The following API services are provided by Cyrus:
Antibody HM creates homology models of antibodies using the Cyrus NextGen Antibody structure prediction method.
This method takes as input an antibody heavy and light chain and returns models of the antibody fV fragment. The Single Chain HM API is a more suitable approach for modeling nanobodies and non-antibody proteins.
DDG is a tool for predicting the energetic consequences of single mutations. It approximates the Gibbs free energy change of folding of the native vs. point mutant.
Disulfidizer is a tool for searching for disulfides. Given an input structure it will attempt to sample disulfides that might exist. This is appropriate for:
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Disulfidizer results are reasonably polished (if the –permissive flag is not used), but you may wish to further evaluate disulfides with other computational tools before proceeding to a wet experiment.
Epitope Scan runs an rosetta MHC II epitope prediction algorithm on an input protein structure or sequence. This API uses a machine learning model to predict epitopes based entirely on the sequence of the protein. Structure input is provided as a convenience but the API will produce identical results regardless of whether a sequence or structure is used as input.
Force Disulfide forces the input disulfide to exist and attempts to relax the protein structure in the presence of that chemical bond (simulated as bond-like restraint, not a kinematic imperative). It requires the user to state which disulfides are desired. This tool is appropriate in three cases:
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Force disulfide results should always be considered preliminary and evaluated with/after other modeling tools.
Loop modeling runs the Rosetta Next Generation KIC loop modeling protocol. This API is useful for modeling loops of between 5 and 17 residues. This tool is suitable for resampling the conformations of existing loops. It is the same underlying tool as our Loop Rebuild Action in Bench; that tool’s documentation contains more details.
Relax 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.
Single Chain HM is a homology modeling tool for generating a structure prediction for your sequence optimizing structures. This tool adds an additional feature to tell Rosetta where extra disulfides are wanted by the researcher, to cover cases where the templates were not clear. This is appropriate for:
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Results from Single Chain HM should be considered gold standard results from Rosetta. Further modeling never hurts but is not strictly necessary.
Solubility Scoring predicts the solubility of a protein structure using a method similar to the AGGRESCAN method. This is a structure based method and requires a protein model as input, a high quality homology model generated by the Single Chain HM method is an acceptable input to the Solubility Scoring tool.
Template Predictorruns blast, sparksX, and hhsearch, and returns alignment information which can be useful in determining how well homology modeling will work for the given target.