do for you
In a recent review published in Biochemistry, Kaufmann, Lemmon and DeLuca et al. from the Meiler Lab, cover the Rosetta modeling suite capabilities. More importantly, as supplementary information they provide tutorials to demonstrate 6 basic use cases of Rosetta.
While other reviews have focused on a specific Rosetta functionality, this work briefly reviews the approaches to sampling and scoring used by each of the major Rosetta protocols, specifically sampling strategies for backbone degrees of freedom, and for side chain degrees of freedom, and the knowledge based scoring functions both for centroid (low resolution) and all-atom (high resolution) modes. The paper reviews the following Rosetta applications:
Protein Structure Prediction:
- De Novo folding simulations (for monomeric as well as homomeric proteins)
- Comparative modeling
- Loop modeling
- Model relaxation and refinement
- Performance in the CASP experiment
- Leveraging Sparse Experimental Data from NMR and EPR Experiments
- Assisting in the Determination of Molecular Structures from Electron Diffraction Data
- Rosetta Structure Prediction Servers
Protein-Protein Docking:
- RosettaDock
- Performance in the CAPRI experiment and benchmarking
- SnugDock (antibody docking)
Protein-Ligand Docking:
- RosettaLigand
- Binding Energy Predictions
- Flexibility in Ligand Docking and Docking to Homology Models
Protein Design:
- RosettaDesing
- De Novo Protein Design
- Redesign of existing proteins
- Protein-Protein interface design
- Enzyme Design (RosettaMatch)
As supplementary information 6 tutorials are included to show case basic Rosetta use cases. These are intended for the novice user and can be attenuated for more advanced scenarios.
- protein folding
- refinement
- loop modeling
- protein?protein docking
- small molecule docking
- protein design.
Kaufmann KW, Lemmon GH, Deluca SL, Sheehan JH, & Meiler J (2010). Practically useful: what the Rosetta protein modeling suite can do for you. Biochemistry, 49 (14), 2987-98 PMID: 20235548
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