Welcome to SOAP’s documentation!¶
Installation¶
Install required packages defined in envConfig.py (
detailed instructions).Copy envConfig.py to env.py and modify it to work with your setup.
Basic workflow to generate a statistical potential¶
Preprocess PDB if necessary and generate sequence files.
Prepare decoys.
Run SOAP script to select models.
Run SOAP script to calculate the optimal statistical potential using the best model.
Write out the optimal potential in hdf5 or lib format for use in Modeller, IMP or other packages.
Examples:
Additonal undocumented examples can be found at SOAP/examples.
Pre-calculated SOAP tables¶
Pre-calculated SOAP statistical potentials for ranking peptides, loops, proteins, protein interfaces and ligands can be found at : salilab.org/SOAP
Modules:¶
- Environmental variables
- Job scheduler (local and on SGE cluster)
- Select the best model and generate statistical potentials
- Collection of sequences for known structures or decoys
- Decoys
- Definition of MDT features
- Calculate statistics from a set of structures
- Recovery Functions
- Structures/Decoys scores
- Structure Refinement using SOAP
- Benchmark SOAP’s performance using a set of criteria
- Combined scores from multiple scoring terms
- Optimize and sample the parameters in SOAP
- Cross Validation of a model
- Loop modeling
- Utility classes and functions
Please cite:¶
Dong GQ, Fan H, Schneidman-Duhovny D, Webb B, Sali A. Optimized atomic statistical potentials: assessment of protein interfaces and loops. Bioinformatics. 2013 Dec 15; 29(24):3158-66.