The Relax API runs the Rosetta FastRelax protocol. Quoting from the RosettaCommons documentation: “This finds low-energy backbone and side-chain conformations near a starting conformations by performing many rounds of packing and minimizing, with the repulsive weight in the scoring function gradually increased from a very low value to the normal value from one round to the next.” This is useful for taking a structure not generated by Rosetta and “relaxing” it into the Rosetta scorefunction preparatory to further modeling, or for generating a backbone ensemble for a further modeling experiment.
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Inputs
Input PDB file
CLI argument:
--pdb-file input.pdb
Python submit() argument:
pdb-file=”input.pdb”
Do not include nonprotein residues.
Do not include multimodel (NMR-sourced) PDBs.
Optional – Number of Repeats. The number of different relaxed conformations the loop modeling API will return.
CLI argument:
--repeats 5
Python submit() argument:
repeats=5
Quickstart
Command Line Examples
Create 10 new relaxed models of input.pdb:
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cyrus engine submit relax input.pdb --repeats 10 |
Python Examples
Create 10 new relaxed models of input.pdb:
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from engine.relax.client import RelaxClient
client = RelaxClient()
job_id = client.submit(pdb_path="input.pdb", repeats=10) |
Inputs
--pdb-file
Input PDB file
CLI argument:
--pdb-file input.pdb
Python submit()
...
Outputs
Results can be downloaded if and only if a job has succeeded – DONE state, see the list command below.
- models — A directory of
argument:
pdb-file=”input.pdb”
Do not include nonprotein residues.
Do not include multimodel (NMR-sourced) PDBs.
Options
--repeats
The number of different relaxed conformations the loop modeling API will return.
CLI argument:
--repeats 5
Python submit() argument:
repeats=5
default = 1
Outputs
models
(directory)PDB files with relaxed structures. The models will be in the form input_####.pdb, where #### is an index (0001, increasing).
Note that Rosetta will renumber the residues monotonically starting from 1, contiguous across chains.
score.sc
—A text file containing the Rosetta scores for each generated model.
Output File interpretation
Info |
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Results can be downloaded if and only if a job has succeeded – DONE state |
Model quality can be assessed via scores. Broad documentation on interpreting scores can be found here. The score.sc file is a space-delimited data table, padded for easier reading. It can be parsed with pandas dataframes, excel, or your tool of choice. In the score.sc file, pay particular attention to the total_score column. The total_score is Rosetta’s overall grade for a model. The total_score should have a negative value for good models, although this will depend enormously on the quality of the input model.
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